ESGq is a graph-based approach for the quantification of Alternative Splicing events across two conditions. It works in three steps:
- simple graphs representing AS events (Event Splicing Graphs) are built from input annotation
- RNA-Seq reads are aligned to the graphs
- graph alignments are analyzed to compute 𝜓 and ∆𝜓 values for each event
git clone https://github.com/AlgoLab/esgq.git
mamba create -c bioconda -n esgq python=3.9 suppa vg biopython gffutils
conda activate esgq
usage: ESGq [-h] [-t THREADS] -1 C1 [C1 ...] -2 C2 [C2 ...] FA GTF WD
required arguments:
FA Reference in FASTA format
GTF Gene annotation in GTF format
WD Output/Working directory
-1 C1 [C1 ...] Samples for condition 1 (can be gzipped)
-2 C2 [C2 ...] Samples for condition 2 (can be gzipped)
optional arguments:
-h, --help show this help message and exit
-t THREADS Number of threads to use (default: 1)
# Paired-end sample
python3 ESGq.py example/ref.fa example/gene.gtf example/OUT-PE -1 example/A_1.fq,example/A_2.fq example/B_1.fq,example/B_2.fq -2 example/C_1.fq,example/C_2.fq example/D_1.fq,example/D_2.fq
# Single-end sample
python3 ESGq.py example/ref.fa example/gene.gtf example/OUT-SE -1 example/A_1.fq example/B_1.fq -2 example/C_1.fq example/D_1.fq
Results are stored in the events.dpsi
file saved in the output directory. For each event (first column), it reports the 𝜓 value per each replicate and the ∆𝜓 (last column).