Skip to content

Latest commit

 

History

History
62 lines (57 loc) · 1.51 KB

README.md

File metadata and controls

62 lines (57 loc) · 1.51 KB
Raw

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