## A. Unstranded and strand-specific read counting for features of interest

• Task 1: Rerun the RNA-Seq workflow with the toy data sets up to the read quantification step here. In the read quantification step with summarizeOverlaps generate count tables for exons by genes (eByg) of the following three strand modes:

1. Unstranded
2. Strand-specific for positive (sense) strand
3. Strand-specific for negative (antisense) strand

The solution for generating the unstranded read counts is given below. Note, the upstream steps 1-4 in the RNA-Seq workflow only need to be rerun to generate the proper inputs for the read counting. Thus, they are not required to be included in the homework results (see HW7.R below).

Before attempting to solve this homework task please read the vignette Counting reads with summarizeOverlaps (here) from the GenomicAlignments package that defines the summarizeOverlap function .

• Task 2: Provide R code that demonstrates that the two strand-specific count tables sum up to the values of the unstranded count table.

• Task 3: Explain the utility (biological relevance) of the different strand counting modes used under Task 1. Include your explanation as comment text in your homework script (see HW7.R below).

## B. Read counting for different feature types

• Task 4: Compute strand-specific count tables for the positive (sense) strand of the following feature types:

1. Genes
2. Exons
3. Exons by genes
4. Introns by transcripts
5. 5’-UTRs by transcripts

## C. DEG analysis

• Task 5: Perform the DEG analysis with edgeR as outlined under section 6 of the RNA-Seq workflow here. Use in one case for the DEG analysis the unstranded count table as input (from Task 1.1) and in another the sense strand count table (from Task 1.2). Compare the DEG result of the two methods in two separate 4-way Venn diagrams for the same sample comparisons used in the workflow example here.

1. 4-way Venn diagram for unstranded count table
2. 4-way Venn diagram for sense strand count table

## Homework submission

Assemble the code from the homework assignments A-C in a single R script (HW7.R) and upload it to your private GitHub repository under Homework/HW7/HW7.R. Please do not upload any data such as count tables or plots with your homework.

## Due date

This homework is due in one week on Thu, May 10th at 6:00 PM.

See here