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Hi all,
On behalf of myself and co-authors (Alyssa Frazee and Jeff Leek in particular), I wanted to call people's attention to a preprint we just published describing Ballgown:
http://biorxiv.org/content/early/2014/03/30/003665
Abstract:
We have built a statistical package called Ballgown for estimating differential expression of genes, transcripts, or exons from RNA sequencing experiments. Ballgown is designed to work with the popular Cufflinks transcript assembly software and uses well-motivated statistical methods to provide estimates of changes in expression. It permits statistical analysis at the transcript level for a wide variety of experimental designs, allows adjustment for confounders, and handles studies with continuous covariates. Ballgown provides improved statistical significance estimates as compared to the Cuffdiff differential expression tool included with Cufflinks. We demonstrate the flexibility of the Ballgown package by re-analyzing 667 samples from the GEUVADIS study to identify transcript-level eQTLs and identify non-linear artifacts in transcript data. Our package is freely available from:
https://github.com/alyssafrazee/ballgown
Could make your much life easier if you spend a lot of time interpreting output from Cufflinks.
Best,
Ben
On behalf of myself and co-authors (Alyssa Frazee and Jeff Leek in particular), I wanted to call people's attention to a preprint we just published describing Ballgown:
http://biorxiv.org/content/early/2014/03/30/003665
Abstract:
We have built a statistical package called Ballgown for estimating differential expression of genes, transcripts, or exons from RNA sequencing experiments. Ballgown is designed to work with the popular Cufflinks transcript assembly software and uses well-motivated statistical methods to provide estimates of changes in expression. It permits statistical analysis at the transcript level for a wide variety of experimental designs, allows adjustment for confounders, and handles studies with continuous covariates. Ballgown provides improved statistical significance estimates as compared to the Cuffdiff differential expression tool included with Cufflinks. We demonstrate the flexibility of the Ballgown package by re-analyzing 667 samples from the GEUVADIS study to identify transcript-level eQTLs and identify non-linear artifacts in transcript data. Our package is freely available from:
https://github.com/alyssafrazee/ballgown
Could make your much life easier if you spend a lot of time interpreting output from Cufflinks.
Best,
Ben