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How do I analyse transcriptomic data?
How do I analyse transcriptomic data?
Updated over a week ago

Nanopore reads are ideal for capturing full-length transcriptomic information.

As such several tools and analysis workflows exist for analysing nanopore cDNA and RNA sequencing data.

Workflows such as differential gene expression, differential transcript usage, and isoform detection are described in detail in our analysis platform EPI2ME Labs.

These workflows incorporate several well-known processes for the assessment and analysis of cDNA and RNA data. For example, to identify differentially expressed genes, users will 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 users 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 Labs 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.

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