This is the GitHub organization of the Computational Medicine Group based in the QMUL PHURI (London) and the BIH@Charité (Berlin).
For recent results and studies please visit www.omicscience.org.
Computational Medicine Lab
Computational Medicine Group based in London (QMUL PHURI) and Berlin (BIH@Charité)
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sparse-proteomic-prediction-of-common-and-rare-diseases
sparse-proteomic-prediction-of-common-and-rare-diseases PublicThis repository contains code associated with the study "Proteomic signatures improve risk predictions for common and rare diseases" (DOI pending) The provided scripts are not designed to work out …
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gwascatftp
gwascatftp PublicForked from cfbeuchel/gwascatftp
R package to access GWAS Catalog FTP data
R 3
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Repositories
Showing 10 of 17 repositories
- nf-download-sumstats Public
Nextflow pipeline for downloading raw GWAS summary statistics to be then processed using `nf-munge-sumstats`
comp-med/nf-download-sumstats’s past year of commit activity - nf-munge-sumstats Public
Nextflow pipeline to download and format (i.e. munge) GWAS summary statistics
comp-med/nf-munge-sumstats’s past year of commit activity - project-template Public template
A suggested directory and file structure for analysis projects in the computational medicine group
comp-med/project-template’s past year of commit activity - r-prodente Public
Companion R package for a publication to run enrichment analysis across protein determining factors
comp-med/r-prodente’s past year of commit activity - nf-nmr-coloc Public
Nextflow pipeline to run metabolome-wide colocalization analysis based on the `nf-scallop-coloc` pipeline.
comp-med/nf-nmr-coloc’s past year of commit activity - nf-template Public template
Template directory for Nextflow pipelines providing basic files and directories when setting up a new workflow
comp-med/nf-template’s past year of commit activity - sparse-proteomic-prediction-of-common-and-rare-diseases Public
This repository contains code associated with the study "Proteomic signatures improve risk predictions for common and rare diseases" (DOI pending) The provided scripts are not designed to work out of the box, but rather illustrate the main steps done for each of the analysis performed.
comp-med/sparse-proteomic-prediction-of-common-and-rare-diseases’s past year of commit activity
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