ExCluster - ExCluster robustly detects differentially expressed exons
between two conditions of RNA-seq data, requiring at least two
independent biological replicates per condition
ExCluster flattens Ensembl and GENCODE GTF files into GFF
files, which are used to count reads per non-overlapping exon
bin from BAM files. This read counting is done using the
function featureCounts from the package Rsubread. Library sizes
are normalized across all biological replicates, and ExCluster
then compares two different conditions to detect signifcantly
differentially spliced genes. This process requires at least
two independent biological repliates per condition, and
ExCluster accepts only exactly two conditions at a time.
ExCluster ultimately produces false discovery rates (FDRs) per
gene, which are used to detect significance. Exon log2 fold
change (log2FC) means and variances may be plotted for each
significantly differentially spliced gene, which helps
scientists develop hypothesis and target differential splicing
events for RT-qPCR validation in the wet lab.