Neurons from ALS, FTD, and Alzheimer’s disease show increased sSNVs and sIndels
Joe identifies a shared mutational signature of 2-bp deletions in these samples (Zhou*, Luquette*, et al Cell, 2026; collaboration with the Chris Walsh lab)
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A recurrent sequencing artifact on Illumina sequencers
Beverly, Vinay, and Dominik identify artifactual T>G substitutions on Illumina two-color chemistry platforms
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Region-specific differences in clonal architecture in human cortex
Vinay uses somatic mutations to track human cortical lineages (Cell Reports, 2025)
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A New Tool for Mutational Signature Analysis
Hu and Doga describe MuSiCal (Mutational Signature Calculator) for analysis of somatic mutations (Nat Genetics 2024)
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Tissue-specific proliferative effects underlie tumor CNA patterns
Chromosome evolution screens using single cell genome sequencing (Emma/Jake, Nat Genetics, 2024)
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Chromoscope for SV analysis
Interactive multiscale visualization for structural variation by Sehi and Dominik (Nat Methods, 2023)
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Widespread emergence of mosaic CNVs in normal human tissues
A pan-tissue survey of mosaic chromosomal alterations in 948 individuals (Teng/Kharchenko Lab, Nat Genetics, 2023)
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A new mechanism for breast cancers
Jake discovers Translocation-Bridge Amplification that generates focal amplifications (Nature, 2023)
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Single-cell genome sequencing of human neurons
Joe finds enrichment of somatic SNVs and indels in regulatory elements (Nat Genetics, 2022)
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Computational analysis of Cancer Genome Sequencing Data
Isidro et al discuss recent advances in cancer genome analysis (Nature Reviews Genetics, 2022)
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Landmarks of embryonic development inscribed in somatic mutations
Mosaic variants in multiple organs resolve post-zygotic lineages (Science, 2021)
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Origins/genetic interactions of KRAS mutations are allele- and tissue-specific
Analysis of KRAS mutations at the allele level using >13K samples (Nat Comm, 2021)
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Comprehensive analysis of chromothripsis using whole-genome data
Analysis of >2500 cancer genomes shows that chromothripsis events are prevalent across multiple tumor types (Nat Genetics, 2020)
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Detecting mosaic mutations using a ML algorithm (MosaicForecast)
Yanmei et al develop MosaicForecast, a machine learning-based variant caller for mosaic mutations (Nat Biotech, 2020)
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Detecting the mutational signature of homologous recombination deficiency
Doga et al develop SigMA to identify patients who may benefit from PARP inhibitor treatment (Nat Genetics, 2019)
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LiRA identifies mutations in scDNA-seq data
Craig develops a method for detection of somatic variants in single cells (Nat Genetics, 2019)
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Review: Detecting somatic mutations in normal cells
Yanmei, Heather, Joe, and Peter discuss issues in detection of somatic variants (Trends in Genetics, 2018)
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Aging & neurodegeneration assoc. with increased mutations in neurons
Analysis of the largest single cell WGS dataset to date (Science, 2018)
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PaSD-qc: quality control for single cell whole-genome sequencing data
Sherman et al. (Nucleic Acids Research, 2017) develop a QC method based on power density estimation
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Analysis of microsatellite instability identifies patients that may benefit from immunotherapy
Cortes-Ciriano et al,Nat Comm, June, 2017
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Impact of mutation in a chromatin remodeling protein complex
Three papers from a collaboration with the Roberts lab inNature GeneticsandNature Communications
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Detecting structural variants from exome data
Yang et al (AJHG, 2016) analyze nearly 5000 cancer exomes and identify thousands of rearrangements.
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Sequencing single neurons
Lineage tracing of neurons using mutational analysis of single cell whole-genome sequencing data (Science, 2015; cover)
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4D Nucleome project to understand higher-order nuclear organization
The Park lab, along with the Kharchenko and Gehlenborg labs at DBMI, are leading the Data Coordination and Integration Center
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Cell lineage analysis in human brain using endogenous retroelements
Gilad Evrony, Alice Lee, et al. inNeuron, 2015 (Collaboration with the Chris Walsh lab)
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Comparative analysis of metazoan chromatin organization
A cross-species analysis from the ENCODE and modENCODE consortia, led by Park lab members,Nature, 2014
Introduction
We are a bioinformatics research group in the Department of Biomedical Informatics at Harvard Medical School. We are part of the Ludwig Center at Harvard, Division of Genetics at Brigham and Women’s Hospital and Harvard-MIT Division of Health, Science, & Technology.
Our main aim is to understand the genetic and epigenetic mechanisms that underlie disease processes through computational and statistical analysis of genomic data. We are particularly interested in mutational processes in normal and cancer cells and their impact in gene regulation.
Collaborative science
We have the privilege of collaborating with a number of superb experimental laboratories at Harvard Medical School and its affiliated hospitals, as well as around the world. Our recent and current collaborators include Connie Cepko, George Daley, Steve Elledge, Konrad Hochedlinger, Mark Johnson, Mitzi Kuroda, Jordan Kreidberg, Bob Kingston, William Pu, Charlie Roberts, Chris Walsh, and Fred Winston.
Here are some consortium projects in which we are involved:
- SMaHT (Somatic Mosaicism across Human Tissues), starting in 2023 - Do mutations accumulate in non-cancer cells? Where and how? Can those mutations lead to cancer or other diseases?
- 4D Nucleome - What are the principles underlying three-dimensional organization of the human genome? What is the role of the nuclear architecture in gene regulation? As the Data Coordination and Analysis Center for this major NIH initiative, we will collect, process, and display all data generated in the consortium and to perform integrative analysis. Main collaborators: Peter Kharchenko (HMS), Leonid Mirny (MIT), Nils Gehlenborg (HMS), Hanspeter Pfister (Harvard) and Ting Wang (WashU).
- Brain Somatic Mosaicism Network - The aim of this network is to characterize the spectrum of somatic variation in human brain samples and its role in psychiatric disorders. We are studying somatic mosaicism in autism with Chris Walsh (Boston Children’s) and schizophrenia with Andy Chess (Mt. Sinai).
- Ludwig Center - This center brings together investigators from across Harvard to develop strategies to overcome the problem of therapy resistence in cancer.
- International Cancer Genome Consortium - This is an effort by the international cancer genomics community to jointly analyze ~2,500 cancer genomes.
Latest News
Oct 2026: Park Lab Hiking Trip 2026
Park lab went on its annual hiking trip over the long weekend and witnessed some beautiful fall views.
Oct 2026: Welcome Liz and Zofia!
Welcome Liz and Zofia! Park lab recently welcomed two new Associate Compuational Biologists, Liz Imhoff and Zofia Dudek. Liz completed a master’s degree in Computational Biology and Quantitative Genetics from Harvard T.H. Chan in 2025 after which she worked in the Leshchiner Lab at Boston University, analyzing cancer genomics data from individuals with CLL. Zofia completed an MS in Bioengineering and Biomedical Data Science at Stanford.
Sep 2026: Julia's Farewell
After nearly four years in the Park Lab, Julia returns to Germany to start a new adventure. Park lab will miss her hardwork, excitement, and ability to bring the whole team together. Farewell Julia!
Aug 2026: Cassie's Farewell
As the website updater today I am posting about my own farewell! Park lab gathered together to send me off after four years with the team. It is a very bittersweet feeling and I already miss the team so much. Wishing all of Park lab the best of luck!
Aug 2026: Welcome Daniel!
Park lab is excited to welcome BIG PhD student Daniel Feng to the team! Daniel graduated from the University of Illinois, Urbana-Champaign in 2025 with a Bachelor’s degree in Computer Science. As an undergraduate, he researched computational cancer phylogenetics, network clustering, and the probabilistic modelling of errors in microsatellite duplex sequencing. In the Park Lab, Daniel is developing algorithmic methods for analyzing and compressing different types of next generation sequencing data! Welcome Daniel!