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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">
<html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en-GB">
<head>
<meta name="google-site-verification" content="jHIqz8fA7bF3VMpsGpt6OjjwA7V9RiLALS-NPD6UitQ" />
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<title>Xinjun Wang</title>
<meta name="keywords" content="xinjun, wang, xinjun wang, wang xinjun, university of pittsburgh, pittsburgh, pitt, phd, statistics, biostatistics, iowa, washington">
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<body>
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<div class="colmask leftmenu">
<div class="colleft">
<div class="col1">
<div class="box1">
<p> <br>
</p>
<br>
<p><h2>About me</h2>
I am an Assistant Attending Biostatistician at Memorial Sloan Kettering Cancer Center. <br> <br>My research areas include 1) single-cell multi-omics data and 2) subgroup analysis with differential treatment effects. <p>
</div>
<div class="box1">
<h2>Awards</h2>
<ul>
<li> ASA Student of the Year, Pittsburgh Chapter, 2021
</li><br>
<li> Outstanding Graduate Student Researcher Award, Pitt Biostatistics, 2021
</li><br>
<li> Biostatistics Doctoral Award, Pitt GSPH Dean's Day, 2021
</li><br>
<li> Outstanding Student Research Award, Pitt Biostatistics Research Day, 2021
</li><br>
<li> ICSA Student Paper Award, 2020
</li>
</ul>
</div>
<div class="box1">
<h2>Research Funding</h2>
<ul>
<li>
Funding Agency: UPMC Children's Hospital of Pittsburgh<br>
Grant Title: Machine Learning and Statistical Methods for Analyzing Single-cell Multi-omics Data<br>
Role on Grant: <b>Principal Investigator</b><br>
Years Inclusive: 7/1/2020 - 6/30/2022<br>
Total Direct Costs: $80,000 ($40,000 per year)</li>
<br>
<li>
Funding Agency: NIH / Clinical and Translational Science Institute, University of Pittsburgh<br>
Grant Number: UL1TR001857<br>
Grant Title: Joint Analysis of Single-cell Multi-omics Data<br>
Role on Grant: <b>co-Principal Investigator</b><br>
Years Inclusive: 9/1/2019 - 8/31/2020<br>
Total Direct Costs: $10,000</li>
</ul>
</div>
<div class="box1">
<h2>Selected Publications</h2>
<ul>
<h3>Methodology</h3>
<ul>
<li><strong>Wang, X</strong>, 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. <em>PNAS Nexus</em>. 2022 Sep; 1(4):pgab165 . </li>
<br>
<li>Wei Y, <strong>Wang, X</strong>, Chew EY, Ding Y. Confident identification of subgroups from SNP testing in RCTs with binary outcomes. <em>Biometrical Journal</em>. 2022 Feb;64(2)256-71. </li>
<br>
<li>Xin H, Lian Q, Jiang Y, Luo J, <strong>Wang, X</strong>, 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. <em>Genome biology</em>. 2020 Dec;21(1):1-35.</li>
<br>
<li><strong>Wang, X</strong>, 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. <em>Nucleic acids research</em>. 2020 Jun 19;48(11):5814-24.</li>
<br>
<li>Zhao C, Xu Z, <strong>Wang, X</strong>, Chen K, Huang H, Chen W.
Transformer Enables Reference Free and Unsupervised Analysis of Spatial Transcriptomics . <em>bioRxiv</em>. Submitted.
</li></ul>
<h3>Collaboration</h3>
<ul>
<li>Xu Z, <strong>Wang X</strong>, 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. <em>iScience</em>. 2022 Sep 16;25(9):104900.</li>
<br>
<li>Chen T, Conroy J, <strong>Wang, X</strong>, 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. <em>EBioMedicine</em>. 2022 Feb 1;76:103860.</li>
<br>
<li>Mirizio E, Liu C, Yan Q, Waltermire J, Mandel R, Schollaert KL, Konnikova L, <strong>Wang, X</strong>, Chen W, Torok KS. Genetic Signatures From RNA Sequencing of Pediatric Localized Scleroderma Skin. <em>Frontiers in Pediatrics</em>. 2021;9.</li>
<br>
<li>Schutt C, Mirizio E, Salgado C, Reyes-Mugica M, <strong>Wang X</strong>, Chen W, Grunwaldt L, Schollaert KL, Torok KS. Transcriptomic evaluation of pediatric localized scleroderma skin with histological and clinical correlation. <em>Arthritis & Rheumatology</em>. 2021 Apr 12. </li>
<br>
<li>Mirizio E, Tabib T, <strong>Wang, X</strong>, 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. <em>Arthritis research & therapy</em>. 2020 Dec;22(1):1-0. </li></ul>
<h3>Book Chapters</h3>
<ul>
<li><strong>Wang X</strong>, 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). <em>Chapman & Hall/CRC</em>.
</li>
<br>
<li>Ding Y, Wei Y, <strong>Wang X</strong>, Hsu JC. Testing SNPs in Targeted Drug Development. Book Chapter In: Handbook of Multiple Comparisons 2021 (pp. 363-386). <em>Chapman & Hall/CRC</em>.
</li>
<br>
<li>Ding Y, Wei Y, <strong>Wang X</strong>. Logical Inference on Treatment Efficacy When Subgroups Exist. Book Chapter In: Design and Analysis of Subgroups with Biopharmaceutical Applications 2020 (pp. 209-228). <em>Springer, Cham</em>.
</li></ul>
</div>
<div class="box1">
<h2>Selected Presentations</h2>
<ul>
<li>(Virtual Talk) ENAR, March 2021. </li><br>
<li>(Invited Virtual Talk) The Pulmonary Medicine Research Conference, University of Pittsburgh, December 2020. </li><br>
<li>(Virtual Talk) ICSA, December 2020.</li><br>
<li>(Virtual Talk) ENAR, March 2020.</li><br>
<li>(Invited Talk) Center for Systems Immunology Research Forum, University of Pittsburgh, Pittsburgh, PA, September 2019.</li><br>
<li>(Poster) ENAR, Philadelphia, PA, March 2019.</li><br> </li>
<li>(Talk) ORISE Statistical Conference, FDA, White Oak, MD, August 2018.</li>
</ul>
</div>
<div class="box1">
<h2>Statistical Packages </h2>
<ul>
<li><strong>SECANT</strong>: A Python package (with GPU acceleration) for a novel biology-guided semi-supervised method for clustering, classification, and annotation of single-cell multi-omics. <a href="https://github.com/tarot0410/SECANT" target="_blank" >link</a> </li>
<br>
<li><strong>BREMSC</strong>: An R package for joint clustering droplet-based CITE-seq data. <a href="https://github.com/tarot0410/BREMSC" target="_blank" >link</a> </li>
</ul>
<br>
</div>
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<div class="col2">
<h2><big>Xinjun Wang</big><br>
</h2>
<img alt="Xinjun" src="./Headshot_XW.JPG" width="250" height="333"><br>
<p><strong> </strong> </p>
<p><strong>xinjun.wang119@gmail.com</strong> </p>
<p>PhD in Biostatistics<br>
University of Pittsburgh <br>
Fall 2017 - Summer 2022<br>
<div class="cv-link">
<a href="./cv_updated.pdf" target="_blank" class="email-link">Download CV</a>
</div>
</p>
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<p><small>Last updated Aug 2021. </small> </p>
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