The functional false discovery rate with applications to genomics
© The Author 2019. Published by Oxford University Press..
The false discovery rate (FDR) measures the proportion of false discoveries among a set of hypothesis tests called significant. This quantity is typically estimated based on p-values or test statistics. In some scenarios, there is additional information available that may be used to more accurately estimate the FDR. We develop a new framework for formulating and estimating FDRs and q-values when an additional piece of information, which we call an "informative variable", is available. For a given test, the informative variable provides information about the prior probability a null hypothesis is true or the power of that particular test. The FDR is then treated as a function of this informative variable. We consider two applications in genomics. Our first application is a genetics of gene expression (eQTL) experiment in yeast where every genetic marker and gene expression trait pair are tested for associations. The informative variable in this case is the distance between each genetic marker and gene. Our second application is to detect differentially expressed genes in an RNA-seq study carried out in mice. The informative variable in this study is the per-gene read depth. The framework we develop is quite general, and it should be useful in a broad range of scientific applications.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2021 |
|---|---|
| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:22 |
|---|---|
| Enthalten in: |
Biostatistics (Oxford, England) - 22(2021), 1 vom: 28. Jan., Seite 68-81 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Chen, Xiongzhi [VerfasserIn] |
|---|
| Links: |
|---|
| Anmerkungen: |
Date Completed 14.10.2021 Date Revised 30.03.2024 published: Print Citation Status MEDLINE |
|---|
| doi: |
10.1093/biostatistics/kxz010 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM29753890X |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM29753890X | ||
| 003 | DE-627 | ||
| 005 | 20240330232339.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231225s2021 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1093/biostatistics/kxz010 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1356.xml |
| 035 | |a (DE-627)NLM29753890X | ||
| 035 | |a (NLM)31135886 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Chen, Xiongzhi |e verfasserin |4 aut | |
| 245 | 1 | 4 | |a The functional false discovery rate with applications to genomics |
| 264 | 1 | |c 2021 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 14.10.2021 | ||
| 500 | |a Date Revised 30.03.2024 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © The Author 2019. Published by Oxford University Press. | ||
| 520 | |a The false discovery rate (FDR) measures the proportion of false discoveries among a set of hypothesis tests called significant. This quantity is typically estimated based on p-values or test statistics. In some scenarios, there is additional information available that may be used to more accurately estimate the FDR. We develop a new framework for formulating and estimating FDRs and q-values when an additional piece of information, which we call an "informative variable", is available. For a given test, the informative variable provides information about the prior probability a null hypothesis is true or the power of that particular test. The FDR is then treated as a function of this informative variable. We consider two applications in genomics. Our first application is a genetics of gene expression (eQTL) experiment in yeast where every genetic marker and gene expression trait pair are tested for associations. The informative variable in this case is the distance between each genetic marker and gene. Our second application is to detect differentially expressed genes in an RNA-seq study carried out in mice. The informative variable in this study is the per-gene read depth. The framework we develop is quite general, and it should be useful in a broad range of scientific applications | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
| 650 | 4 | |a Research Support, U.S. Gov't, Non-P.H.S. | |
| 650 | 4 | |a q-value | |
| 650 | 4 | |a FDR | |
| 650 | 4 | |a Functional data analysis | |
| 650 | 4 | |a Genetics of gene expression | |
| 650 | 4 | |a Kernel density estimation | |
| 650 | 4 | |a Local false discovery rate | |
| 650 | 4 | |a Multiple hypothesis testing | |
| 650 | 4 | |a RNA-seq | |
| 650 | 4 | |a Sequencing depth | |
| 650 | 4 | |a eQTL | |
| 650 | 7 | |a Genetic Markers |2 NLM | |
| 700 | 1 | |a Robinson, David G |e verfasserin |4 aut | |
| 700 | 1 | |a Storey, John D |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Biostatistics (Oxford, England) |d 2000 |g 22(2021), 1 vom: 28. Jan., Seite 68-81 |w (DE-627)NLM126770980 |x 1468-4357 |7 nnns |
| 773 | 1 | 8 | |g volume:22 |g year:2021 |g number:1 |g day:28 |g month:01 |g pages:68-81 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1093/biostatistics/kxz010 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 22 |j 2021 |e 1 |b 28 |c 01 |h 68-81 | ||