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onlineFDR: an R package to control the false discovery rate for growing data repositories.
Robertson, David S; Wildenhain, Jan; Javanmard, Adel; Karp, Natasha A.
Affiliation
  • Robertson DS; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
  • Wildenhain J; Quantitative Biology, Discovery Sciences, IMED Biotech Unit, AstraZeneca, Cambridge, UK.
  • Javanmard A; Department of Data Sciences and Operations, University of Southern California, Los Angeles, CA, USA.
  • Karp NA; Quantitative Biology, Discovery Sciences, IMED Biotech Unit, AstraZeneca, Cambridge, UK.
Bioinformatics ; 35(20): 4196-4199, 2019 10 15.
Article in En | MEDLINE | ID: mdl-30873526
ABSTRACT

SUMMARY:

In many areas of biological research, hypotheses are tested in a sequential manner, without having access to future P-values or even the number of hypotheses to be tested. A key setting where this online hypothesis testing occurs is in the context of publicly available data repositories, where the family of hypotheses to be tested is continually growing as new data is accumulated over time. Recently, Javanmard and Montanari proposed the first procedures that control the FDR for online hypothesis testing. We present an R package, onlineFDR, which implements these procedures and provides wrapper functions to apply them to a historic dataset or a growing data repository. AVAILABILITY AND IMPLEMENTATION The R package is freely available through Bioconductor (http//www.bioconductor.org/packages/onlineFDR). SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2019 Type: Article Affiliation country: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2019 Type: Article Affiliation country: United kingdom