Evidence map›Paper›PMID 33574831›Full record

ArticleFrontiers in genetics2020

Integrated Weighted Gene Co-expression Network Analysis Identified That

Bin Qi, Jian-Hong Chen, Lin Tao, Chuan-Meng Zhu, Yong Wang, Guo-Xiong Deng, Liu Miao

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

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  4. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Bin QiDepartments of Cardiology, Liuzhou People's Hospital, Liuzhou, China.
Jian-Hong ChenDepartments of Cardiology, Liuzhou People's Hospital, Liuzhou, China.
Lin TaoDepartments of Cardiology, Liuzhou People's Hospital, Liuzhou, China.
Chuan-Meng ZhuDepartments of Cardiology, Liuzhou People's Hospital, Liuzhou, China.
Yong WangDepartments of Cardiology, Liuzhou People's Hospital, Liuzhou, China.
Guo-Xiong DengDepartments of Cardiology, The First People's Hospital of Nanning, Nanning, China.
Liu MiaoDepartments of Cardiology, Liuzhou People's Hospital, Liuzhou, China.
Liuzhou General Hospital · CNFirst People's Hospital of Nanning · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current research attempted to identify possible hub genes and pathways of coronary artery disease (CAD) and to detect the possible mechanisms. Array data from GSE90074 were downloaded from the Gene Expression Omnibus (GEO) database. Integrated weighted gene co-expression network analysis (WGCNA) was performed to analyze the gene module and clinical characteristics. Gene Ontology annotation (GO), Disease Ontology (DO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by clusterProfiler and the DOSE package in R. A protein-protein interaction (PPI) network was established using Cytoscape software, and significant modules were analyzed using Molecular Complex Detection (MCODE) to identify hub genes. Then, further functional validation of hub genes in other microarrays and population samples was performed, and survival analysis was performed to investigate the prognosis. A total of 660 genes were located in three modules and associated with CAD. GO functions identified 484 biological processes, 39 cellular components, and 22 molecular functions with an adjusted

Indexed as

coronary artery diseasefunctional enrichmentfunctional validationgene expression omnibusintegrated weighted gene co-expression network analysisprognostic analysis

Identifiers

PMID33574831
PMCPMC7870792
OpenAlexW3122422201

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.