https://github.com/thelovelab/tximport
Transcript quantification import for modular pipelines
https://github.com/thelovelab/tximport
bioconductor deseq2 rnaseq
Last synced: 8 months ago
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Transcript quantification import for modular pipelines
- Host: GitHub
- URL: https://github.com/thelovelab/tximport
- Owner: thelovelab
- Created: 2015-11-18T13:13:13.000Z (over 10 years ago)
- Default Branch: devel
- Last Pushed: 2025-08-22T18:52:57.000Z (10 months ago)
- Last Synced: 2025-09-08T10:58:13.268Z (9 months ago)
- Topics: bioconductor, deseq2, rnaseq
- Language: R
- Homepage:
- Size: 368 KB
- Stars: 140
- Watchers: 14
- Forks: 34
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Changelog: NEWS
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# tximport
Import and summarize transcript-level estimates for transcript- and gene-level analysis
Description of methods and analysis described in:
* Charlotte Soneson, Michael I. Love, Mark D. Robinson.
[Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences](http://f1000research.com/articles/4-1521),
*F1000Research*, 4:1521, December 2015. doi: 10.12688/f1000research.7563.1
---
Imports transcript-level abundance, estimated counts and
transcript lengths, and summarizes into matrices for use with downstream
statistical analysis packages such as edgeR, DESeq2, limma-voom.
Average transcript length, weighted by
sample-specific transcript abundance estimates, is provided as a matrix
which can be used as an offset for different expression of
gene-level counts.
See examples in the [vignette](http://bioconductor.org/packages/release/bioc/vignettes/tximport/inst/doc/tximport.html).
Notes:
* tximport as of version 1.3.9 will import inferential replicates
(Gibbs samples or bootstrap samples) from Salmon, Sailfish or kallisto.
* Though we provide here functionality for performing gene-level
differential expression using summarized transcript-level estimates,
this is does not mean we suggest that users *only* perform gene-level
analysis. Gene-level differential expression can be complemented
with transcript- or exon-level analysis. The argument `txOut=TRUE`
can be used to generate transcript-level matrices.