Second release

Manage the single read data.
Run the workflow using singularity then conda environment for each rules instead of a general docker image.

First release of differential-expression_workflow

Release of a workflow performing an RNA-seq analysis from the sequencing output data to the differential expression analyses.
3 steps for the analysis:

• clean.smk: The quality of the raw reads are assessed using FastQC v0.11.9 toolkit. Adapters and low quality reads are trimmed using Trimmomatic v0.39.
• count.smk: HiSat2 v2.2.1 is used for mapping the raw reads to the reference genome. The expression for each gene is evaluated using featureCounts from the Subread v2.0.1 package.
• differential_exp.smk: The low expressed genes are removed from further analysis. The raw counts are normalized and used for differential expression testing using DESeq2 v1.28.0.