Quantification

The quantification step involves remapping and quantifying transcripts to the de novo transcriptome.

Minimap2 is first to map the reads to the transcriptome. Then, few custom scripts are used to normalize the reads using DESeq2 and calculate TPMs.

One thing to note here is that because Gffcompare filters redundant transcripts, there could be a potential loss of transcripts with alternative start and stop sites. As such, the mapping index was created from only non-redundant transcripts rather than filtering the transcripts after mapping.

Usage

Input - Results/Gffcompare/nanopore.combined.gtf

Output - Results/Quantification/all_counts_deseq2norm_all.txt"

snakemake

Configuration

Below are changes that can be configured in the config.yaml file or explicitly specified in the command line.

Minimap2

minimap2_opts: -uf - Required for stranded data.

maximum_secondary: 200 - Output at most these many secondary alignments.

secondary_score_ratio: 1 - Minimum secondary to primary score ratio to output secondary mappings.

Output Folder Structure

| -- IGV/
    | -- X.genome.bam
    | -- X.genome.bam.bai
    | -- X.transcriptome.bam
    | -- X.transcriptome.bam.bai
    ...
| -- Results/
    | -- Minimap2/
        | -- Transcriptome.mmi
    | -- Quantification/
        | -- X.bam
        | -- X.sorted.bam
        | -- X.sorted.bam.bai
        | -- X.counts
        ...
        | -- counts_all.txt
        | -- counts_deseq2norm_all.txt