RNA Expression Analysis Simulator
Set of scripts to simulate thousands of gene by sample count tables matching statistical properties of RNA-Seq based on the negative binomial (NB), log-normal (LN), and gamma-multinomial distributions. Uses customizable parameters to simulate data matching all kinds of scenarious from high to low biological variation, deep or shallow sequencing, with different proportions of DEX genes at different effect sizes.
Also contains scripts to analyze simulated data for differential expression (DEX) using a number of different algorithms (DESeq2, edgeR, voom-limma, ALDEx2, t-test, Mann-Whitney test) and normalizations (no scaling, scaling to number of counted reads, scaling to upper-quartile, TMM, RLE, and quantile normalization).
Designed to make runnning dozens of analyses over thousands of simulations easy. Results derived from this program are soon to be posted on bioRxiv and later published.
A grid search engine
Runs r * c searches, where 'r' is the number of row terms (commonly genes) and 'c' is the number of column terms (commonly tissues or diseases) and reports the numbers of resulting hits in scientific journal databases like PubMed, so you can easily look for overlaps in the literature between genes and phenotypes
Confirms sample match between genotyping and RNA-Seq data based on SNPs
Python script to compare a set of RNA-Seq samples with a set of genotyping data samples and identify matches based on variants in a comprehensive manner, finding matches you don't expect as well as the matches you expect and the mismatches you are primarily looking for. Aid for general RNA-Seq QC.