From 049ed44591d7b362913a6c0bffacf0eb0918eba5 Mon Sep 17 00:00:00 2001 From: Shilpa Nadimpalli Kobren Date: Wed, 22 May 2024 13:56:20 -0400 Subject: [PATCH] Update README.md --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 17a97b4..0fb09d2 100644 --- a/README.md +++ b/README.md @@ -5,17 +5,17 @@ This software package implements three well-calibrated statistical methods for a 2. genes recurrently impacted by inherited compound heterozygous variants across the cohort 3. genes harboring significant compound heterozygous variants in individual patients -Our [RaMeDiES wiki](https://github.com/hms-dbmi/RaMeDiES/wiki) also details how we ran our [pathway analysis](https://github.com/hms-dbmi/RaMeDiES/wiki/Pathway-analysis) to find biologically-related groups of genes impacted with -candidate variants across phenotypically similar patients. +Our [RaMeDiES wiki](https://github.com/hms-dbmi/RaMeDiES/wiki) also details how we ran our [pathway analysis](https://github.com/hms-dbmi/RaMeDiES/wiki/Pathway-analysis) to find pathways enriched with +candidate diagnostic variants across phenotypically similar patients. If you use RaMeDiES in your work, please cite our publication: -> SN Kobren*, MA Moldovan*, R Reimers, D Traviglia, X Li, D Barnum, A Veit, J Willett, M Berselli, W Ronchetti, R Sherwood, J Krier, IS Kohane, Undiagnosed Diseases Network, SR Sunyaev (2024). "Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra-rare monogenic presentations." _bioRxiv._ doi: [10.1101/2024.02.13.580158](https://www.biorxiv.org/content/10.1101/2024.02.13.580158v1). +> SN Kobren*, MA Moldovan*, R Reimers, D Traviglia, X Li, D Barnum, A Veit, RI Corona, GdV Carvalho Neto, J Willett, M Berselli, W Ronchetti, SF Nelson, JA Martinez-Agosto, R Sherwood, J Krier, IS Kohane, Undiagnosed Diseases Network, SR Sunyaev (2024). "Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra-rare monogenic presentations." _bioRxiv._ doi: [10.1101/2024.02.13.580158](https://www.biorxiv.org/content/10.1101/2024.02.13.580158v1). ## :sparkles: Prerequisites * Python 3.6+, R 4.1+ * Python libraries: os, sys, argparse v1.1+, numpy v1.23.3+, scipy v1.91+, rpy2 v3.15.16+, requests v3.31+, urllib3 v1.26.8+ * R packages: cluster -* :exclamation: **Operating System:** Linux distribution; compatibility on MacOS is not guaranteed, and Windows is not supported. +* :exclamation: **Operating System:** Linux or MacOS; Windows is not supported. ## :sparkles: Configuration Edit the configuration `cfg.py` file to include the full path to your local installation of this repository. @@ -25,7 +25,7 @@ script_directory = "/full/path/to/github/repo/RaMeDiES/" ``` ## :sparkles: Precomputed data files -We have precomputed per-gene mutational targets for CADD and SpliceAI variant functionality scores with respect to GRCh38/hg38. *The most up-to-date versions of these files can be found in* `/full/path/to/github/repo/RaMeDiES/data`. +We have precomputed per-gene mutational targets for various variant functionality scores with respect to GRCh38/hg38. *The most up-to-date versions of these files can be found in* `/full/path/to/github/repo/RaMeDiES/data`. A freeze of the precomputed files used in our initial manuscript submission (2024-02-01) can be downloaded from [Harvard Dataverse](https://doi.org/10.7910/DVN/UISZTE).