Evidence map›Paper›PMID 35610053›Full record

ArticleNucleic acids research2022

WebCSEA: web-based cell-type-specific enrichment analysis of genes.

Yulin Dai, Ruifeng Hu, Andi Liu, Kyung Serk Cho, Astrid Marilyn Manuel, Xiaoyang Li, Xianjun Dong, Peilin Jia, Zhongming Zhao

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
95citing papers in PubMed, 3 pooled it
12.5field-weighted citation impact, top 1% of its field
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

95 citing papers in PubMed, 3 syntheses or guidelines pooled it, 140 citations in OpenAlex.

  1. Pooled it
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  4. Article
  5. celltypeEnrich: a consensus-based scRNA-seq cluster annotation tool.bioRxiv : the preprint server for biology · 2026
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  13. Integrated single-cell transcriptomic analysis identifiesBiochemistry and biophysics reports · 2026
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35 more citing papers are in PubMed but not listed here.

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

9 authors at 3 institutions in 1 country.

Yulin DaiCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.ORCID 0000-0003-1874-7893
Ruifeng HuCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.ORCID 0000-0001-5549-3082
Andi LiuCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Kyung Serk ChoCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Astrid Marilyn ManuelCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Xiaoyang LiCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Xianjun DongCenter for Advanced Parkinson Research, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.ORCID 0000-0002-8052-9320
Peilin JiaCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.ORCID 0000-0003-4523-4153
Zhongming ZhaoCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.ORCID 0000-0002-3477-0914
The University of Texas Health Science Center at Houston · USBrigham and Women's Hospital · USThe University of Texas MD Anderson Cancer Center · US

Funding

TRAINING PROGRAM IN COMPUTATIONAL BIOLOGY AND MEDICINET15LM007093 · NLM · RICE UNIVERSITY · PI Lydia E. Kavraki · 1992 to 2026
$20.8M
Transforming dbGaP genetic and genomic data to FAIR-ready by artificial intelligence and machine learning algorithmsR01LM012806 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Zhongming Zhao · 2017 to 2026
$3.7M
Training in Precision Environmental Health SciencesT32ES027801 · NIEHS · BAYLOR COLLEGE OF MEDICINE · PI Cheryl L. Walker · 2018 to 2026
$2.8M
Role of cellular metabolism in palate morphogenesisR01DE029818 · NIDCR · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI IWATA, JUNICHI, ZHAO, ZHONGMING · 2020 to 2024
$1.8M
Deep learning for decoding genetic regulation and cellular maps in craniofacial developmentR01DE030122 · NIDCR · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI IWATA, JUNICHI, ZHAO, ZHONGMING · 2021 to 2023
$1.7M
NIDCR NIH HHS R01 DE029818NIDCR NIH HHS R01 DE030122NIEHS NIH HHS T32 ES027801NLM NIH HHS R01 LM012806NLM NIH HHS T15 LM007093
6 · The paper itself

Abstract

Human complex traits and common diseases show tissue- and cell-type- specificity. Recently, single-cell RNA sequencing (scRNA-seq) technology has successfully depicted cellular heterogeneity in human tissue, providing an unprecedented opportunity to understand the context-specific expression of complex trait-associated genes in human tissue-cell types (TCs). Here, we present the first web-based application to quickly assess the cell-type-specificity of genes, named Web-based Cell-type Specific Enrichment Analysis of Genes (WebCSEA, available at https://bioinfo.uth.edu/webcsea/). Specifically, we curated a total of 111 scRNA-seq panels of human tissues and 1,355 TCs from 61 different general tissues across 11 human organ systems. We adapted our previous decoding tissue-specificity (deTS) algorithm to measure the enrichment for each tissue-cell type (TC). To overcome the potential bias from the number of signature genes between different TCs, we further developed a permutation-based method that accurately estimates the TC-specificity of a given inquiry gene list. WebCSEA also provides an interactive heatmap that displays the cell-type specificity across 1355 human TCs, and other interactive and static visualizations of cell-type specificity by human organ system, developmental stage, and top-ranked tissues and cell types. In short, WebCSEA is a one-click application that provides a comprehensive exploration of the TC-specificity of genes among human major TC map.

Indexed as

Gene Expression ProfilingSingle-Cell AnalysisSoftwareAlgorithmsHumansInternetMultifactorial InheritanceSequence Analysis, RNA

Identifiers

PMID35610053
PMCPMC10359109
OpenAlexW4282926069

What Socratic 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 Socratic graph.