Our Team
Kaitlin Samocha, Ph.D.
Principal Investigator
Kaitlin Samocha is an Assistant Professor in the Center for Genomic Medicine at Massachusetts General Hospital. She is on the steering committee for the Genome Aggregation Database (gnomAD), one of the world’s largest publicly available collections of human genetic variation data, and is part of the Translational Genomics Group at the Broad Institute.
The focus of her research career has been on developing methods and statistical tools to improve interpretation of genetic variation, particularly rare variation. She created a mutational model to predict the expected number of newly arising (de novo) variants that has been leveraged to associate dozens of genes with autism spectrum disorders, congenital heart disease, and schizophrenia, among others. As a way to aid variant interpretation, Kaitlin developed metrics to measure a gene’s tolerance to mutational changes, including the pLI score that was used to identify thousands of genes intolerant to loss of a single functional copy. Additionally, she led an international consortium studying developmental disorders and identified ~300 significantly associated genes, including 28 that had not been robustly tied to these disorders.
Kaitlin received her A.B. in Biological Sciences with Honors and Phi Beta Kappa in 2010 from the University of Chicago, and her Ph.D. in Genetics and Genomics in 2016 from Harvard University. She trained as a postdoctoral fellow at the Wellcome Sanger Institute and was a College Research Associate at St. John’s College, Cambridge.
Twitter: @ksamocha
Email: samocha[at]broadinstitute.org / ksamocha[at]partners.org
Mackenzie Simper, Ph.D.
Postdoctoral Fellow
Mackenzie is a postdoctoral researcher through the Eric and Wendy Schmidt Center at the Broad Institute. She completed her Ph.D. in mathematics at Stanford University, advised by Persi Diaconis. Her thesis introduced a new framework for studying Markov chains on equivalence classes of finite groups. She also worked on random processes useful in phylogenetics and statistics. Broadly, Mackenzie is excited to find surprising structure in random objects, and looks forward to applying probabilistic ideas to the world of human genetics.
A Salt Lake City native, Mackenzie majored in mathematics at the University of Utah. She spent one year as a Churchill Scholar at Cambridge University to complete Part III of the Mathematical Tripos. At Stanford, she was supported by a National Defense Science & Engineering Graduate Fellowship. She organized the Stanford Women in Math Mentoring group and enjoyed teaching summer classes for high school students.
Kaileigh Ahlquist, Ph.D.
Computational Scienstist
Kaileigh is a Computational Scientist at the Broad Institute. They completed their Ph.D. in Molecular Biology at Brown University, advised by Sohini Ramachandran. Their Ph.D. thesis focused on statistical method development for population genetics research, and adapting machine learning techniques for biological contexts. Kaileigh has prior experience working in industry at Regeneron Pharmaceuticals and Indigo Agriculture, where they were responsible for implementing and testing new pipelines for biological data analysis. Kaileigh enjoys developing new statistical and computational methods that are grounded in the specific needs of biological datasets.
Kaileigh has pursued research in both humans and plants, completing a M.S. at Cornell University in Plant Breeding and Genetics, advised by Walter De Jong, where they focused on phylogenetic methods and the structure of large gene families. Their undergraduate thesis work at Reed College focused on host-virus interactions using genetic engineering techniques.
Ruchit Panchal, M.S.
Computational Associate
Ruchit is a Computational Associate II at the Broad Institute. He completed his Master's degree in physics at University of Massachusetts: Lowell. His thesis was in computational astronomy where he developed binary star model to predict absorption in X-Ray light curves. He joined the realm of genetics research at Beth Israel Deaconess Medical Center (BIDMC), followed by 3 years at the Broad Institute where he developed analysis approaches for Illumina amplicon sequencing data and building bioinformatic analysis pipeline that support diverse projects. He is fond of understanding natural processes in the language of mathematics and statistics and is excited to apply the same in the world of human genetics. His other interests include science fiction, hiking, and traveling.
Projects and Collaborations with Other Teams
We have active collaborations with members of other teams both locally and around the world. A few of note:
Role of background genetic variation in neuropsychiatric disease
Evaluating the role of background genetic variation in carriers of structural variants with and without neuropsychiatric disorders.
Regional missense constraint
Identifying regions within genes that are specifically intolerant to missense mutations + using that information to inform on missense variant deleteriousness (e.g. MPC scores).
Katherine Chao
Software Product Manager, gnomAD
Translational Genomics Group
Lily Wang
Ph.D. Student
Talkowski lab
Jing Zhang, Ph.D.
Postdoctoral Fellow
Robinson lab
How common variation influences penetrance of rare variants
Investigating how common variation, in particular cis-regulatory variation, can impact the penetrance of rare coding variants associated with developmental disorders. This work is being led by Dr. Hilary Martin and the DDD study.
Recessive contributions to developmental disorders
Improving methods and quality control approaches to identify genes contributing to developmental disorders in a recessive manner. This work is being led by Dr. Hilary Martin, the DDD study, and GeneDx.
Kartik Chundru, Ph.D.
Postdoctoral Fellow
Martin group
Emilie Wigdor, Ph.D.
Graduated Ph.D. Student
Martin group
We are looking for more team members, friends, and collaborators! Reach out if you have ideas of how we can work together.