Docker Images

We have developed docker images containing several tools for analysis of high-throughput sequencing data, which are available in the Docker Hub.

Docker is an open-source project that performs operating-system-level virtualization, automating the deployment of applications inside software containers.

Docker really makes it easier to create, run applications and distribute it all out as one package. By doing so, the developer can be assured that the application will run on any other Linux machine regardless of any customized settings that machine might have that could differ from the machine used for writing and testing the code.

Docker makes bioinformatics easier and more reproducible!

Here you have a brief description of our docker images:

Docker Images
Tools Description
argrosso/rbase R base (CRAN) R base (CRAN)
Several R & BioConductor packages

R packages: data.table, ggplot2, gplots, KMsurv, plotrix, pls, RColorBrewer, readr, scales, scatterplot3d, seqinr, survival, VennDiagram. BioConductor packages:biomaRt, Biostrings, DESeq, DESeq2, edgeR, limma, tximport.

argrosso/bismark Bismark & Bowtie2 Bismark & Bowtie2 for DNA methylation data analysis (BS-sequencing)
argrosso/star Star Alignment for transcriptomic data (RNA-seq)
argrosso/htstools Bedtools, Samtools, UCSC tools, BEDOPS Several tools to process High-Throughput Sequencing aligned data: data.table R package, bedtools, samtools, UCSC tools, bedops.
argrosso/rubioseq RubioSeq RubioSeq for variant and CNV from Whole-Exome sequencing data. Original image contained RUBioseq tools installed in /home directory, which is incompatible with the slurm system.
argrosso/pyclone Pyclone Pyclone for clonal population structure based on genotypes.
argrosso/mutsigcv MutSigCV  MutSig analyzes lists of mutations discovered in DNA sequencing, to identify genes that were mutated more often than expected by chance given background mutation processes
argrosso/peakcalling MACS2 Tools for peak calling from ChIP-seq data (MACS2, bedtools, picard tools, samtools)
argrosso/kallisto Kallisto Transcriptome alignment and quantification
argrosso/htspreprocessing SRAtoolkit, fastQC, fastX-toolkit, trimGalore Several tools to pre-process High-Throughput Sequencing data: sra toolkit, fastQC, fastX-toolkit, trimGalore.

You can find more Docker images for Computational Biology and Bioinformatics in: