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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Power analysis of transcriptome-wide association study: Implications for practical protocol choice
Chen Cao, Bowei Ding, Qing Li, et al.
PLoS Genetics (2021) Vol. 17, Iss. 2, pp. e1009405-e1009405
Open Access | Times Cited: 67

Showing 1-25 of 67 citing articles:

webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study
Chen Cao, Jianhua Wang, Devin Kwok, et al.
Nucleic Acids Research (2021) Vol. 50, Iss. D1, pp. D1123-D1130
Open Access | Times Cited: 338
MOSTWAS: Multi-Omic Strategies for Transcriptome-Wide Association Studies
Arjun Bhattacharya, Yun Li, Michael I. Love
PLoS Genetics (2021) Vol. 17, Iss. 3, pp. e1009398-e1009398
Open Access | Times Cited: 66
Identification of shared and differentiating genetic architecture for autism spectrum disorder, attention-deficit hyperactivity disorder and case subgroups
Manuel Mattheisen, Jakob Grove, Thomas D. Als, et al.
Nature Genetics (2022) Vol. 54, Iss. 10, pp. 1470-1478
Open Access | Times Cited: 52
TWAS Atlas: a curated knowledgebase of transcriptome-wide association studies
Mingming Lu, Yadong Zhang, Fengchun Yang, et al.
Nucleic Acids Research (2022) Vol. 51, Iss. D1, pp. D1179-D1187
Open Access | Times Cited: 41
Isoform-level transcriptome-wide association uncovers genetic risk mechanisms for neuropsychiatric disorders in the human brain
Arjun Bhattacharya, Daniel Vo, Connor Jops, et al.
Nature Genetics (2023) Vol. 55, Iss. 12, pp. 2117-2128
Open Access | Times Cited: 33
OTTERS: a powerful TWAS framework leveraging summary-level reference data
Qile Dai, Geyu Zhou, Hongyu Zhao, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 27
Placental genomics mediates genetic associations with complex health traits and disease
Arjun Bhattacharya, Anastasia N. Freedman, Vennela Avula, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 37
Best practices for multi-ancestry, meta-analytic transcriptome-wide association studies: Lessons from the Global Biobank Meta-analysis Initiative
Arjun Bhattacharya, Jibril Hirbo, Dan Zhou, et al.
Cell Genomics (2022) Vol. 2, Iss. 10, pp. 100180-100180
Open Access | Times Cited: 31
Research progress and applications of genome‐wide association study in farm animals
Xiaodong Tan, Zhengxiao He, Alan G. Fahey, et al.
Animal Research and One Health (2023) Vol. 1, Iss. 1, pp. 56-77
Open Access | Times Cited: 21
CapsNet-LDA: predicting lncRNA-disease associations using attention mechanism and capsule network based on multi-view data
Zequn Zhang, Junlin Xu, Yanan Wu, et al.
Briefings in Bioinformatics (2022) Vol. 24, Iss. 1
Closed Access | Times Cited: 27
Integrating transcription factor occupancy with transcriptome-wide association analysis identifies susceptibility genes in human cancers
Jingni He, Wanqing Wen, Alicia Beeghly, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 26
Disentangling genetic feature selection and aggregation in transcriptome-wide association studies
Chen Cao, Pathum Kossinna, Devin Kwok, et al.
Genetics (2021) Vol. 220, Iss. 2
Open Access | Times Cited: 32
TIGAR-V2: Efficient TWAS tool with nonparametric Bayesian eQTL weights of 49 tissue types from GTEx V8
Randy L. Parrish, Greg Gibson, Michael P. Epstein, et al.
Human Genetics and Genomics Advances (2021) Vol. 3, Iss. 1, pp. 100068-100068
Open Access | Times Cited: 28
RAVAR: a curated repository for rare variant–trait associations
Chen Cao, Mengting Shao, Chunman Zuo, et al.
Nucleic Acids Research (2023) Vol. 52, Iss. D1, pp. D990-D997
Open Access | Times Cited: 11
Novel Alzheimer’s disease genes and epistasis identified using machine learning GWAS platform
Mischa Lundberg, Letitia M. F. Sng, Piotr Szul, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 11
Improving polygenic prediction from summary data by learning patterns of effect sharing across multiple phenotypes
Deborah Kunkel, Peter Sørensen, Vijay Shankar, et al.
PLoS Genetics (2025) Vol. 21, Iss. 1, pp. e1011519-e1011519
Open Access
Transcriptome-wide association study of alternative polyadenylation identifies susceptibility genes in non-small cell lung cancer
Xiaohang Xu, Sicong Wang, Hanyi Zhou, et al.
Oncogene (2025)
Open Access
Enhancing nonlinear transcriptome- and proteome-wide association studies via trait imputation with applications to Alzheimer’s disease
Ruoyu He, Jingchen Ren, Mykhaylo M. Malakhov, et al.
PLoS Genetics (2025) Vol. 21, Iss. 4, pp. e1011659-e1011659
Open Access
Adaptive deep propagation graph neural network for predicting miRNA–disease associations
Hua Hu, Huan Zhao, Tangbo Zhong, et al.
Briefings in Functional Genomics (2023) Vol. 22, Iss. 5, pp. 453-462
Closed Access | Times Cited: 9
Identification of drug-side effect association via correntropy-loss based matrix factorization with neural tangent kernel
Yijie Ding, Hongmei Zhou, Quan Zou, et al.
Methods (2023) Vol. 219, pp. 73-81
Closed Access | Times Cited: 9
Investigating the role of common cis-regulatory variants in modifying penetrance of putatively damaging, inherited variants in severe neurodevelopmental disorders
Emilie M. Wigdor, Kaitlin E. Samocha, Ruth Y. Eberhardt, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
Leveraging Random Effects in Cistrome‐Wide Association Studies for Decoding the Genetic Determinants of Prostate Cancer
Mengting Shao, Min Tian, Kaiyang Chen, et al.
Advanced Science (2024)
Open Access | Times Cited: 2
Statistical power of transcriptome‐wide association studies
Ruoyu He, Haoran Xue, Wei Pan
Genetic Epidemiology (2022) Vol. 46, Iss. 8, pp. 572-588
Open Access | Times Cited: 11
Identifying Novel Drug Targets for Epilepsy Through a Brain Transcriptome-Wide Association Study and Protein-Wide Association Study with Chemical-Gene-Interaction Analysis
Mengnan Lu, Ruoyang Feng, Chenglin Zhang, et al.
Molecular Neurobiology (2023) Vol. 60, Iss. 9, pp. 5055-5066
Open Access | Times Cited: 6
Network propagation for GWAS analysis: a practical guide to leveraging molecular networks for disease gene discovery
Giovanni Visonà, Emmanuelle Bouzigon, Florence Démenais, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 2
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