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authorPjotr Prins2020-11-29 09:16:46 +0000
committerPjotr Prins2020-11-29 09:52:31 +0000
commite9e8424af2e02d46ac97af206765b9bbec8f9732 (patch)
tree2d8199fd706b03bee4e0d522de470d5dba147b3a /README.md
parentfeacf0ec3cedaa3cecadd67674ca673d1bfa962e (diff)
downloadpangemma-e9e8424af2e02d46ac97af206765b9bbec8f9732.tar.gz
Updating README and manual
Diffstat (limited to 'README.md')
-rw-r--r--README.md50
1 files changed, 25 insertions, 25 deletions
diff --git a/README.md b/README.md
index 68e2d05..b7a2bb8 100644
--- a/README.md
+++ b/README.md
@@ -25,7 +25,9 @@ Debian, Conda, Homebrew and GNU Guix. With Guix you find the latest
version
[here](http://git.genenetwork.org/guix-bioinformatics/guix-bioinformatics)
as it is the version we use every day on http://genenetwork.org. For
-installation instructions see also [INSTALL.md](INSTALL.md).
+installation instructions see also [INSTALL.md](INSTALL.md). We use
+continous integration builds on Travis-CI for Linux (amd64 & arm64)
+and MacOS (amd64).
*(The above image depicts physiological and behavioral trait
loci identified in CFW mice using GEMMA, from [Parker et al, Nature
@@ -51,19 +53,19 @@ Genetics, 2016](https://doi.org/10.1038/ng.3609).)
1. Fast assocation tests implemented using the univariate linear mixed
model (LMM). In GWAS, this can correct for population structure and
-sample nonexchangeability. It also provides estimates of the
+sample non-exchangeability. It also provides estimates of the
proportion of variance in phenotypes explained by available genotypes
(PVE), often called "chip heritability" or "SNP heritability".
2. Fast association tests for multiple phenotypes implemented using a
multivariate linear mixed model (mvLMM). In GWAS, this can correct for
-populations tructure and sample nonexchangeability jointly in multiple
-complex phenotypes.
+population structure and sample (non)exchangeability - jointly in
+multiple complex phenotypes.
3. Bayesian sparse linear mixed model (BSLMM) for estimating PVE,
phenotype prediction, and multi-marker modeling in GWAS.
-4. Estimation of variance components ("chip heritability") partitioned
+4. Estimation of variance components ("chip/SNP heritability") partitioned
by different SNP functional categories from raw (individual-level)
data or summary data. For raw data, HE regression or the REML AI
algorithm can be used to estimate variance components when
@@ -74,7 +76,8 @@ MQS algorithm to estimate variance components.
To install GEMMA you can
-1. Download the precompiled binaries (64-bit Linux and Mac only)
+1. Download the precompiled or Docker binaries
+ from [releases](https://github.com/genetics-statistics/GEMMA/releases).
2. Use existing package managers, see [INSTALL.md](INSTALL.md).
@@ -89,20 +92,16 @@ numerical libraries.
1. Fetch the [latest stable release][latest_release] and download the
file appropriate for your platform.
-2. For .tar.bz2 files unpack the tar ball
+2. For Docker images, install Docker, load the image into Docker and
+ run with something like
- tar xvjf gemma-$version-installer.tar.bz2
-
- run the installer
-
- ./install.sh ~/gemma
-
- and run gemma
-
- ~/gemma/bin/gemma
+ docker run -w /run -v ${PWD}:/run ed5bf7499691 gemma -gk -bfile example/mouse_hs1940
3. For .gz files run `gunzip gemma.linux.gz` or `gunzip
-gemma.linux.gz` to unpack the file.
+gemma.linux.gz` to unpack the file. And make sure it is executable with
+
+ chmod u+x gemma-linux
+ ./gemma-linux
## Run GEMMA
@@ -132,24 +131,25 @@ Above example files can be downloaded from
GEMMA has a wide range of debugging options which can be viewed with
```
-gemma -h 14
-
DEBUG OPTIONS
+
-check enable checks (slower)
-no-fpe-check disable hardware floating point checking
-strict strict mode will stop when there is a problem
-silence silent terminal display
-debug debug output
-debug-data debug data output
+ -nind [num] read up to num individuals
+ -issue [num] enable tests relevant to issue tracker
-legacy run gemma in legacy mode
```
-typically when running gemma you should use -debug which includes relevant
-checks.
+typically when running gemma you should use -debug which includes
+relevant checks. When compiled for debugging the debug version of
+GEMMA gives more information.
-For performances you may want to use the -no-check option
-instead. Also check the build optimization notes in
-[INSTALL.md](INSTALL.md).
+For performance you may want to use the -no-check option. Also check
+the build optimization notes in [INSTALL.md](INSTALL.md).
## Help
@@ -192,7 +192,7 @@ studies.](https://doi.org/10.1101/042846) *Annals of Applied Statistics*, in pre
## License
-Copyright (C) 2012–2018, Xiang Zhou and team.
+Copyright (C) 2012–2020, Xiang Zhou and team.
The *GEMMA* source code repository is free software: you can
redistribute it under the terms of the