Title |
stageR: a general stage-wise method for controlling the gene-level false discovery rate in differential expression and differential transcript usage
|
---|---|
Published in |
Genome Biology, August 2017
|
DOI | 10.1186/s13059-017-1277-0 |
Pubmed ID | |
Authors |
Koen Van den Berge, Charlotte Soneson, Mark D. Robinson, Lieven Clement |
Abstract |
RNA sequencing studies with complex designs and transcript-resolution analyses involve multiple hypotheses per gene; however, conventional approaches fail to control the false discovery rate (FDR) at gene level. We propose stageR, a two-stage testing paradigm that leverages the increased power of aggregated gene-level tests and allows post hoc assessment for significant genes. This method provides gene-level FDR control and boosts power for testing interaction effects. In transcript-level analysis, it provides a framework that performs powerful gene-level tests while maintaining biological interpretation at transcript-level resolution. The procedure is applicable whenever individual hypotheses can be aggregated, providing a unified framework for complex high-throughput experiments. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 12 | 27% |
Australia | 3 | 7% |
Netherlands | 3 | 7% |
Germany | 3 | 7% |
Switzerland | 2 | 4% |
France | 2 | 4% |
Belgium | 2 | 4% |
United Kingdom | 2 | 4% |
Taiwan | 1 | 2% |
Other | 2 | 4% |
Unknown | 13 | 29% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 29 | 64% |
Members of the public | 14 | 31% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Unknown | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 144 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 36 | 25% |
Student > Ph. D. Student | 33 | 23% |
Student > Master | 20 | 14% |
Student > Bachelor | 10 | 7% |
Other | 5 | 3% |
Other | 11 | 8% |
Unknown | 29 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 42 | 29% |
Biochemistry, Genetics and Molecular Biology | 38 | 26% |
Engineering | 7 | 5% |
Computer Science | 4 | 3% |
Medicine and Dentistry | 4 | 3% |
Other | 17 | 12% |
Unknown | 32 | 22% |