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Transcript quantification

Definition
AI-generated

Transcript quantification estimates abundances for transcripts or genes from RNA-seq reads—via alignment-based assignment, pseudoalignment to a transcriptome, or assembly-informed models—producing counts or TPM-like scales for downstream differential expression analysis and eQTL inputs.

Topics
Sequencing Data Analysis Bioinformatics
Related
Differential expression analysis Expression Quantitative Trait Locus (eQTL) Gene expression

Why it matters in GWAS

Reliable expression and isoform abundances feed eQTL/sQTL resources, TWAS, and colocalization; quantification choices (reference annotation, bias correction, multi-mapping) affect which signals replicate across studies.

Example usage

"Gene and transcript quantification TPMs from pseudoalignment were used as phenotypes for tensor-QTL mapping."

Differential expression analysis Expression Quantitative Trait Locus (eQTL) Gene expression Pseudoalignment RNA Sequencing (RNA-seq) Transcript Transcriptome-Wide Association Study (TWAS)
Related-term network

Click any node to open that term page.

Node order. The current term is first. Next come every page linked from Related terms, in the same top-to-bottom order as that list. Then new terms appear in two-hop layers: for each of those direct neighbors (in that same order), their related terms are appended if not already listed. A third pass does the same for two-hop nodes. The walk stops when a fixed maximum number of nodes is reached.

References

  • Bray NL, Pimentel H, Melsted P, Pachter L. (2016). Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol.
← Transcript Assembly Transcription →

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