About me

I am an Assistant Attending Biostatistician at Memorial Sloan Kettering Cancer Center.

My research areas include 1) single-cell multi-omics data and 2) subgroup analysis with differential treatment effects.

Awards

• ASA Student of the Year, Pittsburgh Chapter, 2021


• Outstanding Graduate Student Researcher Award, Pitt Biostatistics, 2021


• Biostatistics Doctoral Award, Pitt GSPH Dean's Day, 2021


• Outstanding Student Research Award, Pitt Biostatistics Research Day, 2021


• ICSA Student Paper Award, 2020

Research Funding

• Funding Agency: UPMC Children's Hospital of Pittsburgh
  Grant Title: Machine Learning and Statistical Methods for Analyzing Single-cell Multi-omics Data
  Role on Grant: Principal Investigator
  Years Inclusive: 7/1/2020 - 6/30/2022
  Total Direct Costs: $80,000 ($40,000 per year)


• Funding Agency: NIH / Clinical and Translational Science Institute, University of Pittsburgh
  Grant Number: UL1TR001857
  Grant Title: Joint Analysis of Single-cell Multi-omics Data
  Role on Grant: co-Principal Investigator
  Years Inclusive: 9/1/2019 - 8/31/2020
  Total Direct Costs: $10,000

Selected Publications

Methodology

• Wang, X, Xu Z, Zhou X, Zhang Y, Lafyatis R, Chen K, Huang H, Ding Y, Duerr R, Chen W. SECANT: a biology-guided semi-supervised method for clustering, classification, and annotation of single-cell multi-omics. PNAS Nexus. 2022 Sep; 1(4):pgab165 .


• Wei Y, Wang, X, Chew EY, Ding Y. Confident identification of subgroups from SNP testing in RCTs with binary outcomes. Biometrical Journal. 2022 Feb;64(2)256-71.


• Xin H, Lian Q, Jiang Y, Luo J, Wang, X, Erb C, Xu Z, Zhang X, Heidrich-O'Hare E, Yan Q, Duerr RH. GMM-Demux: sample demultiplexing, multiplet detection, experiment planning, and novel cell-type verification in single cell sequencing. Genome biology. 2020 Dec;21(1):1-35.


• Wang, X, Sun Z, Zhang Y, Xu Z, Xin H, Huang H, Duerr RH, Chen K, Ding Y, Chen W. BREM-SC: a bayesian random effects mixture model for joint clustering single cell multi-omics data. Nucleic acids research. 2020 Jun 19;48(11):5814-24.


• Zhao C, Xu Z, Wang, X, Chen K, Huang H, Chen W. Transformer Enables Reference Free and Unsupervised Analysis of Spatial Transcriptomics . bioRxiv. Submitted.

Collaboration

• Xu Z, Wang X, Fan L, Wang F, Wang J, Chen W, Chen K. Integrative Analysis of Spatial Transcriptome with Single-cell Transcriptome and Single-cell Epigenome in Mice Lungs after Immunization. iScience. 2022 Sep 16;25(9):104900.


• Chen T, Conroy J, Wang, X, Situ M, Namas R, Vodovotz Y, Chen W, Singh H, Billiar T. The independent prognostic value of global epigenetic alterations: An analysis of single-cell ATAC-seq of circulating leukocytes from trauma patients followed by validation in whole blood leukocyte transcriptomes across three etiologies of critical illness. EBioMedicine. 2022 Feb 1;76:103860.


• Mirizio E, Liu C, Yan Q, Waltermire J, Mandel R, Schollaert KL, Konnikova L, Wang, X, Chen W, Torok KS. Genetic Signatures From RNA Sequencing of Pediatric Localized Scleroderma Skin. Frontiers in Pediatrics. 2021;9.


• Schutt C, Mirizio E, Salgado C, Reyes-Mugica M, Wang X, Chen W, Grunwaldt L, Schollaert KL, Torok KS. Transcriptomic evaluation of pediatric localized scleroderma skin with histological and clinical correlation. Arthritis & Rheumatology. 2021 Apr 12.


• Mirizio E, Tabib T, Wang, X, Chen W, Liu C, Lafyatis R, Jacobe H, Torok KS. Single-cell transcriptome conservation in a comparative analysis of fresh and cryopreserved human skin tissue: pilot in localized scleroderma. Arthritis research & therapy. 2020 Dec;22(1):1-0.

Book Chapters

• Wang X, Hu H, Wei Y, Chen W. Model-based Clustering of Single-cell Data. Book Chapter In: Handbook of Statistical Bioinformatics (2nd Edition) 2022 (pp. 85-108). Chapman & Hall/CRC.


• Ding Y, Wei Y, Wang X, Hsu JC. Testing SNPs in Targeted Drug Development. Book Chapter In: Handbook of Multiple Comparisons 2021 (pp. 363-386). Chapman & Hall/CRC.


• Ding Y, Wei Y, Wang X. Logical Inference on Treatment Efficacy When Subgroups Exist. Book Chapter In: Design and Analysis of Subgroups with Biopharmaceutical Applications 2020 (pp. 209-228). Springer, Cham.

Selected Presentations

• (Virtual Talk) ENAR, March 2021.


• (Invited Virtual Talk) The Pulmonary Medicine Research Conference, University of Pittsburgh, December 2020.


• (Virtual Talk) ICSA, December 2020.


• (Virtual Talk) ENAR, March 2020.


• (Invited Talk) Center for Systems Immunology Research Forum, University of Pittsburgh, Pittsburgh, PA, September 2019.


• (Poster) ENAR, Philadelphia, PA, March 2019.


• (Talk) ORISE Statistical Conference, FDA, White Oak, MD, August 2018.

Statistical Packages

• SECANT: A Python package (with GPU acceleration) for a novel biology-guided semi-supervised method for clustering, classification, and annotation of single-cell multi-omics. link


• BREMSC: An R package for joint clustering droplet-based CITE-seq data. link