Evidence map›Paper›PMID 33466792›Full record

ArticleMetabolites2021

Comprehensive Comparative Analysis of Local False Discovery Rate Control Methods.

Shin June Kim, Youngjae Oh, Jaesik Jeong

Abstract read
In one paragraph

Article in Metabolites, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Shin June KimDepartment of Mathematics and Statistics, Chonnam National University, Gwangju 61186, Korea.
Youngjae OhDepartment of Mathematics and Statistics, Chonnam National University, Gwangju 61186, Korea.ORCID 0000-0002-9980-4812
Jaesik JeongDepartment of Mathematics and Statistics, Chonnam National University, Gwangju 61186, Korea.ORCID 0000-0001-8278-1135

Funding

BK21 FOUR by Ministry of Education 21A20132212094National Research Foundation of Korea (NRF-2018R1D1A1B07042372
6 · The paper itself

Abstract

Due to the advance in technology, the type of data is getting more complicated and large-scale. To analyze such complex data, more advanced technique is required. In case of omics data from two different groups, it is interesting to find significant biomarkers between two groups while controlling error rate such as false discovery rate (FDR). Over the last few decades, a lot of methods that control local false discovery rate have been developed, ranging from one-dimensional to

Indexed as

biomarkerfalse discovery ratefamilywise error ratelarge scale inference

Identifiers

PMID33466792
PMCPMC7830472

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.