Package: ldsc
LDSC (LD SCore)v2.0.0ldscis a command line tool for estimating heritability and genetic correlation from GWAS summary statistics.ldscalso computes LD Scores.Getting StartedIn order to downloadldsc, you should clone this repository via the commandsgit clone https://github.com/bulik/ldsc.git
cd ldscIn order to install the Python dependencies, you will need theAnacondaPython distribution and package manager. After installing Anaconda, run the following commands to create an environment with LDSC's dependencies:conda env create --file environment.yml
source activate ldscOnce the above has completed, you can run:./ldsc.py -h
./munge_sumstats.py -hto print a list of all command-line options. If these commands fail with an error, then something as gone wrong during the installation process.Short tutorials describing the four basic functions ofldsc(estimating LD Scores, h2 and partitioned h2, genetic correlation, the LD Score regression intercept) can be found in the wiki. If you would like to run the tests, please see the wiki.Updating LDSCYou can update to the newest version ofldscusinggit. First, navigate to yourldsc/directory (e.g.,cd ldsc), then rungit pullIfldscis up to date, you will seeAlready up-to-date.otherwise, you will seegitoutput similar toremote: Counting objects: 3, done.
remote: Compressing objects: 100% (3/3), done.
remote: Total 3 (delta 0), reused 0 (delta 0), pack-reused 0
Unpacking objects: 100% (3/3), done.
From https://github.com/bulik/ldsc
   95f4db3..a6a6b18  master     -> origin/master
Updating 95f4db3..a6a6b18
Fast-forward
 README.md | 15 +++++++++++++++
 1 file changed, 15 insertions(+)which tells you which files were changed. If you have modified theldscsource code,git pullmay fail with an error such aserror: Your local changes to the following files would be overwritten by merge:.In case the Python dependencies have changed, you can update the LDSC environment withconda env update --file environment.ymlWhere Can I Get LD Scores?You can downloadEuropeanandEast Asian LD Scoresfrom 1000 Genomeshere. These LD Scores are suitable for basic LD Score analyses (the LD Score regression intercept, heritability, genetic correlation, cross-sex genetic correlation). You can download partitioned LD Scores for partitioned heritability estimationhere.SupportBefore contacting us, please try the following:Thewikihas tutorials onestimating LD Score,heritability, genetic correlation and the LD Score regression interceptandpartitioned heritability.Common issues are described in theFAQThe methods are described in the papers (citations below)If that doesn't work, you can get in touch with us via thegoogle group.Issues with LD Hub?  Emailld-hub@bristol.ac.ukCitationIf you use the software or the LD Score regression intercept, please citeBulik-Sullivan, et al. LD Score Regression Distinguishes Confounding from Polygenicity in Genome-Wide Association Studies.
Nature Genetics, 2015.For genetic correlation, please also citeBulik-Sullivan, B., et al. An Atlas of Genetic Correlations across Human Diseases and Traits. Nature Genetics, 2015.Preprint available on bioRxiv doi:http://dx.doi.org/10.1101/014498For partitioned heritability, please also citeFinucane, HK, et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nature Genetics, 2015.Preprint available on bioRxiv doi:http://dx.doi.org/10.1101/014241For stratified heritability using continuous annotation, please also citeGazal, S, et al. Linkage disequilibrium–dependent architecture of human complex traits shows action of negative selection. Nature Genetics, 2017.If you find the fact that LD Score regression approximates HE regression to be conceptually useful, please citeBulik-Sullivan, Brendan. Relationship between LD Score and Haseman-Elston, bioRxiv doi:http://dx.doi.org/10.1101/018283For LD Hub, please citeZheng, et al. LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics (2016)LicenseThis project is licensed under GNU GPL v3.AuthorsBrendan Bulik-Sullivan (Broad Institute of MIT and Harvard)Hilary Finucane (MIT Department of Mathematics)