A New Tool for Mutational Signature Analysis

Hu and Doga describe MuSiCal (Mutational Signature Calculator) for analysis of somatic mutations (Nat Genetics 2024)
Tissue-specific proliferative effects underlie tumor CNA patterns

Chromosome evolution screens using single cell genome sequencing (Emma/Jake, Nat Genetics, 2024)
Chromoscope for SV analysis

Interactive multiscale visualization for structural variation by Sehi and Dominik (Nat Methods, 2023)
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)
A new mechanism for breast cancers

Jake discovers Translocation-Bridge Amplification that generates focal amplifications (Nature, 2023)
Single-cell genome sequencing of human neurons

Joe finds enrichment of somatic SNVs and indels in regulatory elements (Nat Genetics, 2022)
Computational analysis of Cancer Genome Sequencing Data

Isidro et al discuss recent advances in cancer genome analysis (Nature Reviews Genetics, 2022)
Landmarks of embryonic development inscribed in somatic mutations

Mosaic variants in multiple organs resolve post-zygotic lineages (Science, 2021)
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)
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)
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)
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)
LiRA identifies mutations in scDNA-seq data

Craig develops a method for detection of somatic variants in single cells (Nat Genetics, 2019)
Review: Detecting somatic mutations in normal cells

Yanmei, Heather, Joe, and Peter discuss issues in detection of somatic variants (Trends in Genetics, 2018)
Aging & neurodegeneration assoc. with increased mutations in neurons

Analysis of the largest single cell WGS dataset to date (Science, 2018)
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
Analysis of microsatellite instability identifies patients that may benefit from immunotherapy

Cortes-Ciriano et al,Nat Comm, June, 2017
Impact of mutation in a chromatin remodeling protein complex

Three papers from a collaboration with the Roberts lab inNature GeneticsandNature Communications
Detecting structural variants from exome data

Yang et al (AJHG, 2016) analyze nearly 5000 cancer exomes and identify thousands of rearrangements.
Sequencing single neurons

Lineage tracing of neurons using mutational analysis of single cell whole-genome sequencing data (Science, 2015; cover)
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
Cell lineage analysis in human brain using endogenous retroelements

Gilad Evrony, Alice Lee, et al. inNeuron, 2015 (Collaboration with the Chris Walsh lab)
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.

A New Tool for Mutational Signature Analysis

Tissue-specific proliferative effects underlie tumor CNA patterns

Chromoscope for SV analysis

Widespread emergence of mosaic CNVs in normal human tissues

A new mechanism for breast cancers

Single-cell genome sequencing of human neurons

Computational analysis of Cancer Genome Sequencing Data

Landmarks of embryonic development inscribed in somatic mutations

Origins/genetic interactions of KRAS mutations are allele- and tissue-specific

Comprehensive analysis of chromothripsis using whole-genome data

Detecting mosaic mutations using a ML algorithm (MosaicForecast)

Detecting the mutational signature of homologous recombination deficiency

LiRA identifies mutations in scDNA-seq data

Review: Detecting somatic mutations in normal cells

Aging & neurodegeneration assoc. with increased mutations in neurons

PaSD-qc: quality control for single cell whole-genome sequencing data

Analysis of microsatellite instability identifies patients that may benefit from immunotherapy

Impact of mutation in a chromatin remodeling protein complex

Detecting structural variants from exome data

Sequencing single neurons

4D Nucleome project to understand higher-order nuclear organization

Cell lineage analysis in human brain using endogenous retroelements

Comparative analysis of metazoan chromatin organization

Introduction

Collaborative science

Here are some consortium projects in which we are involved: