Journal article

Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses

Nucleic acids research | Published : 2015

Open access

Abstract

© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates ..

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Grants

Awarded by National Science Foundation


Funding Acknowledgements

National Health and Medical Research Council (NHMRC) Project Grant [1050661 to M.E.R., G.K.S., M.L.A.L.; 1045936 to M.E.B., M.E.R.]; Victorian State Government Operational Infrastructure Support and Australian Government NHMRC IRIISS. Funding for open access charge: NHMRC Project Grant [1050661].