Workflow Tutorial

There are a variety of functions and tools implemented in detk for differential expression analysis. This example will assume that you have a raw counts matrix file that you have obtained from an RNASeq analysis using appropriate upstream tools, e.g. salmon transcriptome quantification or STAR + htseq-count.

Tool Tip

If you have a pipeline that produces individual counts files for each of your samples, our command line tool csvgather may be helpful to easily combine these files together into a single matrix.

Using detk, we will perform the following steps:

1. examine statistics of the counts matrix using the stats - Count Matrix Statistics module
2. filter genes based on the statistics we gathered previously using the filter - Filtering Count Matrices module and mini-language
3. normalize the counts matrix with the DESeq2 normalization method using the norm - Normalizing Count Matrices module
4. perform DESeq2 differential expression analysis for a condition of interest with the de - Differential Expression module

These pages contain a walkthrough tutorial of how to use detk for examining and analyzing a counts matrix file, like those produced by an RNASeq experiment.

• First detk principles
  • The Count Matrix
  • The Column Metadata File
• Calculating Counts Matrix Statistics
• Filtering a Counts Matrix File
• Normalization
• Performing Differential Expression
  • Firth Logistic Expression