smsk_tuxedo2: snakemake files of the tuxedo v2 pipeline from Pertea et al 2016

1. Description

This is a SnakeMake workflow to apply the protocol described in Pertea et al. 2016. With some modifications.

The idea is to produce Differential Expression analysis given a bunch of FASTQ files,

2. First steps

Follow the contents of the .travis.yml file:

1. Install (ana|mini)conda

   • Anaconda

   • miniconda

2. Installation

   git clone https://github.com/jlanga/smsk_tuxedo2.git smsk_tuxedo2
   cd smsk_tuxedo2
   snakemake --use-conda --create-envs-only

3. Execute the test pipeline:

   snakemake --use-conda -j

4. Modify the following files:

   • features.yml with your reference genome and annotation,
   • samples.tsv with the paths and info of your samples src/config.yaml

5. Run the pipeline with your data:

   snakemake --use-conda -j

3. File organization

The hierarchy of the folder is the one described in Good enough practices in scientific computing:

smsk
├── bin/: external scripts/binaries
├── data/: test data.
├── doc/: documentation.
├── README.md
├── results:
|   ├── raw: links to your raw data.
|   ├── map: files from HISAT2 mapping: index and CRAM files.
|   ├── quant: files from StringTie assembly and quantification
|   └── de: files from Ballgown: differential expression tables, RData objects for closer inspection.
├── Snakefile: driver script of the project.
├── environment.yml: packages to execute the analysis.
└── src: snakefiles, installers, config.yaml, R scripts.

4. Workflow description

4.1 Mapping with HISAT2 (rule map)

• Index is build from scratch

• Exons and splicing sites are computed from the reference GTF file

• Paired reads are mapped with HISAT2. Results are compressed to CRAM on the fly.

4.2 Transcript assembly and quantification with StringTie (rule quant)

• Using the exact parameters from Pertea et al. 2016

• CRAM -> SAM conversion on the fly

4.3 Differential expression analysis with Ballgown (rule de)

• Performing DE with the R script provided in src/de_ballgown.R

• Visualization should be done interactively.

Bibliography

• Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Pertea et al 2016

• The Sequence Alignment/Map format and SAMtools. Li et al.

• HISAT: a fast spliced aligner with low memory requirements. Kim et al.

• StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Pertea et al.

• Flexible isoform-level differential expression analysis with Ballgown. Frazee et al.

• RSkittleBrewer. Frazee et al.

• SnakeMake - A scalable workflow engine. Köster et al.

• smsk - a snakemake skeleton to jumpstart your projects. Langa.