diff --git a/.github/workflows/dev.yml b/.github/workflows/dev.yml
index 42e8e755..a0aa15c1 100644
--- a/.github/workflows/dev.yml
+++ b/.github/workflows/dev.yml
@@ -21,8 +21,9 @@ jobs:
         python-version:
           - "3.8"
           - "3.9"
-          - "3.10"
-          - "3.11"
+          # Support for Python 3.10 and 3.11 is temproarily disabled
+          # - "3.10"
+          # - "3.11"
     steps:
       - uses: actions/checkout@v3
       - name: Set up Python ${{ matrix.python-version }}
diff --git a/.gitignore b/.gitignore
index 14aa1c4b..cfc9de0f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -75,10 +75,6 @@ docs/_build/
 # PyBuilder
 target/
 
-# Jupyter Notebook
-.ipynb_checkpoints
-*.ipynb
-
 # IPython
 profile_default/
 ipython_config.py
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index bc5da0e1..04995990 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -139,6 +139,25 @@ This package has a `src/agoradatatools/etl/transform` submodule.  This folder ho
     - Use `pytest.mark.parameterize` to loop through multiple datasets in a single test.
     - The class `TestTransformGenesBiodomains` can be used as an example for future tests contibuted.
 
+### Great Expectations
+
+This package uses [Great Expectations](https://greatexpectations.io/) to validate output data.  The `src/agoradatatools/great_expectations` folder houses our file system data context and Great Expectations-specific configuration files. Eventually, our goal is for each `agora-data-tools` output dataset to be convered by an expectation suite. To add data validation for more datasets, follow these steps:
+
+1. Create a new expectation suite by defining the expectations for the new dataset in a Jupyter Notebook inside the `gx_suite_definitions` folder. Use `metabolomics.ipynb` as an example. You can find a catalog of existing expectations [here](https://greatexpectations.io/expectations/).
+1. Run the notebook to generate the new expectation suite. It should populate as a JSON file in the `/great_expectations/expectations` folder.
+1. Add support for running Great Expectations on a dataset by adding the `gx_folder` key to the configuration for the datatset in both `test_config.yaml` and `config.yaml`. The `gx_folder` should be the Synapse ID pointing of a folder where generated HTML reports from Great Expectations for that dataset should be uploaded. If a folder specific to your dataset does not yet exist in the proper locations ([Prod](https://www.synapse.org/#!Synapse:syn52948668), [Testing](https://www.synapse.org/#!Synapse:syn52948670)), create folders with the same name as the dataset itself and copy the new folders' Synapse IDs to the config files.
+1. Test data processing by running `adt test_config.yaml` and ensure that HTML reports with all expectations are generated and uploaded to the proper folder in Synapse.
+
+#### Custom Expectations
+
+This repository is currently home to three custom expectations that were created for use on `agora-data-tools` datasets:
+
+1. `ExpectColumnValuesToHaveListLength`: checks to see if the lists in a particular column are the length that we expect.
+1. `ExpectColumnValuesToHaveListMembers`: checks to see if the lists in a particular column contain only values that we expect.
+1. `ExpectColumnValuesToHaveListMembersOfType`: checks to see if the lists in a particular column contain members of the type we expect.
+
+These expectations are defined in the `/great_expectations/gx/plugins/expectations` folder. To add more custom expectations, follow the instructions [here](https://docs.greatexpectations.io/docs/guides/expectations/custom_expectations_lp).
+
 ### DockerHub
 
 Rather than using GitHub actions to build and push Docker images to DockerHub, the Docker images are automatically built in DockerHub. This requires the `sagebiodockerhub` GitHub user to be an Admin of this repo. You can view the docker build [here](https://hub.docker.com/r/sagebionetworks/agora-data-tools).
diff --git a/MANIFEST.in b/MANIFEST.in
new file mode 100644
index 00000000..febd446a
--- /dev/null
+++ b/MANIFEST.in
@@ -0,0 +1,2 @@
+# Ensure that /great_expectations and all of its contents are included when the package is installed
+graft src/agoradatatools/great_expectations/
diff --git a/Pipfile.lock b/Pipfile.lock
index 5c529bd9..38e6b6c0 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -16,110 +16,386 @@
         ]
     },
     "default": {
-        "agora-data-tools": {
-            "editable": true,
-            "path": "."
-        },
         "agoradatatools": {
             "editable": true,
             "path": "."
         },
+        "altair": {
+            "hashes": [
+                "sha256:39399a267c49b30d102c10411e67ab26374156a84b1aeb9fcd15140429ba49c5",
+                "sha256:8b45ebeaf8557f2d760c5c77b79f02ae12aee7c46c27c06014febab6f849bc87"
+            ],
+            "markers": "python_version >= '3.7'",
+            "version": "==4.2.2"
+        },
+        "annotated-types": {
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+            ],
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+            "version": "==0.6.0"
+        },
+        "anyio": {
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+            "version": "==4.0.0"
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+            ],
+            "markers": "sys_platform == 'darwin'",
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+        },
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@@ -129,6 +405,76 @@
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@@ -139,11 +485,177 @@
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@@ -153,36 +665,208 @@
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@@ -237,381 +1005,1518 @@
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@@ -822,6 +3233,230 @@
             "markers": "python_version >= '3.7'",
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@@ -854,6 +3528,47 @@
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@@ -862,110 +3577,164 @@
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-                "sha256:fd69666217b62fa5d7c6aa88e507493a34dec4fa20c5bd925e4bc12fce586639"
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+                "sha256:66027d667efe95cc4fa945af59f92c5a02c6f5bb6012bff9e60542c74c75c362",
+                "sha256:66dfbaa7cfa3eb707bbfcd46dab2bc6207b005cbc9caa2199bcbc81d95071a00",
+                "sha256:685f568fa5e627e93f3b52fda002c7ed2fa1800b50ce51f6ed1d572d8ab3e7fc",
+                "sha256:6906c4100a8fcbf2fa735f6059214bb13b97f75b1a61777fcf6432121ef12ef1",
+                "sha256:6a42cd0cfa8ffc1915aef79cb4284f6383d8a3e9dcca70c445dcfdd639d51267",
+                "sha256:6dcfcffe73710be01d90cae08c3e548d90932d37b39ef83969ae135d36ef3956",
+                "sha256:6f6eac2360f2d543cc875a0e5efd413b6cbd483cb3ad7ebf888884a6e0d2e966",
+                "sha256:72554a23c78a8e7aa02abbd699d129eead8b147a23c56e08d08dfc29cfdddca1",
+                "sha256:73870c364c11f03ed072dda68ff7aea6d2a3a5c3fe250d917a429c7432e15228",
+                "sha256:73aa7d98215d39b8455f103de64391cb79dfcad601701a3aa0dddacf74911d72",
+                "sha256:75ea7d0ee2a15733684badb16de6794894ed9c55aa5e9903260922f0482e687d",
+                "sha256:7bd2d7ff69a2cac767fbf7a2b206add2e9a210e57947dd7ce03e25d03d2de292",
+                "sha256:807cc8543a477ab7422f1120a217054f958a66ef7314f76dd9e77d3f02cdccd0",
+                "sha256:8e9723528b9f787dc59168369e42ae1c3b0d3fadb2f1a71de14531d321ee05b0",
+                "sha256:9090c9e676d5236a6948330e83cb89969f433b1943a558968f659ead07cb3b36",
+                "sha256:9153ed35fc5e4fa3b2fe97bddaa7cbec0ed22412b85bcdaf54aeba92ea37428c",
+                "sha256:9159485323798c8dc530a224bd3ffcf76659319ccc7bbd52e01e73bd0241a0c5",
+                "sha256:941988b89b4fd6b41c3f0bfb20e92bd23746579736b7343283297c4c8cbae68f",
+                "sha256:94265b00870aa407bd0cbcfd536f17ecde43b94fb8d228560a1e9d3041462d73",
+                "sha256:98b5e1f498a8ca1858a1cdbffb023bfd954da4e3fa2c0cb5853d40014557248b",
+                "sha256:9b201ae332c3637a42f02d1045e1d0cccfdc41f1f2f801dafbaa7e9b4797bfc2",
+                "sha256:a0ea261ce52b5952bf669684a251a66df239ec6d441ccb59ec7afa882265d593",
+                "sha256:a33a747400b94b6d6b8a165e4480264a64a78c8a4c734b62136062e9a248dd39",
+                "sha256:a452f9ca3e3267cd4d0fcf2edd0d035b1934ac2bd7e0e57ac91ad6b95c0c6389",
+                "sha256:a86373cf37cd7764f2201b76496aba58a52e76dedfaa698ef9e9688bfd9e41cf",
+                "sha256:ac83a914ebaf589b69f7d0a1277602ff494e21f4c2f743313414378f8f50a4cf",
+                "sha256:aefbc4cb0a54f91af643660a0a150ce2c090d3652cf4052a5397fb2de549cd89",
+                "sha256:b3646eefa23daeba62643a58aac816945cadc0afaf21800a1421eeba5f6cfb9c",
+                "sha256:b47cfad9e9bbbed2339081f4e346c93ecd7ab504299403320bf85f7f85c7d46c",
+                "sha256:b935ae30c6e7400022b50f8d359c03ed233d45b725cfdd299462f41ee5ffba6f",
+                "sha256:bb2dee3874a500de01c93d5c71415fcaef1d858370d405824783e7a8ef5db440",
+                "sha256:bc57efac2da352a51cc4658878a68d2b1b67dbe9d33c36cb826ca449d80a8465",
+                "sha256:bf5703fdeb350e36885f2875d853ce13172ae281c56e509f4e6eca049bdfb136",
+                "sha256:c31f72b1b6624c9d863fc095da460802f43a7c6868c5dda140f51da24fd47d7b",
+                "sha256:c5cd603b575ebceca7da5a3a251e69561bec509e0b46e4993e1cac402b7247b8",
+                "sha256:d2efee35b4b0a347e0d99d28e884dfd82797852d62fcd7ebdeee26f3ceb72cf3",
+                "sha256:d462f28826f4657968ae51d2181a074dfe03c200d6131690b7d65d55b0f360f8",
+                "sha256:d5e49454f19ef621089e204f862388d29e6e8d8b162efce05208913dde5b9ad6",
+                "sha256:da4813f751142436b075ed7aa012a8778aa43a99f7b36afe9b742d3ed8bdc95e",
+                "sha256:db2e408d983b0e61e238cf579c09ef7020560441906ca990fe8412153e3b291f",
+                "sha256:db98ad84a55eb09b3c32a96c576476777e87c520a34e2519d3e59c44710c002c",
+                "sha256:dbed418ba5c3dce92619656802cc5355cb679e58d0d89b50f116e4a9d5a9603e",
+                "sha256:dcdba5c86e368442528f7060039eda390cc4091bfd1dca41e8046af7c910dda8",
+                "sha256:decbfa2f618fa8ed81c95ee18a387ff973143c656ef800c9f24fb7e9c16054e2",
+                "sha256:e4fdb9275308292e880dcbeb12546df7f3e0f96c6b41197e0cf37d2826359020",
+                "sha256:eb1b046be06b0fce7249f1d025cd359b4b80fc1c3e24ad9eca33e0dcdb2e4a35",
+                "sha256:eb6e651000a19c96f452c85132811d25e9264d836951022d6e81df2fff38337d",
+                "sha256:ed867c42c268f876097248e05b6117a65bcd1e63b779e916fe2e33cd6fd0d3c3",
+                "sha256:edfad1d29c73f9b863ebe7082ae9321374ccb10879eeabc84ba3b69f2579d537",
+                "sha256:f2058f813d4f2b5e3a9eb2eb3faf8f1d99b81c3e51aeda4b168406443e8ba809",
+                "sha256:f6b2d0c6703c988d334f297aa5df18c45e97b0af3679bb75059e0e0bd8b1069d",
+                "sha256:f8212564d49c50eb4565e502814f694e240c55551a5f1bc841d4fcaabb0a9b8a",
+                "sha256:ffa565331890b90056c01db69c0fe634a776f8019c143a5ae265f9c6bc4bd6d4"
             ],
-            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'",
-            "version": "==1.15.0"
+            "markers": "python_version >= '3.6'",
+            "version": "==1.16.0"
         },
         "zipp": {
             "hashes": [
-                "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b",
-                "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"
+                "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31",
+                "sha256:84e64a1c28cf7e91ed2078bb8cc8c259cb19b76942096c8d7b84947690cabaf0"
             ],
-            "markers": "python_version >= '3.7'",
-            "version": "==3.15.0"
+            "markers": "python_version >= '3.8'",
+            "version": "==3.17.0"
         }
     }
 }
diff --git a/config.yaml b/config.yaml
index a769caf6..8caa6193 100644
--- a/config.yaml
+++ b/config.yaml
@@ -13,7 +13,7 @@
         column_rename:
           biodomain: name
         destination: *dest
-        
+
     - genes_biodomains:
         files:
           - name: genes_biodomains
@@ -102,6 +102,7 @@
         provenance:
           - syn26064497.1
         destination: *dest
+        gx_folder: syn52948669
 
     - gene_info:
         files:
diff --git a/gx_suite_definitions/metabolomics.ipynb b/gx_suite_definitions/metabolomics.ipynb
new file mode 100644
index 00000000..0e199959
--- /dev/null
+++ b/gx_suite_definitions/metabolomics.ipynb
@@ -0,0 +1,290 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import synapseclient\n",
+    "\n",
+    "import great_expectations as gx\n",
+    "\n",
+    "context = gx.get_context(project_root_dir='../src/agoradatatools/great_expectations')\n",
+    "\n",
+    "from expectations.expect_column_values_to_have_list_length import ExpectColumnValuesToHaveListLength\n",
+    "from expectations.expect_column_values_to_have_list_members import ExpectColumnValuesToHaveListMembers\n",
+    "from expectations.expect_column_values_to_have_list_members_of_type import ExpectColumnValuesToHaveListMembersOfType\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Create Expectation Suite for Metabolomics Data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Get Example Data File"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "syn = synapseclient.Synapse()\n",
+    "syn.login()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "metabolomics_data_file = syn.get(\"syn19276330\").path\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create Validator Object on Data File"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "validator = context.sources.pandas_default.read_json(\n",
+    "    metabolomics_data_file\n",
+    ")\n",
+    "validator.expectation_suite_name = \"metabolomics\"\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Add Expectations to Validator Object For Each Column"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# ad_diagnosis_p_value\n",
+    "validator.expect_column_values_to_be_of_type(\"ad_diagnosis_p_value\", \"list\")\n",
+    "validator.expect_column_values_to_not_be_null(\"ad_diagnosis_p_value\")\n",
+    "# for custom and experimental expectations you have to pass args as kwargs\n",
+    "validator.expect_column_values_to_have_list_length(column=\"ad_diagnosis_p_value\", list_length=1)\n",
+    "validator.expect_column_values_to_have_list_members_of_type(column=\"ad_diagnosis_p_value\", member_type=\"float\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# associated gene name\n",
+    "validator.expect_column_values_to_be_of_type(\"associated_gene_name\", \"str\")\n",
+    "validator.expect_column_values_to_not_be_null(\"associated_gene_name\")\n",
+    "validator.expect_column_value_lengths_to_be_between(\"associated_gene_name\", min_value=2, max_value=100)\n",
+    "# allows all alphanumeric characters, underscores, periods, and dashes\n",
+    "validator.expect_column_values_to_match_regex(\"associated_gene_name\", \"^[A-Za-z0-9_.-]+$\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# association p\n",
+    "validator.expect_column_values_to_be_of_type(\"association_p\", \"float\")\n",
+    "validator.expect_column_values_to_not_be_null(\"association_p\")\n",
+    "validator.expect_column_values_to_be_between(\"association_p\", strict_min_value=0, max_value=1)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# boxplot_group_names\n",
+    "validator.expect_column_values_to_be_of_type(\"boxplot_group_names\", \"list\")\n",
+    "validator.expect_column_values_to_not_be_null(\"boxplot_group_names\")\n",
+    "validator.expect_column_values_to_have_list_length(column=\"boxplot_group_names\", list_length=2)\n",
+    "validator.expect_column_values_to_have_list_members(column=\"boxplot_group_names\", list_members={\"AD\", \"CN\"})\n",
+    "validator.expect_column_values_to_have_list_members_of_type(column=\"boxplot_group_names\", member_type=\"str\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# ensembl gene id\n",
+    "validator.expect_column_values_to_be_of_type(\"ensembl_gene_id\", \"str\")\n",
+    "validator.expect_column_values_to_not_be_null(\"ensembl_gene_id\")\n",
+    "validator.expect_column_value_lengths_to_equal(\"ensembl_gene_id\", 15)\n",
+    "# checks format and allowed chatacters\n",
+    "validator.expect_column_values_to_match_regex(\"ensembl_gene_id\", \"^ENSG\\d{11}$\")\n",
+    "validator.expect_column_values_to_be_unique(\"ensembl_gene_id\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# gene_wide_p_threshold_1kgp\n",
+    "validator.expect_column_values_to_be_of_type(\"gene_wide_p_threshold_1kgp\", \"float\")\n",
+    "validator.expect_column_values_to_not_be_null(\"gene_wide_p_threshold_1kgp\")\n",
+    "validator.expect_column_values_to_be_between(\"gene_wide_p_threshold_1kgp\", strict_min_value=0, max_value=0.05)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# metabolite full name\n",
+    "validator.expect_column_values_to_be_of_type(\"metabolite_full_name\", \"str\")\n",
+    "validator.expect_column_values_to_not_be_null(\"metabolite_full_name\")\n",
+    "validator.expect_column_value_lengths_to_be_between(\"metabolite_full_name\", min_value=2, max_value=100)  \n",
+    "# allows all alphanumeric characters, dashes, parentheses, hyphens and spaces\n",
+    "validator.expect_column_values_to_match_regex(\"metabolite_full_name\", \"^[A-Za-z0-9\\s\\-:.()+]+$\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# metabolite ID\n",
+    "validator.expect_column_values_to_be_of_type(\"metabolite_id\", \"str\")\n",
+    "validator.expect_column_values_to_not_be_null(\"metabolite_id\")\n",
+    "validator.expect_column_value_lengths_to_be_between(\"metabolite_id\", min_value=2, max_value=100)\n",
+    "# allows all alphanumeric characters and periods\n",
+    "validator.expect_column_values_to_match_regex(\"metabolite_id\", \"^[A-Za-z0-9.]+$\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# n_per_group\n",
+    "validator.expect_column_values_to_be_of_type(\"n_per_group\", \"list\")\n",
+    "validator.expect_column_values_to_not_be_null(\"n_per_group\")\n",
+    "validator.expect_column_values_to_have_list_length(column=\"n_per_group\", list_length=2)\n",
+    "validator.expect_column_values_to_have_list_members_of_type(column=\"n_per_group\", member_type=\"int\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# transposed_boxplot_stats\n",
+    "validator.expect_column_values_to_be_of_type(\"transposed_boxplot_stats\", \"list\")\n",
+    "validator.expect_column_values_to_not_be_null(\"transposed_boxplot_stats\")\n",
+    "validator.expect_column_values_to_have_list_length(column=\"transposed_boxplot_stats\", list_length=2)\n",
+    "validator.expect_column_values_to_have_list_members_of_type(column=\"transposed_boxplot_stats\", member_type=\"list\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Save Expectation Suite"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "validator.save_expectation_suite(discard_failed_expectations=False)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create Checkpoint and View Results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "checkpoint = context.add_or_update_checkpoint(\n",
+    "    name=\"agora-test-checkpoint\",\n",
+    "    validator=validator,\n",
+    ")\n",
+    "checkpoint_result = checkpoint.run()\n",
+    "context.view_validation_result(checkpoint_result)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Build Data Docs - Click on Expectation Suite to View All Expectations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "context.build_data_docs()\n",
+    "context.open_data_docs()\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/setup.cfg b/setup.cfg
index e3f80989..7f9e42c6 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,5 +1,5 @@
 [metadata]
-name = agora-data-tools
+name = agoradatatools
 description = "A collection of tools that can be used to work with Agora's data"
 long_description = file: README.md
 long_description_content_type = text/markdown
@@ -20,8 +20,9 @@ classifiers =
     Programming Language :: Python :: 3 :: Only
     Programming Language :: Python :: 3.8
     Programming Language :: Python :: 3.9
-    Programming Language :: Python :: 3.10
-    Programming Language :: Python :: 3.11
+    # Support for Python versions 3.10 and above is temporarily disabled
+    # Programming Language :: Python :: 3.10 
+    # Programming Language :: Python :: 3.11
     Topic :: Scientific/Engineering
 project_urls =
     Bug Tracker = https://github.com/Sage-Bionetworks/agora-data-tools/issues
@@ -35,10 +36,11 @@ install_requires =
     pandas==1.2.4
     numpy~=1.21
     setuptools~=67.0.0
-    synapseclient~=2.7.0
+    synapseclient~=3.1.1
     PyYAML~=6.0
     pyarrow~=11.0
     typer~=0.7.0
+    great-expectations==0.18.1
 python_requires = >=3.8, <3.12
 include_package_data = True
 zip_safe = False
diff --git a/src/agoradatatools/etl/extract.py b/src/agoradatatools/etl/extract.py
index 3dd38099..c5c302ee 100644
--- a/src/agoradatatools/etl/extract.py
+++ b/src/agoradatatools/etl/extract.py
@@ -1,8 +1,11 @@
-from . import utils
 import pandas as pd
 
+import synapseclient
 
-def get_entity_as_df(syn_id: str, source: str, syn=None) -> pd.DataFrame:
+
+def get_entity_as_df(
+    syn_id: str, source: str, syn: synapseclient.Synapse
+) -> pd.DataFrame:
     """
     1. Creates and logs into synapseclient session (if not provided)
     2. Gets synapse entity from id string (and version number if provided)
@@ -11,13 +14,11 @@ def get_entity_as_df(syn_id: str, source: str, syn=None) -> pd.DataFrame:
     Args:
         syn_id (str): Synapse ID of entity to be loaded to df
         source (str): the source of the data to be loaded to df
-        syn (synapseclient.Synapse, optional): synapseclient.Synapse session. Defaults to None.
+        syn (synapseclient.Synapse): synapseclient.Synapse session object.
 
     Returns:
         pd.DataFrame: data frame generated from data source provided
     """
-    if syn is None:
-        syn = utils._login_to_synapse()
 
     syn_id_version = syn_id.split(".")
     synapse_id = syn_id_version[0]
@@ -92,7 +93,7 @@ def read_tsv_into_df(tsv_path: str) -> pd.DataFrame:
     return pd.read_csv(tsv_path, sep="\t")
 
 
-def read_table_into_df(table_id: str, syn) -> pd.DataFrame:
+def read_table_into_df(table_id: str, syn: synapseclient.Synapse) -> pd.DataFrame:
     """
     Reads a Synapse table into a dataframe.
 
diff --git a/src/agoradatatools/etl/load.py b/src/agoradatatools/etl/load.py
index c6f477e2..5f39d622 100644
--- a/src/agoradatatools/etl/load.py
+++ b/src/agoradatatools/etl/load.py
@@ -5,8 +5,6 @@
 import pandas as pd
 from synapseclient import Activity, File, Synapse
 
-from . import utils
-
 
 class NumpyEncoder(json.JSONEncoder):
     """Special json encoder for numpy types"""
@@ -83,9 +81,7 @@ def remove_non_values(d: dict) -> dict:
     return cleaned_dict
 
 
-def load(
-    file_path: str, provenance: list, destination: str, syn: Synapse = None
-) -> tuple:
+def load(file_path: str, provenance: list, destination: str, syn: Synapse) -> tuple:
     """Reads file to be loaded into Synapse
     :param syn: synapse object
     :return: synapse id of the file loaded into Synapse.  Returns None if it
@@ -95,14 +91,12 @@ def load(
         file_path (str): Path of the file to be loaded into Synapse
         provenance (list): Array of files that originate the one being loaded
         destination (str): Location where the file should be loaded in Synapse
-        syn (synapseclient.Synapse, optional): synapseclient session. Defaults to None.
+        syn (synapseclient.Synapse): synapseclient session.
 
     Returns:
         tuple: Returns a tuple of the name fo the file and the version number.
     """
 
-    if syn is None:
-        syn = utils._login_to_synapse()
     activity = Activity(used=provenance)
     file = File(file_path, parent=destination)
     file = syn.store(file, activity=activity, forceVersion=False)
diff --git a/src/agoradatatools/great_expectations/gx/.gitignore b/src/agoradatatools/great_expectations/gx/.gitignore
new file mode 100644
index 00000000..bfbef3d0
--- /dev/null
+++ b/src/agoradatatools/great_expectations/gx/.gitignore
@@ -0,0 +1,3 @@
+
+uncommitted/
+.ge_store_backend_id
diff --git a/src/agoradatatools/great_expectations/gx/checkpoints/metabolomics.yml b/src/agoradatatools/great_expectations/gx/checkpoints/metabolomics.yml
new file mode 100644
index 00000000..4fe2a27c
--- /dev/null
+++ b/src/agoradatatools/great_expectations/gx/checkpoints/metabolomics.yml
@@ -0,0 +1,30 @@
+name: metabolomics
+config_version: 1.0
+template_name:
+module_name: great_expectations.checkpoint
+class_name: Checkpoint
+run_name_template:
+expectation_suite_name:
+batch_request: {}
+action_list:
+  - name: store_validation_result
+    action:
+      class_name: StoreValidationResultAction
+  - name: store_evaluation_params
+    action:
+      class_name: StoreEvaluationParametersAction
+  - name: update_data_docs
+    action:
+      class_name: UpdateDataDocsAction
+evaluation_parameters: {}
+runtime_configuration: {}
+validations:
+  - batch_request:
+      datasource_name: default_pandas_datasource
+      data_asset_name: '#ephemeral_pandas_asset'
+      options: {}
+      batch_slice:
+    expectation_suite_name: metabolomics
+profilers: []
+ge_cloud_id:
+expectation_suite_ge_cloud_id:
diff --git a/src/agoradatatools/great_expectations/gx/expectations/metabolomics.json b/src/agoradatatools/great_expectations/gx/expectations/metabolomics.json
new file mode 100644
index 00000000..e3b561dd
--- /dev/null
+++ b/src/agoradatatools/great_expectations/gx/expectations/metabolomics.json
@@ -0,0 +1,327 @@
+{
+  "data_asset_type": null,
+  "expectation_suite_name": "metabolomics",
+  "expectations": [
+    {
+      "expectation_type": "expect_column_values_to_be_of_type",
+      "kwargs": {
+        "column": "ad_diagnosis_p_value",
+        "type_": "list"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_not_be_null",
+      "kwargs": {
+        "column": "ad_diagnosis_p_value"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_have_list_length",
+      "kwargs": {
+        "column": "ad_diagnosis_p_value",
+        "list_length": 1
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_have_list_members_of_type",
+      "kwargs": {
+        "column": "ad_diagnosis_p_value",
+        "member_type": "float"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_be_of_type",
+      "kwargs": {
+        "column": "associated_gene_name",
+        "type_": "str"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_not_be_null",
+      "kwargs": {
+        "column": "associated_gene_name"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_value_lengths_to_be_between",
+      "kwargs": {
+        "column": "associated_gene_name",
+        "max_value": 100,
+        "min_value": 2
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_match_regex",
+      "kwargs": {
+        "column": "associated_gene_name",
+        "regex": "^[A-Za-z0-9_.-]+$"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_be_of_type",
+      "kwargs": {
+        "column": "association_p",
+        "type_": "float"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_not_be_null",
+      "kwargs": {
+        "column": "association_p"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_be_between",
+      "kwargs": {
+        "column": "association_p",
+        "max_value": 1,
+        "strict_min_value": 0
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_be_of_type",
+      "kwargs": {
+        "column": "boxplot_group_names",
+        "type_": "list"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_not_be_null",
+      "kwargs": {
+        "column": "boxplot_group_names"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_have_list_length",
+      "kwargs": {
+        "column": "boxplot_group_names",
+        "list_length": 2
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_have_list_members",
+      "kwargs": {
+        "column": "boxplot_group_names",
+        "list_members": [
+          "CN",
+          "AD"
+        ]
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_have_list_members_of_type",
+      "kwargs": {
+        "column": "boxplot_group_names",
+        "member_type": "str"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_be_of_type",
+      "kwargs": {
+        "column": "ensembl_gene_id",
+        "type_": "str"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_not_be_null",
+      "kwargs": {
+        "column": "ensembl_gene_id"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_value_lengths_to_equal",
+      "kwargs": {
+        "column": "ensembl_gene_id",
+        "value": 15
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_match_regex",
+      "kwargs": {
+        "column": "ensembl_gene_id",
+        "regex": "^ENSG\\d{11}$"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_be_unique",
+      "kwargs": {
+        "column": "ensembl_gene_id"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_be_of_type",
+      "kwargs": {
+        "column": "gene_wide_p_threshold_1kgp",
+        "type_": "float"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_not_be_null",
+      "kwargs": {
+        "column": "gene_wide_p_threshold_1kgp"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_be_between",
+      "kwargs": {
+        "column": "gene_wide_p_threshold_1kgp",
+        "max_value": 0.05,
+        "strict_min_value": 0
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_be_of_type",
+      "kwargs": {
+        "column": "metabolite_full_name",
+        "type_": "str"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_not_be_null",
+      "kwargs": {
+        "column": "metabolite_full_name"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_value_lengths_to_be_between",
+      "kwargs": {
+        "column": "metabolite_full_name",
+        "max_value": 100,
+        "min_value": 2
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_match_regex",
+      "kwargs": {
+        "column": "metabolite_full_name",
+        "regex": "^[A-Za-z0-9\\s\\-:.()+]+$"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_be_of_type",
+      "kwargs": {
+        "column": "metabolite_id",
+        "type_": "str"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_not_be_null",
+      "kwargs": {
+        "column": "metabolite_id"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_value_lengths_to_be_between",
+      "kwargs": {
+        "column": "metabolite_id",
+        "max_value": 100,
+        "min_value": 2
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_match_regex",
+      "kwargs": {
+        "column": "metabolite_id",
+        "regex": "^[A-Za-z0-9.]+$"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_be_of_type",
+      "kwargs": {
+        "column": "n_per_group",
+        "type_": "list"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_not_be_null",
+      "kwargs": {
+        "column": "n_per_group"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_have_list_length",
+      "kwargs": {
+        "column": "n_per_group",
+        "list_length": 2
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_have_list_members_of_type",
+      "kwargs": {
+        "column": "n_per_group",
+        "member_type": "int"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_be_of_type",
+      "kwargs": {
+        "column": "transposed_boxplot_stats",
+        "type_": "list"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_not_be_null",
+      "kwargs": {
+        "column": "transposed_boxplot_stats"
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_have_list_length",
+      "kwargs": {
+        "column": "transposed_boxplot_stats",
+        "list_length": 2
+      },
+      "meta": {}
+    },
+    {
+      "expectation_type": "expect_column_values_to_have_list_members_of_type",
+      "kwargs": {
+        "column": "transposed_boxplot_stats",
+        "member_type": "list"
+      },
+      "meta": {}
+    }
+  ],
+  "ge_cloud_id": null,
+  "meta": {
+    "great_expectations_version": "0.18.1"
+  }
+}
\ No newline at end of file
diff --git a/src/agoradatatools/great_expectations/gx/great_expectations.yml b/src/agoradatatools/great_expectations/gx/great_expectations.yml
new file mode 100644
index 00000000..f56803a4
--- /dev/null
+++ b/src/agoradatatools/great_expectations/gx/great_expectations.yml
@@ -0,0 +1,106 @@
+# Welcome to Great Expectations! Always know what to expect from your data.
+#
+# Here you can define datasources, batch kwargs generators, integrations and
+# more. This file is intended to be committed to your repo. For help with
+# configuration please:
+#   - Read our docs: https://docs.greatexpectations.io/docs/guides/connecting_to_your_data/connect_to_data_overview/#2-configure-your-datasource
+#   - Join our slack channel: http://greatexpectations.io/slack
+
+# config_version refers to the syntactic version of this config file, and is used in maintaining backwards compatibility
+# It is auto-generated and usually does not need to be changed.
+config_version: 3.0
+
+# Datasources tell Great Expectations where your data lives and how to get it.
+# Read more at https://docs.greatexpectations.io/docs/guides/connecting_to_your_data/connect_to_data_overview
+datasources: {}
+
+# This config file supports variable substitution which enables: 1) keeping
+# secrets out of source control & 2) environment-based configuration changes
+# such as staging vs prod.
+#
+# When GX encounters substitution syntax (like `my_key: ${my_value}` or
+# `my_key: $my_value`) in the great_expectations.yml file, it will attempt
+# to replace the value of `my_key` with the value from an environment
+# variable `my_value` or a corresponding key read from this config file,
+# which is defined through the `config_variables_file_path`.
+# Environment variables take precedence over variables defined here.
+#
+# Substitution values defined here can be a simple (non-nested) value,
+# nested value such as a dictionary, or an environment variable (i.e. ${ENV_VAR})
+#
+#
+# https://docs.greatexpectations.io/docs/guides/setup/configuring_data_contexts/how_to_configure_credentials
+
+
+config_variables_file_path: uncommitted/config_variables.yml
+
+# The plugins_directory will be added to your python path for custom modules
+# used to override and extend Great Expectations.
+plugins_directory: plugins/
+
+stores:
+# Stores are configurable places to store things like Expectations, Validations
+# Data Docs, and more. These are for advanced users only - most users can simply
+# leave this section alone.
+#
+# Three stores are required: expectations, validations, and
+# evaluation_parameters, and must exist with a valid store entry. Additional
+# stores can be configured for uses such as data_docs, etc.
+  expectations_store:
+    class_name: ExpectationsStore
+    store_backend:
+      class_name: TupleFilesystemStoreBackend
+      base_directory: expectations/
+
+  validations_store:
+    class_name: ValidationsStore
+    store_backend:
+      class_name: TupleFilesystemStoreBackend
+      base_directory: uncommitted/validations/
+
+  evaluation_parameter_store:
+    class_name: EvaluationParameterStore
+  checkpoint_store:
+    class_name: CheckpointStore
+    store_backend:
+      class_name: TupleFilesystemStoreBackend
+      suppress_store_backend_id: true
+      base_directory: checkpoints/
+
+  profiler_store:
+    class_name: ProfilerStore
+    store_backend:
+      class_name: TupleFilesystemStoreBackend
+      suppress_store_backend_id: true
+      base_directory: profilers/
+
+expectations_store_name: expectations_store
+validations_store_name: validations_store
+evaluation_parameter_store_name: evaluation_parameter_store
+checkpoint_store_name: checkpoint_store
+
+data_docs_sites:
+  # Data Docs make it simple to visualize data quality in your project. These
+  # include Expectations, Validations & Profiles. The are built for all
+  # Datasources from JSON artifacts in the local repo including validations &
+  # profiles from the uncommitted directory. Read more at https://docs.greatexpectations.io/docs/terms/data_docs
+  local_site:
+    class_name: SiteBuilder
+    show_how_to_buttons: true
+    store_backend:
+      class_name: TupleFilesystemStoreBackend
+      base_directory: uncommitted/data_docs/local_site/
+    site_index_builder:
+      class_name: DefaultSiteIndexBuilder
+
+anonymous_usage_statistics:
+  data_context_id: f2b1d45a-9ad9-450a-a1f0-dc440e568a45
+  enabled: true
+fluent_datasources:
+  default_pandas_datasource:
+    type: pandas
+notebooks:
+include_rendered_content:
+  globally: false
+  expectation_suite: false
+  expectation_validation_result: false
diff --git a/src/agoradatatools/great_expectations/gx/plugins/custom_data_docs/styles/data_docs_custom_styles.css b/src/agoradatatools/great_expectations/gx/plugins/custom_data_docs/styles/data_docs_custom_styles.css
new file mode 100644
index 00000000..8bf5a152
--- /dev/null
+++ b/src/agoradatatools/great_expectations/gx/plugins/custom_data_docs/styles/data_docs_custom_styles.css
@@ -0,0 +1,22 @@
+/*index page*/
+.ge-index-page-site-name-title {}
+.ge-index-page-table-container {}
+.ge-index-page-table {}
+.ge-index-page-table-profiling-links-header {}
+.ge-index-page-table-expectations-links-header {}
+.ge-index-page-table-validations-links-header {}
+.ge-index-page-table-profiling-links-list {}
+.ge-index-page-table-profiling-links-item {}
+.ge-index-page-table-expectation-suite-link {}
+.ge-index-page-table-validation-links-list {}
+.ge-index-page-table-validation-links-item {}
+
+/*breadcrumbs*/
+.ge-breadcrumbs {}
+.ge-breadcrumbs-item {}
+
+/*navigation sidebar*/
+.ge-navigation-sidebar-container {}
+.ge-navigation-sidebar-content {}
+.ge-navigation-sidebar-title {}
+.ge-navigation-sidebar-link {}
diff --git a/src/agoradatatools/great_expectations/gx/plugins/expectations/expect_column_values_to_have_list_length.py b/src/agoradatatools/great_expectations/gx/plugins/expectations/expect_column_values_to_have_list_length.py
new file mode 100644
index 00000000..3b2e12dc
--- /dev/null
+++ b/src/agoradatatools/great_expectations/gx/plugins/expectations/expect_column_values_to_have_list_length.py
@@ -0,0 +1,121 @@
+import pandas as pd
+from typing import Optional, Any
+
+from great_expectations.core.expectation_configuration import ExpectationConfiguration
+from great_expectations.execution_engine import PandasExecutionEngine
+from great_expectations.expectations.expectation import ColumnMapExpectation
+from great_expectations.expectations.metrics import (
+    ColumnMapMetricProvider,
+    column_condition_partial,
+)
+
+
+# This class defines a Metric to support your Expectation.
+# For most ColumnMapExpectations, the main business logic for calculation will live in this class.
+class ColumnValuesListLength(ColumnMapMetricProvider):
+    """Class definition for list length checking metric."""
+
+    # This is the id string that will be used to reference your metric.
+    condition_metric_name = "column_values.list_length"
+    condition_value_keys = ("list_length",)
+
+    # This method implements the core logic for the PandasExecutionEngine
+    @column_condition_partial(engine=PandasExecutionEngine)
+    def _pandas(cls, column: pd.core.series.Series, list_length: int, **kwargs) -> bool:
+        """Core logic for list length checking metric on a
+        pandas execution engine.
+
+        Args:
+            column (pd.core.series.Series): Pandas column to be evaluated.
+            list_length (int): Expected list length.
+        Returns:
+            bool: Whether or not the column values have the expected list length.
+        """
+        return column.apply(lambda x: cls._check_list_length(x, list_length))
+
+    @staticmethod
+    def _check_list_length(cell: Any, list_length: int) -> bool:
+        """Check if a cell is a list, and if it has the expected length.
+
+        Args:
+            cell (Any): Individual cell to be evaluated.
+            list_length (int): Expected list length.
+
+        Returns:
+            bool: Whether or not the cell is a list with the expected length.
+        """
+        if not isinstance(cell, list):
+            return False
+        if len(cell) != list_length:
+            return False
+        return True
+
+
+# This class defines the Expectation itself
+class ExpectColumnValuesToHaveListLength(ColumnMapExpectation):
+    """Expect the list in column values to have a certain length."""
+
+    # These examples will be shown in the public gallery.
+    # They will also be executed as unit tests for your Expectation.
+    examples = [
+        {
+            "data": {
+                "a": [[1, 2, 3, 4, 5]],
+            },
+            "tests": [
+                {
+                    "title": "positive_test_with_list_length_5",
+                    "exact_match_out": False,
+                    "include_in_gallery": True,
+                    "in": {"column": "a", "list_length": 5},
+                    "out": {"success": True},
+                },
+                {
+                    "title": "negative_test_with_list_length_5",
+                    "exact_match_out": False,
+                    "include_in_gallery": True,
+                    "in": {"column": "a", "list_length": 4},
+                    "out": {"success": False},
+                },
+            ],
+        }
+    ]
+
+    # This is the id string of the Metric used by this Expectation.
+    # For most Expectations, it will be the same as the `condition_metric_name` defined in your Metric class above.
+    map_metric = "column_values.list_length"
+
+    # This is a list of parameter names that can affect whether the Expectation evaluates to True or False
+    success_keys = ("list_length",)
+
+    # This dictionary contains default values for any parameters that should have default values
+    default_kwarg_values = {}
+
+    def validate_configuration(
+        self, configuration: Optional[ExpectationConfiguration] = None
+    ) -> None:
+        """
+        Validates that a configuration has been set, and sets a configuration if it has yet to be set. Ensures that
+        necessary configuration arguments have been provided for the validation of the expectation.
+
+        Args:
+            configuration (OPTIONAL[ExpectationConfiguration]): \
+                An optional Expectation Configuration entry that will be used to configure the expectation
+        Returns:
+            None. Raises InvalidExpectationConfigurationError if the config is not validated successfully
+        """
+
+        super().validate_configuration(configuration)
+        configuration = configuration or self.configuration
+
+    # This object contains metadata for display in the public Gallery
+    library_metadata = {
+        "tags": [],  # Tags for this Expectation in the Gallery
+        "contributors": [  # Github handles for all contributors to this Expectation.
+            "@BWMac",  # Don't forget to add your github handle here!
+        ],
+    }
+
+
+if __name__ == "__main__":
+    ExpectColumnValuesToHaveListLength().print_diagnostic_checklist()
diff --git a/src/agoradatatools/great_expectations/gx/plugins/expectations/expect_column_values_to_have_list_members.py b/src/agoradatatools/great_expectations/gx/plugins/expectations/expect_column_values_to_have_list_members.py
new file mode 100644
index 00000000..66b2fbee
--- /dev/null
+++ b/src/agoradatatools/great_expectations/gx/plugins/expectations/expect_column_values_to_have_list_members.py
@@ -0,0 +1,124 @@
+import pandas as pd
+from typing import Optional, Any
+
+from great_expectations.core.expectation_configuration import ExpectationConfiguration
+from great_expectations.execution_engine import PandasExecutionEngine
+from great_expectations.expectations.expectation import ColumnMapExpectation
+from great_expectations.expectations.metrics import (
+    ColumnMapMetricProvider,
+    column_condition_partial,
+)
+
+
+# This class defines a Metric to support your Expectation.
+# For most ColumnMapExpectations, the main business logic for calculation will live in this class.
+class ColumnValuesListMembers(ColumnMapMetricProvider):
+    """Class definition for list members checking metric."""
+
+    # This is the id string that will be used to reference your metric.
+    condition_metric_name = "column_values.list_members"
+    condition_value_keys = ("list_members",)
+
+    # This method implements the core logic for the PandasExecutionEngine
+    @column_condition_partial(engine=PandasExecutionEngine)
+    def _pandas(
+        cls, column: pd.core.series.Series, list_members: set, **kwargs
+    ) -> bool:
+        """Core logic for list member checking metric on a
+        pandas execution engine.
+
+        Args:
+            column (pd.core.series.Series): Pandas column to be evaluated.
+            list_members (set): Expected list members.
+        Returns:
+            bool: Whether or not the column values have the expected list members.
+        """
+        return column.apply(lambda x: cls._check_list_members(x, list_members))
+
+    @staticmethod
+    def _check_list_members(cell: Any, list_members: set) -> bool:
+        """Check if a cell is a list, and if it has the expected members.
+
+        Args:
+            cell (Any): Individual cell to be evaluated.
+            list_members (set): Expected list members.
+
+        Returns:
+            bool: Whether or not the cell is a list with the expected members.
+        """
+        if not isinstance(cell, list):
+            return False
+        if not all(item in list_members for item in cell):
+            return False
+        return True
+
+
+# This class defines the Expectation itself
+class ExpectColumnValuesToHaveListMembers(ColumnMapExpectation):
+    """Expect the list in column values to have certain members."""
+
+    # These examples will be shown in the public gallery.
+    # They will also be executed as unit tests for your Expectation.
+    examples = [
+        {
+            "data": {
+                "a": [["a", "b", "a", "b"]],
+                "b": [["a", "b", "c", "d"]],
+            },
+            "tests": [
+                {
+                    "title": "positive_test_with_a_and_b",
+                    "exact_match_out": False,
+                    "include_in_gallery": True,
+                    "in": {"column": "a", "list_members": {"a", "b"}},
+                    "out": {"success": True},
+                },
+                {
+                    "title": "negative_test_with_a_b_c_d",
+                    "exact_match_out": False,
+                    "include_in_gallery": True,
+                    "in": {"column": "b", "list_members": {"a", "b"}},
+                    "out": {"success": False},
+                },
+            ],
+        }
+    ]
+
+    # This is the id string of the Metric used by this Expectation.
+    # For most Expectations, it will be the same as the `condition_metric_name` defined in your Metric class above.
+    map_metric = "column_values.list_members"
+
+    # This is a list of parameter names that can affect whether the Expectation evaluates to True or False
+    success_keys = ("list_members",)
+
+    # This dictionary contains default values for any parameters that should have default values
+    default_kwarg_values = {}
+
+    def validate_configuration(
+        self, configuration: Optional[ExpectationConfiguration] = None
+    ) -> None:
+        """
+        Validates that a configuration has been set, and sets a configuration if it has yet to be set. Ensures that
+        necessary configuration arguments have been provided for the validation of the expectation.
+
+        Args:
+            configuration (OPTIONAL[ExpectationConfiguration]): \
+                An optional Expectation Configuration entry that will be used to configure the expectation
+        Returns:
+            None. Raises InvalidExpectationConfigurationError if the config is not validated successfully
+        """
+
+        super().validate_configuration(configuration)
+        configuration = configuration or self.configuration
+
+    # This object contains metadata for display in the public Gallery
+    library_metadata = {
+        "tags": [],  # Tags for this Expectation in the Gallery
+        "contributors": [  # Github handles for all contributors to this Expectation.
+            "@BWMac",  # Don't forget to add your github handle here!
+        ],
+    }
+
+
+if __name__ == "__main__":
+    ExpectColumnValuesToHaveListMembers().print_diagnostic_checklist()
diff --git a/src/agoradatatools/great_expectations/gx/plugins/expectations/expect_column_values_to_have_list_members_of_type.py b/src/agoradatatools/great_expectations/gx/plugins/expectations/expect_column_values_to_have_list_members_of_type.py
new file mode 100644
index 00000000..76337a5a
--- /dev/null
+++ b/src/agoradatatools/great_expectations/gx/plugins/expectations/expect_column_values_to_have_list_members_of_type.py
@@ -0,0 +1,134 @@
+import pandas as pd
+from typing import Optional, Any
+
+from great_expectations.core.expectation_configuration import ExpectationConfiguration
+from great_expectations.execution_engine import PandasExecutionEngine
+from great_expectations.expectations.expectation import ColumnMapExpectation
+from great_expectations.expectations.metrics import (
+    ColumnMapMetricProvider,
+    column_condition_partial,
+)
+
+
+# This class defines a Metric to support your Expectation.
+# For most ColumnMapExpectations, the main business logic for calculation will live in this class.
+class ColumnValuesListMembersOfType(ColumnMapMetricProvider):
+    """Class definition for list member type checking metric."""
+
+    # This is the id string that will be used to reference your metric.
+    condition_metric_name = "column_values.list_members.of_type"
+    condition_value_keys = ("member_type",)
+
+    # This method implements the core logic for the PandasExecutionEngine
+    @column_condition_partial(engine=PandasExecutionEngine)
+    def _pandas(cls, column: pd.core.series.Series, member_type: str, **kwargs) -> bool:
+        """Core logic for list member checking metric on a
+        pandas execution engine.
+
+        Args:
+            column (pd.core.series.Series): Pandas column to be evaluated.
+            member_type (str): Expected list member type represented as a string.
+        Returns:
+            bool: Whether or not the column values have the expected list members.
+        """
+        return column.apply(lambda x: cls._check_list_member_type(x, member_type))
+
+    @staticmethod
+    def _check_list_member_type(cell: Any, member_type: str) -> bool:
+        """Check if a cell is a list, and if it has members of the expected type.
+
+        Args:
+            cell (Any): Individual cell to be evaluated.
+            member_type (str): Expected list member type represented as a string.
+
+        Returns:
+            bool: Whether or not the cell is a list with the expected members.
+        """
+        type_map = {
+            "int": int,
+            "float": float,
+            "str": str,
+            "bool": bool,
+            "list": list,
+            "dict": dict,
+            "set": set,
+        }
+        python_type = type_map.get(member_type)
+        if not python_type:
+            raise ValueError(f"member_type must be one of: {list(type_map.keys())}")
+
+        if not isinstance(cell, list):
+            return False
+        if not all(isinstance(item, python_type) for item in cell):
+            return False
+        return True
+
+
+# This class defines the Expectation itself
+class ExpectColumnValuesToHaveListMembersOfType(ColumnMapExpectation):
+    """Expect the list in column values to have members of a certain type."""
+
+    # These examples will be shown in the public gallery.
+    # They will also be executed as unit tests for your Expectation.
+    examples = [
+        {
+            "data": {
+                "a": [["a", "b", "a", "b"]],
+            },
+            "tests": [
+                {
+                    "title": "positive_test_with_strings",
+                    "exact_match_out": False,
+                    "include_in_gallery": True,
+                    "in": {"column": "a", "member_type": "str"},
+                    "out": {"success": True},
+                },
+                {
+                    "title": "negative_test_with_strings",
+                    "exact_match_out": False,
+                    "include_in_gallery": True,
+                    "in": {"column": "a", "member_type": "int"},
+                    "out": {"success": False},
+                },
+            ],
+        }
+    ]
+
+    # This is the id string of the Metric used by this Expectation.
+    # For most Expectations, it will be the same as the `condition_metric_name` defined in your Metric class above.
+    map_metric = "column_values.list_members.of_type"
+
+    # This is a list of parameter names that can affect whether the Expectation evaluates to True or False
+    success_keys = ("member_type",)
+
+    # This dictionary contains default values for any parameters that should have default values
+    default_kwarg_values = {}
+
+    def validate_configuration(
+        self, configuration: Optional[ExpectationConfiguration] = None
+    ) -> None:
+        """
+        Validates that a configuration has been set, and sets a configuration if it has yet to be set. Ensures that
+        necessary configuration arguments have been provided for the validation of the expectation.
+
+        Args:
+            configuration (OPTIONAL[ExpectationConfiguration]): \
+                An optional Expectation Configuration entry that will be used to configure the expectation
+        Returns:
+            None. Raises InvalidExpectationConfigurationError if the config is not validated successfully
+        """
+
+        super().validate_configuration(configuration)
+        configuration = configuration or self.configuration
+
+    # This object contains metadata for display in the public Gallery
+    library_metadata = {
+        "tags": [],  # Tags for this Expectation in the Gallery
+        "contributors": [  # Github handles for all contributors to this Expectation.
+            "@BWMac",  # Don't forget to add your github handle here!
+        ],
+    }
+
+
+if __name__ == "__main__":
+    ExpectColumnValuesToHaveListMembersOfType().print_diagnostic_checklist()
diff --git a/src/agoradatatools/gx.py b/src/agoradatatools/gx.py
new file mode 100644
index 00000000..d9597a22
--- /dev/null
+++ b/src/agoradatatools/gx.py
@@ -0,0 +1,117 @@
+import logging
+import os
+import shutil
+
+from synapseclient import Activity, File, Synapse
+
+import great_expectations as gx
+from great_expectations.checkpoint.types.checkpoint_result import CheckpointResult
+
+logger = logging.getLogger(__name__)
+# Disable GX INFO logging
+logging.getLogger("great_expectations").setLevel(logging.WARNING)
+
+
+class GreatExpectationsRunner:
+    """Class to run great expectations on a dataset and upload the HTML report to Synapse"""
+
+    def __init__(
+        self, syn: Synapse, dataset_path: str, dataset_name: str, upload_folder: str
+    ):
+        """Initialize the class"""
+        self.syn = syn
+        self.dataset_path = dataset_path
+        self.expectation_suite_name = dataset_name
+        self.upload_folder = upload_folder
+        self.gx_project_dir = self._get_data_context_location()
+
+        self.context = gx.get_context(project_root_dir=self.gx_project_dir)
+        self.validations_path = os.path.join(
+            self.gx_project_dir, "gx/uncommitted/data_docs/local_site/validations"
+        )
+        from expectations.expect_column_values_to_have_list_length import (
+            ExpectColumnValuesToHaveListLength,
+        )
+        from expectations.expect_column_values_to_have_list_members import (
+            ExpectColumnValuesToHaveListMembers,
+        )
+        from expectations.expect_column_values_to_have_list_members_of_type import (
+            ExpectColumnValuesToHaveListMembersOfType,
+        )
+
+    def _get_data_context_location(self) -> str:
+        """Gets the path to the great_expectations directory"""
+        script_dir = os.path.dirname(os.path.realpath(__file__))
+        gx_directory = os.path.join(script_dir, "great_expectations")
+        return gx_directory
+
+    def _check_if_expectation_suite_exists(self) -> bool:
+        """Checks if the expectation suite exists in the great_expectations workspace"""
+        exists = (
+            self.expectation_suite_name in self.context.list_expectation_suite_names()
+        )
+        if not exists:
+            logger.info(
+                f"Expectation suite {self.expectation_suite_name} does not exist. Data validation will not be performed."
+            )
+        return exists
+
+    def _get_results_path(self, checkpoint_result: CheckpointResult) -> str:
+        """Gets the path to the most recent HTML report for a checkpoint, copies it to a Synapse-API friendly name, and returns the new path"""
+        validation_results = checkpoint_result.list_validation_result_identifiers()
+        latest_validation_result = validation_results[0]
+
+        original_results_path_items = list(latest_validation_result.to_tuple())
+        original_results_path_items[-1] = original_results_path_items[-1] + ".html"
+        original_results_path = os.path.join(
+            self.validations_path,
+            *original_results_path_items,
+        )
+
+        timestamp_file_name = original_results_path_items[-2] + ".html"
+        new_results_path_items = original_results_path_items
+        new_results_path_items[-1] = timestamp_file_name
+        new_results_path = os.path.join(
+            self.validations_path,
+            *new_results_path_items,
+        )
+
+        shutil.copy(original_results_path, new_results_path)
+        return new_results_path
+
+    def _upload_results_file_to_synapse(self, results_path: str) -> None:
+        """Uploads a results file to Synapse"""
+        self.syn.store(
+            File(
+                results_path,
+                parentId=self.upload_folder,
+            ),
+            activity=Activity(
+                name=f"Great Expectations {self.expectation_suite_name} results",
+                executed="https://github.com/Sage-Bionetworks/agora-data-tools",
+            ),
+        )
+
+    def run(self) -> None:
+        """Run great expectations on a dataset and upload the results to Synapse"""
+        if not self._check_if_expectation_suite_exists():
+            return
+        logger.info(f"Running data validation on {self.expectation_suite_name}")
+        validator = self.context.sources.pandas_default.read_json(
+            self.dataset_path,
+        )
+        expectation_suite = self.context.get_expectation_suite(
+            self.expectation_suite_name
+        )
+        validator.expectation_suite = expectation_suite
+        validator.validate()
+        checkpoint = self.context.add_or_update_checkpoint(
+            name=self.expectation_suite_name,
+            validator=validator,
+        )
+        checkpoint_result = checkpoint.run()
+        logger.info(
+            f"Data validation complete for {self.expectation_suite_name}. Uploading results to Synapse."
+        )
+        latest_reults_path = self._get_results_path(checkpoint_result)
+        self._upload_results_file_to_synapse(latest_reults_path)
diff --git a/src/agoradatatools/process.py b/src/agoradatatools/process.py
index 30e72933..823f427e 100644
--- a/src/agoradatatools/process.py
+++ b/src/agoradatatools/process.py
@@ -6,6 +6,7 @@
 from agoradatatools.etl import extract, load, utils, transform
 from agoradatatools.errors import ADTDataProcessingError
 from agoradatatools.logs import log_time
+from agoradatatools.gx import GreatExpectationsRunner
 
 logger = logging.getLogger(__name__)
 
@@ -30,7 +31,7 @@ def apply_custom_transformations(datasets: dict, dataset_name: str, dataset_obj:
             genetics_max_score=dataset_obj["custom_transformations"][
                 "genetics_max_score"
             ],
-            omics_max_score=dataset_obj["custom_transformations"]["omics_max_score"]
+            omics_max_score=dataset_obj["custom_transformations"]["omics_max_score"],
         )
     if dataset_name == "team_info":
         return transform.transform_team_info(datasets=datasets)
@@ -116,6 +117,16 @@ def process_dataset(
             filename=dataset_name + "." + dataset_obj[dataset_name]["final_format"],
         )
 
+    # run great expectations on dataset if expectation suite exists
+    if "gx_folder" in dataset_obj[dataset_name].keys():
+        gx_runner = GreatExpectationsRunner(
+            syn=syn,
+            dataset_path=json_path,
+            dataset_name=dataset_name,
+            upload_folder=dataset_obj[dataset_name]["gx_folder"],
+        )
+        gx_runner.run()
+
     syn_obj = load.load(
         file_path=json_path,
         provenance=dataset_obj[dataset_name]["provenance"],
@@ -126,12 +137,14 @@ def process_dataset(
     return syn_obj
 
 
-def create_data_manifest(parent=None, syn=None) -> DataFrame:
+def create_data_manifest(
+    syn: synapseclient.Synapse, parent: synapseclient.Folder = None
+) -> DataFrame:
     """Creates data manifest (dataframe) that has the IDs and version numbers of child synapse folders
 
     Args:
+        syn (synapseclient.Synapse): Synapse client session.
         parent (synapseclient.Folder/str, optional): synapse folder or synapse id pointing to parent synapse folder. Defaults to None.
-        syn (synapseclient.Synapse, optional): Synapse client session. Defaults to None.
 
     Returns:
         DataFrame: Dataframe containing IDs and version numbers of folders within the parent directory
@@ -140,9 +153,6 @@ def create_data_manifest(parent=None, syn=None) -> DataFrame:
     if not parent:
         return None
 
-    if not syn:
-        syn = utils._login_to_synapse()
-
     folders = syn.getChildren(parent)
     folder = [folders]
     folder = [
@@ -153,17 +163,17 @@ def create_data_manifest(parent=None, syn=None) -> DataFrame:
 
 
 @log_time(func_name="process_all_files", logger=logger)
-def process_all_files(config_path: str = None, syn=None):
+def process_all_files(
+    syn: synapseclient.Synapse,
+    config_path: str = None,
+):
     """This function will read through the entire configuration and process each file listed.
 
     Args:
+        syn (synapseclient.Session): Synapse client session
         config_path (str, optional): path to configuration file. Defaults to None.
-        syn (synapseclient.Session, optional): Synapse client session. Defaults to None.
     """
 
-    # if not syn:
-    #     syn = utils._login_to_synapse()
-
     if config_path:
         config = utils._get_config(config_path=config_path)
     else:
@@ -192,7 +202,7 @@ def process_all_files(config_path: str = None, syn=None):
 
     if not error_list:
         # create manifest if there are no errors
-        manifest_df = create_data_manifest(parent=destination, syn=syn)
+        manifest_df = create_data_manifest(syn=syn, parent=destination)
         manifest_path = load.df_to_csv(
             df=manifest_df, staging_path=staging_path, filename="data_manifest.csv"
         )
@@ -229,7 +239,7 @@ def process(
     auth_token: str = synapse_auth_opt,
 ):
     syn = utils._login_to_synapse(token=auth_token)
-    process_all_files(config_path=config_path, syn=syn)
+    process_all_files(syn=syn, config_path=config_path)
 
 
 if __name__ == "__main__":
diff --git a/test_config.yaml b/test_config.yaml
index c83afdbf..8dc2907a 100644
--- a/test_config.yaml
+++ b/test_config.yaml
@@ -102,6 +102,7 @@
         provenance:
           - syn26064497.1
         destination: *dest
+        gx_folder: syn52948671
 
     - gene_info:
         files:
diff --git a/tests/load/test_load.py b/tests/load/test_load.py
index f136dbc0..40f35755 100644
--- a/tests/load/test_load.py
+++ b/tests/load/test_load.py
@@ -64,17 +64,7 @@ def setup_method(self, syn):
     def teardown_method(self):
         mock.patch.stopall()
 
-    def test_load_syn_is_none(self):
-        test_tuple = load.load(
-            file_path="fake/path/to/fake/file",
-            provenance=["syn1111111", "syn1111112"],
-            destination="syn1111113",
-            syn=None,
-        )
-        self.patch_syn_login.assert_called_once()
-        assert test_tuple == ("syn1111114", 1)
-
-    def test_load_syn_is_not_none(self, syn):
+    def test_load(self, syn):
         test_tuple = load.load(
             file_path="fake/path/to/fake/file",
             provenance=["syn1111111", "syn1111112"],
diff --git a/tests/test_assets/gx/metabolomics.json b/tests/test_assets/gx/metabolomics.json
new file mode 100644
index 00000000..8e6cd4fe
--- /dev/null
+++ b/tests/test_assets/gx/metabolomics.json
@@ -0,0 +1,177 @@
+[
+  {
+    "associated_gene_name": "Gene_A",
+    "ensembl_gene_id": "ENSG000000001",
+    "metabolite_id": "SM..OH..C22.1",
+    "metabolite_full_name": "SM (OH) C22:1",
+    "association_p": 1.234567e-05,
+    "gene_wide_p_threshold_1kgp": 3.456789e-05,
+    "n_per_group": [
+      150,
+      200
+    ],
+    "boxplot_group_names": [
+      "Control",
+      "Treatment"
+    ],
+    "ad_diagnosis_p_value": [
+      0.345
+    ],
+    "transposed_boxplot_stats": [
+      [
+        -2.0,
+        -0.5,
+        0.0,
+        0.5,
+        2.0
+      ],
+      [
+        -1.5,
+        -0.2,
+        0.1,
+        0.8,
+        1.5
+      ]
+    ]
+  },
+  {
+    "associated_gene_name": "Gene_B",
+    "ensembl_gene_id": "ENSG000000002",
+    "metabolite_id": "SM..OH..C22.2",
+    "metabolite_full_name": "SM (OH) C22:2",
+    "association_p": 2.345678e-05,
+    "gene_wide_p_threshold_1kgp": 4.567890e-05,
+    "n_per_group": [
+      180,
+      220
+    ],
+    "boxplot_group_names": [
+      "Group_A",
+      "Group_B"
+    ],
+    "ad_diagnosis_p_value": [
+      0.456
+    ],
+    "transposed_boxplot_stats": [
+      [
+        -1.8,
+        -0.4,
+        0.2,
+        0.7,
+        1.8
+      ],
+      [
+        -1.6,
+        -0.3,
+        0.0,
+        0.5,
+        1.6
+      ]
+    ]
+  },
+  {
+    "associated_gene_name": "Gene_C",
+    "ensembl_gene_id": "ENSG000000003",
+    "metabolite_id": "SM..OH..C22.3",
+    "metabolite_full_name": "SM (OH) C22:3",
+    "association_p": 3.456789e-05,
+    "gene_wide_p_threshold_1kgp": 5.678901e-05,
+    "n_per_group": [
+      200,
+      250
+    ],
+    "boxplot_group_names": [
+      "Group_X",
+      "Group_Y"
+    ],
+    "ad_diagnosis_p_value": [
+      0.567
+    ],
+    "transposed_boxplot_stats": [
+      [
+        -2.2,
+        -0.7,
+        0.1,
+        0.6,
+        2.2
+      ],
+      [
+        -2.0,
+        -0.5,
+        0.0,
+        0.5,
+        2.0
+      ]
+    ]
+  },
+  {
+    "associated_gene_name": "Gene_D",
+    "ensembl_gene_id": "ENSG000000004",
+    "metabolite_id": "SM..OH..C22.4",
+    "metabolite_full_name": "SM (OH) C22:4",
+    "association_p": 4.567890e-05,
+    "gene_wide_p_threshold_1kgp": 6.789012e-05,
+    "n_per_group": [
+      220,
+      270
+    ],
+    "boxplot_group_names": [
+      "Group_P",
+      "Group_Q"
+    ],
+    "ad_diagnosis_p_value": [
+      0.678
+    ],
+    "transposed_boxplot_stats": [
+      [
+        -2.4,
+        -0.8,
+        0.0,
+        0.8,
+        2.4
+      ],
+      [
+        -2.2,
+        -0.7,
+        0.1,
+        0.6,
+        2.2
+      ]
+    ]
+  },
+  {
+    "associated_gene_name": "Gene_E",
+    "ensembl_gene_id": "ENSG000000005",
+    "metabolite_id": "SM..OH..C22.5",
+    "metabolite_full_name": "SM (OH) C22:5",
+    "association_p": 5.678901e-05,
+    "gene_wide_p_threshold_1kgp": 7.890123e-05,
+    "n_per_group": [
+      250,
+      300
+    ],
+    "boxplot_group_names": [
+      "Group_M",
+      "Group_N"
+    ],
+    "ad_diagnosis_p_value": [
+      0.789
+    ],
+    "transposed_boxplot_stats": [
+      [
+        -2.6,
+        -1.0,
+        -0.2,
+        0.6,
+        2.6
+      ],
+      [
+        -2.4,
+        -0.8,
+        0.0,
+        0.8,
+        2.4
+      ]
+    ]
+  }
+]
diff --git a/tests/test_assets/gx/not_supported_dataset.json b/tests/test_assets/gx/not_supported_dataset.json
new file mode 100644
index 00000000..1e67c561
--- /dev/null
+++ b/tests/test_assets/gx/not_supported_dataset.json
@@ -0,0 +1,5 @@
+{
+  "a": "b",
+  "c": "d",
+  "e": "f"
+}
diff --git a/tests/test_extract.py b/tests/test_extract.py
index da241a91..2b72dd5b 100644
--- a/tests/test_extract.py
+++ b/tests/test_extract.py
@@ -85,15 +85,6 @@ def test_read_json_into_df():
         assert isinstance(df, pd.DataFrame)
 
 
-# test if utils._login_to_synapse is called when syn=None
-def test_get_entity_as_df_syn_is_none(syn):
-    with patch.object(
-        utils, "_login_to_synapse", return_value=syn
-    ) as patch_login_to_synapse:
-        extract.get_entity_as_df(syn_id="syn11111111", source="table", syn=None)
-        patch_login_to_synapse.assert_called_once()
-
-
 @pytest.mark.parametrize(
     "syn_id, version", [("syn1111111", None), ("syn1111111.1", "1")]
 )
@@ -113,7 +104,7 @@ def test_get_entity_as_df_with_version(syn, syn_id, version):
 
 
 # test raise if  is not supported
-def test_get_entity_as_df__not_supported(syn):
+def test_get_entity_as_df_not_supported(syn):
     with pytest.raises(ValueError, match="File type not *"):
         extract.get_entity_as_df(syn_id="syn1111111", source="abc", syn=syn)
 
diff --git a/tests/test_gx.py b/tests/test_gx.py
new file mode 100644
index 00000000..def12f64
--- /dev/null
+++ b/tests/test_gx.py
@@ -0,0 +1,133 @@
+import os
+import shutil
+from unittest import mock
+from unittest.mock import patch
+
+import pytest
+from great_expectations.checkpoint.types.checkpoint_result import CheckpointResult
+from great_expectations.data_context import FileDataContext
+from great_expectations.data_context.types.resource_identifiers import (
+    ValidationResultIdentifier,
+)
+from synapseclient import Activity, File
+
+from agoradatatools.gx import GreatExpectationsRunner
+
+
+class TestGreatExpectationsRunner:
+    @pytest.fixture(scope="function", autouse=True)
+    def setup_method(self, syn):
+        self.good_runner = GreatExpectationsRunner(
+            syn=syn,
+            dataset_path="./tests/test_assets/gx/metabolomics.json",
+            dataset_name="metabolomics",
+            upload_folder="test_folder",
+        )
+        self.bad_runner = GreatExpectationsRunner(
+            syn=syn,
+            dataset_path="./tests/test_assets/gx/not_supported_dataset.json",
+            dataset_name="not_supported_dataset",
+            upload_folder="test_folder",
+        )
+
+    def test_that_an_initialized_runner_has_the_attributes_it_should(self, syn):
+        assert (
+            self.good_runner.gx_project_dir
+            == self.good_runner._get_data_context_location()
+        )
+        assert self.good_runner.syn == syn
+        assert (
+            self.good_runner.dataset_path == "./tests/test_assets/gx/metabolomics.json"
+        )
+        assert self.good_runner.expectation_suite_name == "metabolomics"
+        assert self.good_runner.upload_folder == "test_folder"
+        assert isinstance(self.good_runner.context, FileDataContext)
+        assert (
+            self.good_runner.validations_path
+            == self.good_runner.gx_project_dir
+            + "/gx/uncommitted/data_docs/local_site/validations"
+        )
+
+    def test_that_get_data_context_location_returns_the_path_to_the_gx_directory(
+        self,
+    ):
+        expected_end = os.path.join("agoradatatools", "great_expectations")
+        result = self.good_runner._get_data_context_location()
+        assert result.endswith(expected_end)
+
+    def test_check_if_expectation_suite_exists_returns_false_when_the_expectation_suite_does_not_exist(
+        self,
+    ):
+        assert self.bad_runner._check_if_expectation_suite_exists() is False
+
+    def test_check_if_expectation_suite_exists_returns_true_when_the_expectation_suite_exists(
+        self,
+    ):
+        assert self.good_runner._check_if_expectation_suite_exists() is True
+
+    def test_get_results_path(self):
+        expected = self.good_runner.validations_path + "/test/path/to/to.html"
+        mocked_checkpoint_result = mock.create_autospec(CheckpointResult)
+        mocked_validation_result_identifier = mock.create_autospec(
+            ValidationResultIdentifier(
+                expectation_suite_identifier="test_expectation_suite_identifier",
+                run_id="test_run_id",
+                batch_identifier="test_batch_identifier",
+            )
+        )
+        mocked_checkpoint_result.list_validation_result_identifiers.return_value = [
+            mocked_validation_result_identifier
+        ]
+        with patch.object(
+            mocked_validation_result_identifier,
+            "to_tuple",
+            return_value=("test", "path", "to", "file"),
+        ) as patch_list_validation_result_identifiers, patch.object(
+            shutil, "copy"
+        ) as patch_copy:
+            result = self.good_runner._get_results_path(mocked_checkpoint_result)
+            patch_list_validation_result_identifiers.assert_called_once()
+            patch_copy.assert_called_once_with(
+                self.good_runner.validations_path + "/test/path/to/file.html",
+                self.good_runner.validations_path + "/test/path/to/to.html",
+            )
+            assert result == expected
+
+    def test_upload_results_file_to_synapse(self):
+        with patch.object(self.good_runner.syn, "store") as patch_syn_store:
+            self.good_runner._upload_results_file_to_synapse("test_path")
+            patch_syn_store.assert_called_once_with(
+                File(path="test_path", parent=self.good_runner.upload_folder),
+                activity=Activity(
+                    name=f"Great Expectations {self.good_runner.expectation_suite_name} results",
+                    executed="https://github.com/Sage-Bionetworks/agora-data-tools",
+                ),
+            )
+
+    def test_that_run_completes_successfully_when_check_if_expectation_suite_exists_is_true(
+        self,
+    ):
+        with patch.object(
+            self.good_runner, "_check_if_expectation_suite_exists", return_value=True
+        ), patch.object(
+            self.good_runner, "_get_results_path", return_value="test_path"
+        ) as patch_get_results_path, patch.object(
+            self.good_runner, "_upload_results_file_to_synapse", return_value=None
+        ) as patch_upload_results_file_to_synapse:
+            self.good_runner.run()
+            patch_get_results_path.assert_called_once()
+            patch_upload_results_file_to_synapse.assert_called_once_with("test_path")
+
+    def test_that_run_does_not_complete_when_check_if_expectation_suite_exists_is_false(
+        self,
+    ):
+        with patch.object(
+            self.good_runner, "_check_if_expectation_suite_exists", return_value=False
+        ), patch.object(
+            self.good_runner, "_get_results_path", return_value="test_path"
+        ) as patch_get_results_path, patch.object(
+            self.good_runner, "_upload_results_file_to_synapse", return_value=None
+        ) as patch_upload_results_file_to_synapse:
+            self.good_runner.run()
+            patch_get_results_path.assert_not_called()
+            patch_upload_results_file_to_synapse.assert_not_called()
diff --git a/tests/test_process.py b/tests/test_process.py
index 7d597e8c..84d9be79 100644
--- a/tests/test_process.py
+++ b/tests/test_process.py
@@ -157,15 +157,11 @@ def teardown_method(self):
         mock.patch.stopall()
 
     def test_create_data_manifest_parent_none(self, syn: Any):
-        assert process.create_data_manifest(parent=None, syn=syn) is None
+        assert process.create_data_manifest(syn=syn, parent=None) is None
         self.patch_syn_login.assert_not_called()
 
-    def test_create_data_manifest_syn_none(self):
-        process.create_data_manifest(parent="syn1111111", syn=None)
-        self.patch_syn_login.assert_called_once()
-
     def test_create_data_manifest_no_none(self, syn: Any):
-        df = process.create_data_manifest(parent="syn1111111", syn=syn)
+        df = process.create_data_manifest(syn=syn, parent="syn1111111")
         self.patch_get_children.assert_called_once_with("syn1111111")
         self.patch_syn_login.assert_not_called()
         assert isinstance(df, pd.DataFrame)
@@ -202,21 +198,21 @@ def teardown_method(self):
         mock.patch.stopall()
 
     def test_process_all_files_config_path(self, syn: Any):
-        process.process_all_files(config_path="path/to/config", syn=syn)
+        process.process_all_files(syn=syn, config_path="path/to/config")
         self.patch_get_config.assert_called_once_with(config_path="path/to/config")
 
     def test_process_all_files_no_config_path(self, syn: Any):
-        process.process_all_files(config_path=None, syn=syn)
+        process.process_all_files(syn=syn, config_path=None)
         self.patch_get_config.assert_called_once_with()
 
     def test_process_all_files_process_dataset_fails(self, syn: Any):
         with pytest.raises(ADTDataProcessingError):
             self.patch_process_dataset.side_effect = Exception
-            process.process_all_files(config_path="path/to/config", syn=syn)
+            process.process_all_files(syn=syn, config_path="path/to/config")
             self.patch_create_data_manifest.assert_not_called()
 
     def test_process_all_files_full(self, syn: Any):
-        process.process_all_files(config_path=None, syn=syn)
+        process.process_all_files(syn=syn, config_path=None)
         self.patch_process_dataset.assert_any_call(
             dataset_obj={"a": {"b": "c"}}, staging_path="./staging", syn=syn
         )