genomic-analysis docker

A fat docker image for ad-hoc genomic analyses - combines a lot of the tools that are handy for exploring data

R 4.11 and some basic packages are installed. For convenience, it can be useful to set up a specific folder in which to keep your own library installs for testing. This will keep them persistent across sessions. Add something like this to your .Rprofile:

devlib <- paste('/home/USERNAME/lib/R',paste(R.version$major,R.version$minor,sep="."),sep="")
if (!file.exists(devlib))
  dir.create(devlib)
x <- .libPaths()
.libPaths(c(devlib,x))
rm(x,devlib)

This is great for quickly prototyping and exploring data, but don't forget that if you're sharing code with others, you'll need to create a new container with the proper libraries installed so they can also use it!

Partial list of tools:

• Bedtools
• Samtools
• BCFtools
• VCFtools
• pdftk
• tabix
• bam-readcount
• GATK (and picard tools)
• FastQC
• Google cloud SDK
• R 4.11 and packages including:
  • BioCManager
  • data.table
  • dplyr
  • foreach
  • fishplot
  • gridExtra
  • Hmisc
  • plotrix
  • png
  • RColorBrewer
  • tidyverse
  • wesanderson
  • viridis
  • GenVisR
  • GenomicRanges
  • tximport
  • biomaRt
• Python 3 and packages including:
  • numpy
  • scipy
  • cython
  • pyfaidx
  • pybedtools
  • cyvcf2
  • pandas
  • pysam
  • seaborn
  • openpyxl
  • cruzdb
  • intervaltree_bio
  • multiqc
  • pyensembl
  • scikit-learn
  • svviz
  • vatools