Evidence map›Paper›PMID 38741205›Full record

ArticleGenome biology2024

Commonly used software tools produce conflicting and overly-optimistic AUPRC values.

Wenyu Chen, Chen Miao, Zhenghao Zhang, Cathy Sin-Hang Fung, Ran Wang, Yizhen Chen, Yan Qian, Lixin Cheng, Kevin Y Yip, Stephen Kwok-Wing Tsui and 1 more

Abstract read
In one paragraph

Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Wenyu Chen *School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Chen Miao *School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Zhenghao ZhangDepartment of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Cathy Sin-Hang FungSchool of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Ran WangSchool of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Yizhen ChenDepartment of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Yan QianThe First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Lixin ChengShenzhen People's Hospital, First Affiliated Hospital of Southern University of Science and Technology, Second Clinical Medical College of Jinan University, Shenzhen, China.
Kevin Y YipDepartment of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China. kyip@sbpdiscovery.org.
Stephen Kwok-Wing TsuiSchool of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China. kwtsui@cuhk.edu.hk.
Qin CaoSchool of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China. qcao@cuhk.edu.hk.ORCID 0000-0002-3106-562X

Funding

Tumor Microenvironment and Cancer ImmunologyP30CA030199 · NCI · SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE · PI ELENA B PASQUALE · 1985 to 2026
$107.2M
Spatial Mapping Senescent Cells Across the Mouse Lifespan by Multiplex Transcriptomics and EpigenomicsU54AG079758 · NIA · SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE · PI PETER D. ADAMS, Bing Ren · 2022 to 2026
$12.1M
Novel Neuroprotective Roles for the Alzheimer's Disease Risk Gene SORLA in Tau Pathology and PathogenesisR01AG085498 · NIA · SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE · PI Timothy Yikai Huang · 2024 to 2026
$2.6M
NCI NIH HHS P30 CA030199NCI NIH HHS P30CA030199NIA NIH HHS R01 AG085498NIA NIH HHS R01AG085498NIA NIH HHS U54 AG079758NIA NIH HHS U54AG079758
6 · The paper itself

Abstract

The precision-recall curve (PRC) and the area under the precision-recall curve (AUPRC) are useful for quantifying classification performance. They are commonly used in situations with imbalanced classes, such as cancer diagnosis and cell type annotation. We evaluate 10 popular tools for plotting PRC and computing AUPRC, which were collectively used in more than 3000 published studies. We find the AUPRC values computed by the tools rank classifiers differently and some tools produce overly-optimistic results.

Indexed as

SoftwareArea Under CurveComputational BiologyHumans

Identifiers

PMID38741205
PMCPMC11089773

What OpenQuestion holds

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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.