Update README.md

analyses/cell-type-wilms-tumor-06/notebook/README.md

@@ -15,25 +15,25 @@ As part of the `00b_characterize_fetal_kidney_reference_Stewart.Rmd` notebook te
 Each of the sample of the Wilms tumor dataset SCPCP000006 as been pre-processed and characterized as the following. 
 Reports for each of the steps are found in the notebook/{sample_id} directory:
 
--[x] `01_seurat_processing_{sample-id}.html` is the output of the [`01_seurat-processing.Rmd`](../notebook_template/01_seurat-processing.Rmd) notebook template.
+- [x] `01_seurat_processing_{sample-id}.html` is the output of the [`01_seurat-processing.Rmd`](../notebook_template/01_seurat-processing.Rmd) notebook template.
 In brief, the `_processed.rds` `sce object` is converted to `Seurat` and normalized using `SCTransform`.
 Dimensionality reduction (`RunPCA` and `RunUMAP`) and clustering (`FindNeighbors` and `FindClusters`) are performed before saving the `Seurat` object. 
 
--[x] `02a_fetal_full_label-transfer_{sample-id}.html` is the output of the [`02a_label-transfer_fetal_full_reference_Cao.Rmd`](../notebook_template/02a_label-transfer_fetal_full_reference_Cao.Rmd) notebook template.
+- [x] `02a_fetal_full_label-transfer_{sample-id}.html` is the output of the [`02a_label-transfer_fetal_full_reference_Cao.Rmd`](../notebook_template/02a_label-transfer_fetal_full_reference_Cao.Rmd) notebook template.
 In brief, we used `Azimuth` to transfer labels from the `Azimuth` fetal full reference (Cao et al.) 
 
--[x] `02b_fetal_kidney_label-transfer_{sample-id}.html` is the output of the [`02b_label-transfer_fetal_kidney_reference_Stewart.Rmd`](../notebook_template/02b_label-transfer_fetal_kidney_reference_Stewart.Rmd) notebook template.
+- [x] `02b_fetal_kidney_label-transfer_{sample-id}.html` is the output of the [`02b_label-transfer_fetal_kidney_reference_Stewart.Rmd`](../notebook_template/02b_label-transfer_fetal_kidney_reference_Stewart.Rmd) notebook template.
 In brief, we used `Azimuth` to transfer labels from the fetal kidney reference (Stewart et al.) 
 
--[x] `03_clustering_exploration_{sample-id}.html` is the output of the [`03_clustering_exploration.Rmd`](../notebook_template/03_clustering_exploration.Rmd) notebook template.
+- [x] `03_clustering_exploration_{sample-id}.html` is the output of the [`03_clustering_exploration.Rmd`](../notebook_template/03_clustering_exploration.Rmd) notebook template.
 In brief, we explore the clustering results, we look into some marker genes, pathways enrichment and label transfer.
 
 
 ## Global analysis
 
 The next step in analysis is to identify tumor vs. normal cells.
 
--[x] `04_annotation_Across_Samples_exploration.html` is the output of the [`04_annotation_Across_Samples_exploration.Rmd`](../notebook/04_annotation_Across_Samples_exploration.Rmd) notebook. 
+- [x] `04_annotation_Across_Samples_exploration.html` is the output of the [`04_annotation_Across_Samples_exploration.Rmd`](../notebook/04_annotation_Across_Samples_exploration.Rmd) notebook. 
 In brief, we explored the label transfer results across all samples in the Wilms tumor dataset SCPCP000006 in order to identify a few samples that we can begin next analysis steps with.
 
 ## Exploratory analysis
@@ -45,14 +45,14 @@ We selected in [`04_annotation_Across_Samples_exploration.Rmd`](../notebook/04_a
 - sample SCPCS000205 has > 89 % of cells predicted as kidney and 92 + 76 endothelium and immune cells.
 - sample SCPCS0000208 has > 95 % of cells predicted as kidney and 18 + 35 endothelium and immune cells.
 
--[x] `05_copykat_exploration_{sample_id}.html` is the output of the [`05_copykat_exploration.Rmd`](../notebook_template/05_copykat_exploration.Rmd) notebook template.
+- [x] `05_copykat_exploration_{sample_id}.html` is the output of the [`05_copykat_exploration.Rmd`](../notebook_template/05_copykat_exploration.Rmd) notebook template.
 
 In brief, we wanted to test `copykat` results obtained with or without normal cells as reference, using either an euclidean or statistical (spearman) method for CNV heatmap clustering. 
 This impact the final decision made by `copykat` for each cell to be either aneuploid or diploid, and it is thus crucial to explore the results using the different methods.
 For each of the selected samples, we explore the results in the template `notebook` [`05_copykat_exploration.Rmd`](../notebook_template/05_copykat_exploration.Rmd), which creates a notebook `05_cnv_copykat_exploration_{sample_id}.html` for each sample.
 These `notebooks` are inspired by the plots written for the Ewing Sarcoma analysis in [`03-copykat.Rmd`](https://github.com/AlexsLemonade/OpenScPCA-analysis/blob/main/analyses/cell-type-ewings/exploratory_analysis/03-copykat.Rmd).
 
--[x] `06_infercnv_exploration_{sample_id}.html` is the output of the [`06_infercnv_exploration.Rmd`](../notebook_template/06_infercnv_exploration.Rmd) notebook template.
+- [x] `06_infercnv_exploration_{sample_id}.html` is the output of the [`06_infercnv_exploration.Rmd`](../notebook_template/06_infercnv_exploration.Rmd) notebook template.
 
 In brief, we wanted to test `infercnv` results obtained with or without endothelium and/or immune cells as reference. 
 We also explore the potential of using a HMM model to assign CNV scores for each cells and discriminate normal from cancer cells.