llgai508/helloworld:latest

$ singularity pull shub://llgai508/helloworld:latest

Singularity Recipe

Bootstrap: docker
From: debian:stretch-slim
%labels
MAINTAINER Gao Wang, gaow@uchicago.edu
%post

cd /tmp

# Install dev libraries
apt-get update \
&& apt-get install -y --no-install-recommends \
curl \
unzip \
gzip \
bzip2 \
ca-certificates \
build-essential \
gfortran \
libgfortran-6-dev \
libgomp1 \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/* /var/log/dpkg.log

# R, Python, SoS and DSC
MINICONDA_VERSION=4.5.11
PATH=/opt/miniconda3/bin:$PATH
curl https://repo.continuum.io/miniconda/Miniconda3-$MINICONDA_VERSION-Linux-x86_64.sh -o MCON.sh \
&& /bin/bash MCON.sh -b -p /opt/miniconda3 \
&& ln -s /opt/miniconda3/etc/profile.d/conda.sh /etc/profile.d/conda.sh \
&& conda install matplotlib==3.0.2 seaborn==0.9.0 \
&& conda install -c conda-forge r-base==3.5.1 sos==0.17.7 dsc==0.3.1.2 rpy2==2.9.4 \
&& conda clean --all -tipsy 
pip install sos-notebook==0.17.3 jupyter_contrib_nbextensions==0.5.0 --no-cache-dir

# Packages for building and running susieR vignettes
conda install -c conda-forge r-devtools r-testthat r-openssl r-reshape r-ggplot2 r-cowplot \
r-profvis r-microbenchmark r-pkgdown r-dplyr r-stringr r-readr r-magrittr \
r-matrixstats r-glmnet \
libiconv && conda clean --all -tipsy 
ln -s /bin/tar /bin/gtar

# Large scale regression related tools for running some susieR vignettes
R --slave -e "devtools::install_github('glmgen/genlasso')"
R --slave -e "devtools::install_github('hazimehh/L0Learn')"

# Fine-mapping tools
apt-get update && apt-get install -y --no-install-recommends libgsl-dev libgsl2 libatlas3-base liblapack-dev && apt-get clean
curl -L https://github.com/fhormoz/caviar/tarball/743038a32ae66ea06ee599670cb7939fb80a923f -o caviar.tar.gz \
&& tar -zxvf caviar.tar.gz && cd fhormoz-caviar-*/CAVIAR-C++ && make \
&& mv CAVIAR eCAVIAR mupCAVIAR setCAVIAR /usr/local/bin 


curl -L https://github.com/xqwen/dap/tarball/ef11b263ae5e11b9e2e295757927877c03274095 -o dap.tar.gz \
&& tar -zxvf dap.tar.gz && cd xqwen-dap-*/dap_src && make && mv dap-g /usr/local/bin 

curl -L http://www.christianbenner.com/finemap_v1.1_x86_64.tgz -o finemap.tgz \
&& tar zxvf finemap.tgz && mv finemap_v1.1_x86_64/finemap_v1.1_x86_64 /usr/local/bin/finemap \
&& chmod +x /usr/local/bin/finemap 

SuSiE_VERSION=8a4f7177c0031255901083fa0f62555307acb6d9

# Supporting files
curl -L https://raw.githubusercontent.com/stephenslab/susieR/${SuSiE_VERSION}/inst/code/finemap.R -o /usr/local/bin/finemap.R \
&& chmod +x /usr/local/bin/finemap.R

curl -L https://raw.githubusercontent.com/stephenslab/susieR/${SuSiE_VERSION}/inst/code/caviar.R -o /usr/local/bin/caviar.R \
&& chmod +x /usr/local/bin/caviar.R

curl -L https://raw.githubusercontent.com/stephenslab/susieR/${SuSiE_VERSION}/inst/code/dap-g.py -o /usr/local/bin/dap-g.py \
&& chmod +x /usr/local/bin/dap-g.py

# DSC R-utils
R --slave -e "devtools::install_github('rstudio/reticulate')"
R --slave -e "devtools::install_github('stephenslab/dsc@v0.3.1.2', subdir = 'dscrutils')"

# susieR 
R --slave -e "devtools::install_github('stephenslab/susieR', ref = '"${SuSiE_VERSION}"')"

# Benchmark related
R --slave -e "install.packages('abind', repos='http://cran.us.r-project.org')"


# Prevent local config / packages from being loaded
R_ENVIRON_USER=""
R_PROFILE_USER=""
R_LIBS_USER=' '

# In response to the following numpy error
# Error: Numpy + Intel(R) MKL: MKL_THREADING_LAYER=INTEL is incompatible with libgomp.so.1 library.
# Try to import numpy first or set the threading layer accordingly. Set NPY_MKL_FORCE_INTEL to force it.
MKL_THREADING_LAYER=GNU

%environment
export MINICONDA_VERSION=4.5.11
export PATH=/opt/miniconda3/bin:$PATH
export SuSiE_VERSION=8a4f7177c0031255901083fa0f62555307acb6d9
export R_ENVIRON_USER=""
export R_PROFILE_USER=""
export R_LIBS_USER=' '
export MKL_THREADING_LAYER=GNU
%runscript
exec /bin/bash "$@"

Collection

• Name: llgai508/helloworld
• License: Apache License 2.0

Metrics

Feedback

Was this page helpful?

Glad to hear it! Please tell us how we can improve.

Sorry to hear that. Please tell us how we can improve.