Professor & Program Head, Biostatistics @FredHutch | Affiliate Professor @UWBiostat | Formerly @UCLA | Junction of Statistics & Biology; Rigor & Reproducibility
Joined March 2018
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I am so greatly honored and happy to be selected together with my colleague Yingqi Zhao as ASA Fellows this year.
Congratulations to Yingqi Zhao and @jsb_ucla from our Biostatistics Program at @FredhutchOrg on being named 2026 American Statistical Association Fellows! The ASA Fellow designation is one of the field's highest honors.
🔗 amstat.org/news-listing/2026…
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I am deeply honored by this recognition from the ISCB, which would not have been possible without the immense trust and hard work of my trainees. I am also thankful for the strong support of my colleagues and administrative team.
Congratulations to @jsb_ucla on her election to the 2026 Class of @iscb Fellows! 🎉 Her groundbreaking work in single-cell omics, FDR methods, and genomics has set a new bar for rigor and reproducibility in the field. A well-deserved honor! #Bioinformatics #genomics
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I hope that Nullstrap-DE can be a useful add-on to calibrate the FDR control of popular parametric DE methods, including DESeq2 and edgeR, while maintaining the strong power. Looking forward to feedback and comments from the community.
We will post the scDesignPop preprint soon.
🔥Congratulations to @jsb_ucla lab on two papers accepted to the highly selective #RECOMB2026 🎉
📌 Nullstrap-DE: arxiv.org/abs/2507.20598
📌 scDesignPop generates population-scale single-cell RNA-seq data for power analysis, method benchmarking, and privacy protection
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The Fred Hutch Biostatistics X account is now online: @biostats_fhcc.
Follow us for cutting-edge biostatistics, AI and data science in cancer research, trainee stories, faculty highlights, and more from @fredhutch. Please follow us and help spread the word!
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Fred Hutch Biostatistics is hiring (Asst/Assoc/Full Prof)!
We seek scholars who lead with statistical thinking and connect computation, medicine & science across imaging, AI, genomics, clinical trials & cancer prevention.
Apply by Dec 1, 2025: apply.interfolio.com/176402
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Great science happens at the intersections. STATGEN is a fantastic forum to connect, challenge assumptions, and raise the bar for rigor in genetics and genomics.
Submit an abstract by December 15, 2025: forms.gle/4VgspgwTZpdELD3h7
Conference Website: statgen26.emory.edu
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1/3 Metacells boost power in single-cell RNA-seq & multiome analysis. But without checking homogeneity, they risk forming dubious metacells that bias discoveries.
We introduce mcRigor: a statistical safeguard for rigorous metacell analysis.
👉 nature.com/articles/s41467-0…
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2/3 At the core of mcRigor is a feature-correlation statistic with a null derived from a double permutation scheme — a brilliant idea by my postdoc Pan Liu jsb-lab.org/people/pan-liu/
mcRigor detects dubious metacells and optimizes method & hyperparameter for a specific dataset.
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3/3 With mcRigor, downstream analyses become more reliable:
✅ gene co-expression modules
✅ enhancer–gene associations
✅ temporal expression patterns
Benchmarking shows MetaCell & SEACells are better-performing methods.
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18 Jul 2025
Excited to share our new method ClipperQTL published in @GenomeBiology
Built on our p-value-free FDR control framework Clipper, ClipperQTL performs on par with FastQTL and runs up to 500× faster.
Big thanks to my former PhD student Heather Zhou!
genomebiology.biomedcentral.…
#eQTL
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30 Jun 2025
I’m honored to join Fred Hutch as Professor and Program Head of Biostatistics, and as the Donald and Janet K. Guthrie Endowed Chair in Statistics. Excited to be part of a deeply collaborative and scientifically vibrant community with a rich legacy of impact.
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I’m deeply thankful for the incredible support and opportunities at UCLA over the past 12 years—ever since finishing my PhD. Grateful for the journey so far and looking forward to this new chapter at the intersection of statistics and biomedical science.
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I’ll speak on July 16 (2:30pm ET) at NSF@75: Advancing Statistical Science for a Data‑Driven World @InStatsOrg conference.
My talk is about an info-theoretic criterion (ITCA) for combining ambiguous class labels: jmlr.org/papers/v23/21-1043.…
Free registration: instats.org/seminar/nsfa75-a…
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The course covers a wide range of topics, including NGS data analysis, single-cell transcriptomics, gene regulatory networks, AI, and protein structure prediction. It combines lectures with hands-on projects for practical experience.
31 May 2025
Excited to announce a 2 week Cold Spring Harbor Asia (CSHA) summer course on Computational Genomics Aug 9-23, co organized by Jingyi Jessica Li @jsb_ucla, Qiangfeng Cliff Zhang, and myself. Application deadline June 8. @cshlcourses @CSHANews
csh-asia.org/?content/2818.
CSHA is located in the beautiful garden city Suzhou, 30min from Shanghai by high speed train.
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I’m deeply honored to be named a 2025 Guggenheim Fellow—especially as part of the Foundation’s historic 100th class. Grateful to be in the company of so many brilliant artists, scholars, and scientists. #guggfellows2025
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Honored to be part of the Farm Animal Genotype–Tissue Expression (FarmGTEx) Project. This study maps RNA-based molecular QTL across 16 farm animal species, unlocking key insights into genetics & physiology. nature.com/articles/s41588-0… #FarmGTEx
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Thanks @davidliwei for inviting us to this great collaboration! Thanks my PhD student @Qingyang__Wang for extending our simulator scDesign3 to perform the simulation study in this work.
27 Feb 2025
Our most recent Nature Cell Biology paper describes an innovative Perturbation-response Score (PS) method to decode heterogeneous responses of cells to perturbations at single-cell level. Particularly helpful for analyzing Perturb-seq data. nature.com/articles/s41556-0…
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In this review article led by Kris Sankaran, we discuss the versatile use of semi-synthetic simulation for microbiome data analysis, including power analysis, methods benchmarking, and reliability analysis.
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academic.oup.com/bib/article…
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We also discuss the trade-offs of simulators: generality, faithfulness, and controllability. Recognizing that all simulators only approximate reality, we review methods to evaluate how accurately they reflect key properties.
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We also present case studies demonstrating the value of simulation in differential abundance testing, dimensionality reduction, network analysis, and data integration.
Code is available in an online tutorial (go.wisc.edu/8994yz) that can be easily adapted.
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