Consistent testing for recurrent genomic aberrations.

V Walter, F A Wright, A B Nobel

Abstract read

In one paragraph

Article in Biometrika, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

V WalterDepartment of Biochemistry and Molecular Biology, Pennyslvania State University College of Medicine, Milton S. Hershey Medical Center, 500 University Drive, P.O. Box 850, Hershey, Pennsylvania 17033 U.S.A.

F A WrightDepartment of Statistics, North Carolina State University Bioinformatics Research Center, Campus Box 7566, 2601 Stinson Drive, Raleigh, North Carolina 27695 U.S.A., fred_wright@ncsu.edu.

A B NobelDepartment of Statistics and Operations Research, CB 3260, University of North Carolina, Chapel Hill, North Carolina, 27599 U.S.A., nobel@email.unc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We consider the detection and identification of recurrent departures from stationary behaviour in genomic or similarly arranged data containing measurements at an ordered set of variables. Our primary focus is on departures that occur only at a single variable, or within a small window of contiguous variables, but involve more than one sample. This encompasses the identification of aberrant markers in genome-wide measurements of DNA copy number and DNA methylation, as well as meta-analyses of genome-wide association studies. We propose and analyse a cyclic shift-based procedure for testing recurrent departures from stationarity. Our analysis establishes the consistency of cyclic shift [Formula: see text]-values for datasets with a fixed set of samples as the number of observed variables tends to infinity, under the assumption that each sample is an independent realization of a stationary Markov chain. Our results apply to any test statistic satisfying a simple invariance condition.

Indexed as

ConsistencyDNA copy numberDNA methylationGenome-wide association studyHypothesis testing

Identifiers

PMID30799871

DOI10.1093/biomet/asv046

PMCPMC6372979

What OpenQuestion holds

Textmetadata

Read underepoch 390

Registered trials

None linked

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.