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Awen He

dblp:197/8117 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2018
0000-0003-1038-9163ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genomics
genome-wide association study
0.312017
Tissue-specific pathway association analysis using genome-wide association study summaries · Bioinform. 2017
Bioinformatics and computational biology
genomics
0.312017
Tissue-specific pathway association analysis using genome-wide association study summaries · Bioinform. 2017
Bioinformatics and computational biology › genomics › genome-wide association study
pathway-based association analysis
0.312017
Tissue-specific pathway association analysis using genome-wide association study summaries · Bioinform. 2017
Bioinformatics and computational biology › gene expression analysis › gene expression pattern analysis
tissue-specific gene expression
0.312017
Tissue-specific pathway association analysis using genome-wide association study summaries · Bioinform. 2017

Methods — techniques the papers use, named apart from their topics

enrichment analysis · 0.3
YearPublicationVenuePosition
2018 GWAS summary-based pathway analysis correcting for the genetic confounding impact of environmental exposures
abstract
Genome-wide association study (GWAS)-based pathway association analysis is a powerful approach for the genetic studies of human complex diseases. However, the genetic confounding effects of environment exposure-related genes can decrease the accuracy of GWAS-based pathway association analysis of target diseases. In this study, we developed a pathway association analysis approach, named Mendelian randomization-based pathway enrichment analysis (MRPEA), which was capable of correcting the genetic confounding effects of environmental exposures, using the GWAS summary data of environmental exposures. After analyzing the real GWAS summary data of cardiovascular disease and cigarette smoking, we observed significantly improved performance of MRPEA compared with traditional pathway association analysis (TPAA) without adjusting for environmental exposures. Further, simulation studies found that MRPEA generally outperformed TPAA under various scenarios. We hope that MRPEA could help to fill the gap of TPAA and identify novel causal pathways for complex diseases.
Qianrui Fan, Feng Zhang 0034, Jingcan Hao, Awen He, Yan Wen 0003, Cuiyan Wu, Yujie Ning, Xiong Guo
Briefings Bioinform.6
2017 Tissue-specific pathway association analysis using genome-wide association study summaries
abstract
MOTIVATION: Pathway association analysis has made great achievements in elucidating the genetic basis of human complex diseases. However, current pathway association analysis approaches fail to consider tissue-specificity. RESULTS: We developed a tissue-specific pathway interaction enrichment analysis algorithm (TPIEA). TPIEA was applied to two large Caucasian and Chinese genome-wide association study summary datasets of bone mineral density (BMD). TPIEA identified several significant pathways for BMD [false discovery rate (FDR) < 0.05], such as KEGG FOCAL ADHESION and KEGG AXON GUIDANCE, which had been demonstrated to be involved in the development of osteoporosis. We also compared the performance of TPIEA and classical pathway enrichment analysis, and TPIEA presented improved performance in recognizing disease relevant pathways. TPIEA may help to fill the gap of classic pathway association analysis approaches by considering tissue specificity. AVAILABILITY AND IMPLEMENTATION: The online web tool of TPIEA is available at https://sourceforge.net/projects/tpieav1/files CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online.
Jingcan Hao, Qianrui Fan, Awen He, Yan Wen 0003, Xiong Guo, Cuiyan Wu, Tielin Yang, Hui Shen 0007, Xiangding Chen, Qing Tian 0004, Lijun Tan, Hong-Wen Deng, Feng Zhang 0034
Bioinform.5