escott55/rnaseq_toe1

Scripts for analyzing splicing efficiency, expression, and exon inclusion in RNAseq data

TOE1 Analysis

This repository includes three separate RNA-seq analyses, produced to investigate different possible outcomes of a splicing defect.

TODO

1. Make a full processing pipeline for the samples
2. Adjust colors in splicing plot by log-fold-change
3. Perform a tRNA analysis
4. Do an analysis based on intron location

Expression

This code base uses DESeq2 to calculate normalized expression values for all genes and identifies significantly differentially expressed genes by a Case vs Control comparison.

Intron Inclusion

Emulates an analysis from the U2 paper (should add link here). Briefly we calculate read counts for intronic and extronic regions using HT-seq. Calculate FPKM values and convert these to the proportion of transcript inclusion for each intron, as a function of the max value from adjacent exons.

Exon Usage

Run an analysis to identify exons with significantly differential expression.

Prerequisite python packages

1. Rpy2 with ggplot2 installed as part of the R installation
2. Pandas for dataframes

Running The Analysis

Expression Analysis:

cd scripts/expression/
./run_expression_analysis.R

Intron Inclusion Analysis:

python scripts/introninc/run_region_read_counts.py
python scripts/introninc/run_intron_inclusion_analysis.py