publication . Preprint . Other literature type . 2014

largeQvalue: A program for calculating FDR estimates with large datasets

Brown, Andrew Anand;
Open Access
  • Published: 06 Oct 2014
  • Publisher: Cold Spring Harbor Laboratory
Abstract
<jats:p>This is an implementation of the R statistical software qvalue package (Alan Dabney, John D. Storey and with assistance from Gregory R. Warnes (). qvalue: Q-value estimation for false discovery rate control. R package version 1.34.0.), designed for use with large datasets where memory or computation time is limiting. In addition to estimating p values adjusted for multiple testing, the software outputs a script which can be pasted into R to produce diagnostic plots and report parameter estimates. This program runs almost 30 times faster and requests substantially less memory than the qvalue package when analysing 10 million p values on a high performance...
Funded by
WT
Project
  • Funder: Wellcome Trust (WT)

1000 Genomes Project Consortium. An integrated map of genetic variation from 1,092 human genomes. Nature, 491(7422):56{65, 2012.

Andrei Alexandrescu. The D Programming Language. Addison-Wesley Professional, 1st edition, 2010. ISBN 0321635361, 9780321635365.

Yoav Benjamini and Yosef Hochberg. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), pages 289{300, 1995. [OpenAIRE]

Andrew Anand Brown, Alfonso Buil, Ana Vin~uela, Tuuli Lappalainen, Hou-Feng Zheng, J Brent Richards, Kerrin S Small, Timothy D Spector, Emmanouil T Dermitzakis, and Richard Durbin. Genetic interactions a ecting human gene expression identi ed by variance association mapping. eLife, 3, 2014.

Alan Dabney, John D. Storey, and with assistance from Gregory R. Warnes. qvalue: Q-value estimation for false discovery rate control, 2014. R package version 1.34.0.

Tuuli Lappalainen, Michael Sammeth, Marc R Friedla&#x7f;nder, Peter AC't Hoen, Jean Monlong, Manuel A Rivas, Mar Gonzalez-Porta, Natalja Kurbatova, Thasso Griebel, Pedro G Ferreira, et al. Transcriptome and genome sequencing uncovers functional variation in humans. Nature, 2013.

R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, 2013. URL http://www.R-project.org/.

John D Storey. A direct approach to false discovery rates. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 64(3):479{498, 2002.

John D Storey and Robert Tibshirani. Statistical signi cance for genomewide studies. Proceedings of the National Academy of Sciences, 100(16):9440{9445, 2003. [OpenAIRE]

John D Storey, Jonathan E Taylor, and David Siegmund. Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a uni ed approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 66(1):187{205, 2004.

Hadley Wickham. ggplot2: elegant graphics for data analysis. Springer New York, 2009. ISBN 978-0-387-98140-6. URL http://had.co.nz/ggplot2/book.

Abstract
<jats:p>This is an implementation of the R statistical software qvalue package (Alan Dabney, John D. Storey and with assistance from Gregory R. Warnes (). qvalue: Q-value estimation for false discovery rate control. R package version 1.34.0.), designed for use with large datasets where memory or computation time is limiting. In addition to estimating p values adjusted for multiple testing, the software outputs a script which can be pasted into R to produce diagnostic plots and report parameter estimates. This program runs almost 30 times faster and requests substantially less memory than the qvalue package when analysing 10 million p values on a high performance...
Funded by
WT
Project
  • Funder: Wellcome Trust (WT)

1000 Genomes Project Consortium. An integrated map of genetic variation from 1,092 human genomes. Nature, 491(7422):56{65, 2012.

Andrei Alexandrescu. The D Programming Language. Addison-Wesley Professional, 1st edition, 2010. ISBN 0321635361, 9780321635365.

Yoav Benjamini and Yosef Hochberg. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), pages 289{300, 1995. [OpenAIRE]

Andrew Anand Brown, Alfonso Buil, Ana Vin~uela, Tuuli Lappalainen, Hou-Feng Zheng, J Brent Richards, Kerrin S Small, Timothy D Spector, Emmanouil T Dermitzakis, and Richard Durbin. Genetic interactions a ecting human gene expression identi ed by variance association mapping. eLife, 3, 2014.

Alan Dabney, John D. Storey, and with assistance from Gregory R. Warnes. qvalue: Q-value estimation for false discovery rate control, 2014. R package version 1.34.0.

Tuuli Lappalainen, Michael Sammeth, Marc R Friedla&#x7f;nder, Peter AC't Hoen, Jean Monlong, Manuel A Rivas, Mar Gonzalez-Porta, Natalja Kurbatova, Thasso Griebel, Pedro G Ferreira, et al. Transcriptome and genome sequencing uncovers functional variation in humans. Nature, 2013.

R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, 2013. URL http://www.R-project.org/.

John D Storey. A direct approach to false discovery rates. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 64(3):479{498, 2002.

John D Storey and Robert Tibshirani. Statistical signi cance for genomewide studies. Proceedings of the National Academy of Sciences, 100(16):9440{9445, 2003. [OpenAIRE]

John D Storey, Jonathan E Taylor, and David Siegmund. Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a uni ed approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 66(1):187{205, 2004.

Hadley Wickham. ggplot2: elegant graphics for data analysis. Springer New York, 2009. ISBN 978-0-387-98140-6. URL http://had.co.nz/ggplot2/book.

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