This section provides a brief summary of how to use the image. More detailed instructions can be found on GitHub.
Create the data volume (see the accompanying documentation for details on the data themselves):
docker create --name jurkat_assembled humburg/jurkat-only-rna-assembled
and start a container:
docker run -ti --volumes-from jurkat_assembled -v /path/to/source/code:/code humburg/healthhack-2016
The data files will then be located in
- Python (3.5.2)
including support for Cython and numpy. The biopython, pysam and Levenshtein modules may be of use. Support for unit testing is provided by the nose and coverage modules.
- Java (openjdk 1.8.0_91)
- FastQC (0.11.5)
A quality control tool for high throughput sequence data.
- PEAR (0.9.10) A tool designed for the efficient and accurate merging of overlapping paired-end reads.
- GSNAP (2016-09-23)
Aligns RNA-seq reads to a reference genome.
- Samtools (1.3.1) A suite of programs for interacting with high-throughput sequencing data. Includes bcftools and HTSlib.
- Picard (2.2.4) A set of command line tools for manipulating high-throughput sequencing data and formats.