[BioC] running roast with 6 samples in 2 groups

Wu, Di dwu at fas.harvard.edu
Wed Jun 26 01:35:00 CEST 2013

Hi Julie,

Thank you for asking. What you described is an acceptable case. ROAST has increased power when you have extra samples that are not in the contrast but in the dataset, however it's not required to have those extra samples.
P value is still valid. 

Hope this help. Let me know if you have further questions.

Di Wu
Postdoctoral fellow
Harvard University, Statistics Department
Harvard Medical School
Science Center, 1 Oxford Street, Cambridge, MA 02138-2901 USA

From: bioconductor-bounces at r-project.org [bioconductor-bounces at r-project.org] on behalf of julie.leonard at syngenta.com [julie.leonard at syngenta.com]
Sent: Tuesday, June 25, 2013 4:38 PM
To: bioconductor at r-project.org
Subject: [BioC] running roast with 6 samples in 2 groups

   In the roast paper, the examples tended to have extra samples not used to define the contrast - which helped increase the degrees of freedom for the rotation test (e.g. 26 samples in a 3 group experiment; group 1 has 3 samples, group 2 has 3 samples and group 3 has 20 samples. - the contrast compared group 1 and group 2).   Is running roast on a dataset with 6 samples in 2 groups (3 test, 3 control) an acceptable use case or will the degrees of freedom be too small to get valid p-values?


Julie Leonard
Computational Biologist
Global Bioinformatics

Syngenta Biotechnology, Inc.
3054 E. Cornwallis Rd.
Research Triangle Park, NC 27709

julie.leonard at syngenta.com<mailto:julie.leonard at syngenta.com>

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