Author

Hongjian Qi

Columbia University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2 Genetics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:variant calling· 3 Research Focus:differential expression· 2 Organism:human· 2 Assay:whole-exome sequencing· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Yufeng SheniD· 4 shared Wendy K. ChungiD· 3 shared Alexander KitaygorodskyiD· 2 shared Bruce D. GelbiD· 2 shared Christine E. SeidmaniD· 2 shared Jonathan G. SeidmaniD· 2 shared Sarah U. MortoniD· 2 shared Steven R. DePalmaiD· 2 shared

Activity by Year

2017-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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4 shared papersBioinformatics

Yufeng ShenORCID

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Author profile →

4 papers

Recent·Most cited

Whole Genome De Novo Variant Identification with FreeBayes and Neural Network Approaches

Felix Richter, Sarah U. Morton, Hongjian Qi, Alexander Kitaygorodsky, Jiayao Wang, Jason G. Homsy, Steven R. DePalma, Nihir Patel, Bruce D. Gelb, Jonathan G. Seidman, Christine E. Seidman, Yufeng Shen

The paper develops a framework for de novo variant identification using FreeBayes and a neural network, achieving high accuracy in SNVs and indels through validation with Sanger sequencing.

bioRxiv · Mar 24, 2020 · PreprintGenomics

Early post-zygotic mutations contribute to congenital heart disease

Alexander Hsieh, Sarah U. Morton, Jon A. L. Willcox, Joshua Gorham, Angela C. Tai, Hongjian Qi, Steven R. DePalma, David M. McKean, Emily Griffin, Kathryn B. Manheimer, Daniel Bernstein, Richard W. Kim, Jane W. Newburger, George Arthur Porter Jr., Deepak Srivastava, , Yufeng Shen

The paper identifies mosaic mutations in blood and cardiac tissue from CHD patients, finding 1% of cases have detectable mosaic variants that may contribute to congenital heart disease.

bioRxiv · Aug 13, 2019 · PreprintBioinformatics

MVP: predicting pathogenicity of missense variants by deep learning

Hongjian Qi, Chen Chen, Haicang Zhang, John J. Long, Wendy K. Chung, Yongtao Guan, Yufeng Shen

MVP uses deep learning to predict pathogenicity of missense variants, outperforming previous methods in prioritizing pathogenic variants.

bioRxiv · Apr 2, 2018 · PreprintBioinformatics

Genetic analysis of de novo variants reveals sex differences in complex and isolated congenital diaphragmatic hernia and indicates MYRF as a candidate gene

Hongjian Qi, Lan Yu, Xueya Zhou, Alexander Kitaygorodsky, Julia Wynn, Na Zhu, Guðrún Aspelund, Foong‐Yen Y. Lim, Timothy M. Crombleholme, Robert A. Cusick, Kenneth S. Azarow, Melissa Ellen Danko, Dai H. Chung, Brad W. Warner, George B. Mychaliska, , Yufeng Shen

The paper analyzes de novo variants in congenital diaphragmatic hernia cases to identify sex differences and a new candidate gene MYRF.

bioRxiv · Nov 12, 2017 · PreprintGenetics