Evidence map›Paper›PMID 30873526›Full record

ArticleBioinformatics (Oxford, England)2019

onlineFDR: an R package to control the false discovery rate for growing data repositories.

David S Robertson, Jan Wildenhain, Adel Javanmard, Natasha A Karp

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Online multiple hypothesis testing.Statistical science : a review journal of the Institute of Mathematical Statistics · 2023
    Article
  4. Article
  5. Global FDR control across multiple RNAseq experiments.Bioinformatics (Oxford, England) · 2023
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

David S RobertsonMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
Jan WildenhainQuantitative Biology, Discovery Sciences, IMED Biotech Unit, AstraZeneca, Cambridge, UK.
Adel JavanmardDepartment of Data Sciences and Operations, University of Southern California, Los Angeles, CA, USA.
Natasha A KarpQuantitative Biology, Discovery Sciences, IMED Biotech Unit, AstraZeneca, Cambridge, UK.

Funding

Medical Research Council MC_UU_00002/6
6 · The paper itself

Abstract

summaryIn 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.

Indexed as

Software

Identifiers

PMID30873526
PMCPMC6792083

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.