Nanopore reads are ideal for capturing full-length transcriptomic information. As such we have implemented workflows for analysing nanopore cDNA and RNA sequencing data. The wf-transcriptomics workflow provides functionality for differential gene expression, differential transcript usage, and novel isoform detection. This workflow is described in detail at its GitHub documentation page and is available through both the command line and the EPI2ME Desktop Application.

Another workflow in the transcriptomes space is the wf-single-cell workflow that has been implemented to facilitate the analysis of 10X Genomics libraries that have been sequenced using a PromethION device. The code and documentation for the wf-single-cell workflow is available here and may also be run from the command line and through the EPI2ME Desktop Application.

These workflows incorporate well-known bioinformatics methods for the assessment and analysis of cDNA and RNA data. For example, to identify differentially expressed genes, you would typically map reads to a reference genome (or transcriptome), tabulate the number of reads overlapping each gene, and then compare these counts from a control sample against an experimental sample.

This allows you to identify genes and transcripts that are over- or under-represented in the experimental sample compared to the control samples. Specific recommendations for tools within these workflows are described in both EPI2ME and on our Applications page.

It is important to note that many alignment tools will have parameters specific to cDNA and RNA data, which allow for the alignment of reads over splice junctions. This is particularly important when trying to identify and annotate novel isoforms.