README.md

HDR UK Open Source Contributions (173)

APPLIED ANALYTICS (5)

1. HDRUK_AppliedML: This repository contains code and supporting material for the HDRUK Summer School Course on Applied Deep Learning, August 22nd 2019
2. UKBiobank_deep_pretrain: Pretrained neural networks for UK Biobank brain MRI images. SFCN, 3D-ResNet etc.
3. biobankAccelerometerAnalysis: Extracting meaningful health information from large accelerometer datasets
4. metaviz:
5. tpot: A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

BHF DATA SCIENCE CENTRE (2)

1. 4C-Initiative: 4C-Initiative
2. Linked-EHR-England-2021: Publication: Linked electronic health records for research on a nationwide cohort including over 54 million people in England

BETTER CARE (3)

1. collaborathon-2020-team3: HDR UK Collaborathon Team3 Submission
2. openpathology-web: Openpathology website
3. openprescribing: A Django app providing a REST API and dashboards for the HSCIC's GP prescribing data

BIOINFORMATICS (6)

1. bedtools2: bedtools - the swiss army knife for genome arithmetic
2. bwa: Burrow-Wheeler Aligner for short-read alignment (see minimap2 for long-read alignment)
3. crossplatform_mGWAS: Cross-platform genetic discovery of small molecule products of metabolism and application to clinical outcomes Luca A. Lotta, Maik Pietzner, Isobel D. Stewart, Laura B.L. Wittemans, Chen Li, Roberto Bonelli, Johannes Raffler, Emma K. Biggs, Clare Oliver-Williams, Victoria P.W. Auyeung, Jian’an Luan, Eleanor Wheeler, Ellie Paige, Praveen Surendran, Gregory A. Michelotti, Robert A. Scott, Stephen Burgess, Verena Zuber, Eleanor Sanderson, Albert Koulman, Fumiaki Imamura, Nita G. Forouhi, Kay-Tee Khaw, MacTel Consortium, Julian L. Griffin, Angela M. Wood, Gabi Kastenmüller, John Danesh, Adam S. Butterworth, Fiona M. Gribble, Frank Reimann, Melanie Bahlo, Eric Fauman, Nicholas J. Wareham, Claudia Langenberg bioRxiv 2020.02.03.932541; doi: https://doi.org/10.1101/2020.02.03.932541
4. ensembl-vep: The Ensembl Variant Effect Predictor predicts the functional effects of genomic variants
5. gatk: Official code repository for GATK versions 1.0 through 3.7 (core engine). For GATK 4 code, see the https://github.com/broadinstitute/gatk repository
6. seqtk: Toolkit for processing sequences in FASTA/Q formats

COVID-19 (26)

1. 2019nCoV_proportion_asym:
2. BSTI COVID-19 Imaging Database:
3. CMMID Interactive Applications:
4. COVID19_NPIs_vs_Rt:
5. COVID19_clustersize: Analysis of COVID-19 transmission using cluster size distribution
6. ISARIC 4C prognostic score: The ISARIC 4C prognostic score uses data from more than 70,000 hospital admissions, we have devised a simple, robust and generalisable prognostic scoring system for hospitalised patients. The 4C Mortality Score is a risk stratification score that predicts in-hospital mortality for hospitalised COVID-19 patients, produced by the ISARIC 4C consortium. It is intended for use by clinicians. It is designed to be easy-to-use, and require only parameters that are commonly available at hospital presentation. For full details, see the paper introducing the score. This is an infographic that visualises risk, based on observed mortality among hospitalised adult COVID19 patients recruited into the ISARIC 4C study in the UK.
7. SAHSU-COVID-19: Repository for code and results from SAHSU's research into SARS-CoV-2 and COVID-19
8. SocialBubble:
9. benevolentai-dat: BenevolentAI's Diversity Analysis Tool (DAT) is a software package that can be used to produce demographic analysis reports given health data sets that contain for fields of age, sex, ethnicity, race and socio-economic status. For example, you might have a data about a cohort of patients and want to know how well you cover various ethnicities, age groups, sex groups and socio-economic status levels. Assuming your data sets have some of these fields, this software will help generate various views of the data to help inform your work. The DAT tool was developed as part of BenevolentAI's Diversity in Data Initiative, which aims to help improve the ways patients are represented in precision medicine. It is meant to help inspire other developers to find ways of assessing the data diversity in their current and prospective health data sets.
10. comix_covid-19-first_wave: Code and data from the analysis of the 1st wave of the CoMix 2020 contacts survey
11. comix_uk_covid_restrictions: code and data to reproduce analysis for Comix local and national restrictions paper
12. covid-mobility-tracker: Generate maps from google mobility data
13. covid-sim: This is the COVID-19 CovidSim microsimulation model developed by the MRC Centre for Global Infectious Disease Analysis hosted at Imperial College, London.
14. covid-uk: Scenario analyses for COVID-19 outbreak in the United Kingdom
15. covid19_asymptomatic_trans:
16. covid19_cases_from_deaths: Shiny app to infer caes from new deaths of COVID-19
17. gender_covid_uk: How is COVID-19 impacting women and men’s working lives in the UK? Data analysis, interactive visualizations, and integrative dashboard to understand the impact of COVID-19 on women and men's working lives in the UK
18. ggquickeda: ggplot2 and table1 summary statistics quick exploration of data
19. hit-analysis: Data and references on vaccine efficacy, R0 and seroprevalence estimates
20. los_review: Code used to produce the results presented in "A rapid review of evidence for hospital length of stay of COVID-19 patients"
21. ncov_measles_Kenya: Analysis of risk of measles outbreak during COVID19 pandemic in Kenya
22. nhs_pathways_monitoring: Real-time monitoring of potential COVID-19 cases reported through NHS pathways data
23. nsaids-covid-research:
24. rt-comparison-uk-public: Evaluating the use of the reproduction number as an epidemiological tool, using spatio-temporal trends of the Covid-19 outbreak in England https://github.com/epiforecasts/rt-comparison-uk-public/blob/master/README.md
25. screening_outbreak_delay:
26. transmission_inference:

COHORT DISCOVERY (1)

1. link-lite: HDR Link Lite - an open source lightweight version of BC-Link

GATEWAY (3)

1. Winterfell: Generate complex, validated and extendable JSON-based forms in React.
2. gateway-api: HDR UK Gateway API
3. gateway-web: HDR UK Gateway Web

GATEWAY (MVP) (4)

1. Gateway-Auth-Server:
2. Gateway-DB: Health Data Gateway - PostgreSQL Database
3. Gateway-Frontend: Health Data Gateway Frontend - react App
4. Gateway-Middleware: Health Data Gateway - GraphQL Apollo Middleware

HDR UK (7)

1. TRE-Survey:
2. clinical-trials:
3. covid-19: HDR UK - Resources for 🦠COVID-19 Research
4. datasets: HDR UK Gateway Datasets
5. oss: HDR UK OSS Contributions
6. papers: Extract of publications that mention HDR-UK
7. schemata: HDR UK Schemas

ICODA (1)

1. common-api: OpenAPI definitions for the Federated Data Sharing Common API

NATIONAL PHENOMICS RESOURCE (17)

1. CALIBER Drugdose: medication dosage instructions in electronic health records are often in the form of text rather than numbers. This program is designed to convert the text into numbers for the dose, frequency, units, duration etc.
2. CALIBER health records research toolkit: This project comprises a set of R packages to assist in epidemiological studies using electronic health records databases. CALIBER (http://caliberresearch.org/) is led from the Farr Institute @ London. CALIBER investigators represent a collaboration between epidemiologists, clinicians, statisticians, health informaticians and computer scientists with initial funding from the Wellcome Trust and the National Institute for Health Research. The goal of CALIBER is to provide evidence across different stages of translation, from discovery, through evaluation to implementation where electronic health records provide new scientific opportunities.
3. COVID-19 Phenomics:
4. OurRisk.CoV: We recently used large-scale samples of NHS patient data to estimate the excess risk of mortality which may be associated with coronavirus (COVID-19). We wanted to develop this research to inform simple tools to allow interaction and exploration by policymakers, researchers and the public. In the OurRisk.CoV tool, we provide our initial learning in relation to the implementation and development of policy responses to the COVID-19 pandemic. We have provided some simple tools to allow interaction and exploration. OurRisk.CoV is initially intended for use by researchers, policy makers and those who seek to work with patient data to inform responses to the current emergency.
5. PGS_Catalog: An open database of polygenic scores and relevant metadata needed to apply and evaluate them correctly.
6. PhenomicsLibrary:
7. chronological-map-phenotypes: Machine-readable version of electronic health record phenotypes for Kuan V. and Denaxas S. et al.
8. discrete_frechet: Compute the Fréchet distance between two polygonal curves in Euclidean space.
9. docker-ukbiobank-utils: Docker image for running UK Biobank utilities: ukbunpack, ukbfetch, ukblink, ukbgene, ukbmd5, ukbconv
10. hdr-caliber-phenotype-library: HDR UK National Phenotype Library
11. ohdsi-etl-caliber: ETL scripts for caliber data
12. phemap: Functions to map between ICD-10 terms and PheCodes for UK Biobank hospital electronic health records
13. phenomenet-vp: A phenotype-based tool for variant prioritization in WES and WGS data
14. phenotypes: HDR UK National Phenotype Library
15. tofu: Tofu is a Python tool for generating synthetic UK Biobank data.
16. ukb-biomarker-phenotypes: Phenotyping algorithms for common biomarkers in primary care EHR for UK Biobank
17. ukbiobank-resources: A curated list for preprocessing, cleaning, mapping and analyzing UK Biobank data.

NATIONAL TEXT ANALYTICS (30)

1. BioWSD: corpora containing examples of two ambiguities from the biomedical domain (abbreviations and gene names).
2. CRIS Natural Language Processing: library of applications available for use within South London and Maudsley (SLaM) on the Clinical Record Interaction Search (CRIS) platform. Access to CRIS must be applied for in order to use applications.
3. Cardiovascular research abstracts: corpus containing examples of potentially contradictory claims from Medline abstracts describing cardiovascular research intended as a useful resource for researchers working on similar problems.
4. CogStack-NiFi: Building data processing pipelines for documents processing with NLP using Apache NiFi and related services
5. CogStack-Pipeline: Distributed, fault tolerant batch processing for Natural Language Applications and Search, using remote partitioning
6. CogStack-Recipes: Example deployment recipes based on CogStack
7. CogStack-SemEHR: Surfacing Semantic Data from Clinical Notes in Electronic Health Records for Tailored Care, Trial Recruitment and Clinical Research
8. EdIE-BERT: a neural network system for named entity recognition and negation detection with a pretrained BERT encoder (BlueBERT) for brain imaging reports.
9. EdIE-BiLSTM: a neural network system for named entity recognition and negation detection with a character-aware BiLSTM sentence encoder for brain imaging reports.
10. EdIE-R: a rule-based information extraction tool developed for brain imaging reports.
11. EdIE-Viz: provides an interface for stroke-related clinical concept recognition and negation detection in brain radiology reports.
12. EndoMineR: a rule-based information extraction system for free-text and semi-structured endoscopy reports and their associated pathology specimens.
13. ExECT-V2:
14. HELIN: Demo Entity Linking API for the HDR Text Analytic Team.
15. MedCAT: Medical Concept Annotation Tool
16. MedCATservice: Running MedCAT as a RESTful web service
17. MedCATtrainer: A simple interface to inspect, improve and add concepts to biomedical NER+L -> MedCAT.
18. MedNorm Corpus: MedNorm is a corpus of 27,979 textual descriptions simultaneously mapped to both MedDRA and SNOMED-CT, sourced from five publicly available datasets across biomedical and social media domains. The cross-terminology medical concept embeddings are 64-dimensional vectors for UMLS, MedDRA and SNOMED-CT concepts that are able to capture semantic similarities between concepts from different medical terminologies.
19. PheneBank: 4 million MEDLINE abstracts as well as 3.8M open-access PMC full articles annotated with 9 classes of entity - Phenotype, Disease, Anatomy, Cell, Cell_line, GPR, Gene_variant, Molecule, and Pathway mapped to five major ontologies - SNOMED, HPO, MeSH, PRO, and FMA.
20. PheneBank- Processed Medline Abstracts and PMC full articles: 24 million MEDLINE abstracts as well as 3.8M open-access PMC full articles annotated with 9 classes of entity: Phenotype, Disease, Anatomy, Cell, Cell_line, GPR, Gene_variant, Molecule, and Pathway mapped to five major ontologies: SNOMED, HPO, MeSH, PRO, and FMA.
21. SIPHS: a collection of software and datasets to support linguistic analysis of online health communities.
22. SapBERT: Despite the widespread success of self-supervised learning via masked language models, learning representations directly from text to accurately capture complex and fine-grained semantic relationships in the biomedical domain remains as a challenge. SapBERT is a pre-training scheme based on BERT. It self-aligns the representation space of biomedical entities with a metric learning objective function leveraging UMLS, a collection of biomedical ontologies with >4M concepts.
23. bioreddit: Word embeddings trained on medical subreddits.
24. cometa: Corpus of Online Medical EnTities: the cometA corpus
25. freetext-matching-algorithm: Source code for the Freetext Matching Algorithm, a natural language processing system for clinical text
26. med7:
27. nlp2phenome: using AI model to infer patient phenotypes from identified named entities (instances of biomedical concepts)
28. onset_pipeline:
29. rake-nltk: Python implementation of the Rapid Automatic Keyword Extraction algorithm using NLTK.
30. risk-score-builder: Map clinical risk score concepts to structured definitions using ontologies, calculate structured risk scores from NLP.

TRAINING (3)

1. HDR-UK_Webmapping_in_R: How to use leaflet to make an interactive map using child obesity at reception year data in England.
2. hdruk_summerschool_session1: EHR analysis for the HDR UK summer school 2019
3. hdruk_summerschool_session_1_2: Docker image for first two sessions at the HDRUK summer school 2019

UNCATEGORISED (66)

1. 20190927_IntroductionGithub_HDRUK:
2. ADR-graph: Predicting adverse drug reactions from a knowledge graph
3. ASSIGN:
4. BRASS: Breakpoints via assembly - Identifies breaks and attempts to assemble rearrangements.
5. Biomarker_Identification: Biomarker Identification for Bravo, Williams, Gkoutos and Acharjee
6. CPRD_HES_variability:
7. CPRD_UTI_sepsis_elderly: This is the R code and code lists used to analyse the data for paper "Antibiotic prescribing for lower UTI in elderly patients in primary care and risk of bloodstream infection: A cohort study using electronic health records in England"
8. DWGSIM: Whole Genome Simulator for Next-Generation Sequencing
9. Data-Science-for-Docs: Data Science For Practicing Clinicians
10. ECMO: Extended Clinical Measurement Ontology
11. EHRtemporalVariability: R package for delineating temporal dataset shifts in Eletronic Health Records
12. EPACTS:
13. ESCs_models: Agent-based modelling of pattern formation in embryonic stem cells
14. Electronic-Monitoring-Device-Adherence-Typology: Study Aim: To construct a data-driven multi-dimensional typology of medication non-adherence in children with asthma.
15. FM-summary: Fine-mapping method only using summary statistics
16. HDRUK-fellows-day-2018: Machine Learning Resources collected from the HDRUK UK Fellows's day 2018 (2018-11-15)
17. KGPhenotyping: knowledge graph based phenotyping
18. MetaXcan: MetaXcan software and manuscript
19. PGM:
20. Pulse Wave Database: The aim of this project is to develop a database of simulated pulse waves with which to test pulse wave analysis algorithms. A database of simulated pulse waves representative of a sample of healthy adults was created. It contains several types of pulse waves (such as those measured by smart watches and fitness trackers) at common measurement sites for 4,374 virtual subjects aged 25 - 75 years old. The virtual subjects exhibit a range of cardiovascular properties across the normal ranges encountered in healthy people. The results were verified against in vivo data. Case studies were published (at https://doi.org/10.1152/ajpheart.00218.2019 ) demonstrating the utility of the database. The database is a useful resource for research and education on the topics of - signal processing, physiology, and computational modelling.
21. RDMP: Research Data Management Platform (RDMP) is an open source application for the loading,linking,anonymisation and extraction of datasets stored in relational databases.
22. RF-FeatureSelection-PowerAnalysis:
23. ScienceCOPEMethodsCode: Code accompanying map generation in Drew et al. Science manuscript
24. UNMIREOT: Tools to identify, diagnose, and semi-automatically repair hidden contradictions in biomedical ontologies
25. add_synonyms: add a synonym vocabulary to an ontology
26. artificialMHR:
27. bhpm: Bayesian Hierarchical Poisson Models for Multiple Grouped Outcomes with Clustering
28. cCFRDiamondPrincess:
29. cardio: Pulse oximetry data processing and classification
30. cgpBattenberg: Battenberg algorithm and associated implementation script
31. clockwork: CRyPTIC data processing pipelines
32. clustering_w2v:
33. dpclust: Dirichlet Process based methods for subclonal reconstruction of tumours
34. drug_target_lof: Evaluating potential drug targets through human loss-of-function genetic variation
35. generate-patients:
36. hdr_uk_demo: HDR UK Summer School demo for Image Registration
37. hdruk-phd-handbook: Handbook for the HDRUK-Turing PhD Programme in Health Data Science
38. hdruk_bbmri_hack:
39. hilton-keeling-estimating-R0: The code in this repository accompanies our upcoming paper "Estimation of country-level basic reproductive ratios for novelCoronavirus (COVID-19) using synthetic contact matrices". A preprint version of this paper is available at https://www.medrxiv.org/content/10.1101/2020.02.26.20028167v1. Some of our notation has changed between the preprint and the submission version of the paper. In particular, the age-specific susceptibility is now denoted by sigma rather than z.
40. jabberwocky: toolkit for those nonsensical ontologies
41. komenti: Semantic query and text mining tool
42. ldsc: LD Score Regression (LDSC)
43. loftee:
44. lrTaps:
45. manuscript_code: Manuscript code for our paper: bit.ly/bloodcellgwas
46. metaviz:
47. mim3val: mimic3 nlp evaluation. needs a NOTEEVENTS.csv, processed files from Komenti
48. mimpred: (In development) Reproducible experimental foundation for experiments with MIMIC
49. mimsim: Tools for performing semantic similarity over MIMIC-III
50. multiomic_AITD: Scripts associated with the paper doi: https://doi.org/10.1101/662957
51. mvGWAMA: Python script for multivariate GWAS meta-analysis
52. ocimido: An ontology for ocular immune-mediated inflammatory diseases
53. ontologies:
54. predCAN: Ontology-based prediction of cancer driver genes
55. resource_manager: This is a simple resource manager
56. ringbp:
57. sampledd: Sample MIMIC patients who die during their stay, and associated text records
58. software_differences_paper:
59. sview-sat-combined: Multimodal deep learning from satellite and street-level imagery for measuring income, overcrowding, and environmental deprivation in urban areas. The code used to implement the proposed methods and produce the experimental results in multimodal deep learning article
60. synonym_expansion_validation:
61. treeImbalance: An R package for detecting asymmetry in time-sampled phylogenetic trees.
62. treeSeg: Implementation of the treeSeg algorithm as an R package.
63. treeseq-inference: Work for the tree sequence inference paper.
64. uvR: R package to support analysing UVR data
65. vascular-ageing: Container for Python analysis codes regarding "Prediction of vascular ageing based on smartphoneacquired PPG signals"
66. vec2sparql: SPARQL Endpoint with functions for computing embedding similarities

Note: Contributions are noted where there are direct or indirect contributions (funding and support) made by HDR UK to the above projects.

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How to contribute OSS HDR UK projects

1. Create a Github.com account if you do not have one already
2. Create a fork of this project.
3. Edit the oss_projects.yml file and add an entry for your project using this template:

   - name: 'Project Awesome'
     description: 'Describe what your project is about'
     url: 'https://github.com/YOUREPO (Provide your Github Repo URL)'
     keywords:
      - 'example'
      - 'keyword'
     categories:
      - 'HDR UK'
      - 'themes'

4. Commit the changes to your fork and submit a Pull Request against the master branch of this project.

We'll review all requests and accept them according to HDR UK's policies. If accepted, your project will be listed above