alternative-splicing

You can analyze alternative splicing by inputting aligned RNA-seq reads, junction summaries, and transcript annotations to identify and quantify splice events, generating event tables and sashimi-ready outputs.

Differential isoform switching involves changes in isoform usage across conditions. You assess it using RNA-seq data to detect alternative splicing variations and generate isoform usage summaries.

Yes, you can generate sashimi-ready outputs from aligned RNA-seq reads and transcript annotations. The workflow processes junction summaries to visualize splice events and isoform usage.

Yes, splice-aware quantification tools are required for isoform-level splicing analysis. They process aligned RNA-seq reads alongside data manipulation and plotting libraries to quantify isoform usage accurately.

The best way to perform splice-quality assessment is using a QC-focused workflow that evaluates RNA-seq junctions and annotations, producing QC metrics and referencing appropriate tool selection parameters.

Alternative splicing analysis requires transcript annotations because they provide the reference junctions and isoform structures needed to identify splice events and quantify isoform usage from aligned RNA-seq reads.