Event
Ph.D. Dissertation Defense: Ananth Hari
Thursday, November 13, 2025
12:00 p.m.
AVW 1146
Sarah Pham
301 473 2449
spham124@umd.edu
ANNOUNCEMENT: Ph.D. Dissertation Defense
Name: Ananth Hari
Committee:
Professor Uzi Vishkin, Chair
Professor S. Cenk Sahinalp
Professor Richard La
Professor Behtash Babadi
Professor Philip Johnson
Professor Can Firtina
Professor Stephen Mount, Dean's Representative
Date/time: Thursday, November 13th from 12pm - 2pm
Location: AVW 1146 (A. V. Williams building)
Title: Algorithms for Germline Genotyping and Methylation Deconvolution
Abstract: One of the fundamental problems in nature is to assemble small blocks into known patterns, using a large reference set of known patterns. The complexity of the problem is at least an order of magnitude higher if the reference set is not fully known.
Genotyping germline genes involves assembling sequencing reads into known sequences of genes known as alleles and determining their number of copies in the genomes of individuals. The first part of the thesis presents methods to genotype complex and highly polymorphic germline loci. First, we present ImmunoTyper-SR, an algorithmic approach to genotype and analyze copy numbers of the germline immunoglobulin and T cell receptor genes using Illumina whole genome sequencing (WGS) data. ImmunoTyper-SR is based on a novel combinatorial optimization formulation that aims to minimize the total edit distance between reads and their assigned IGH alleles from a given database, with constraints on the number and distribution of reads across each called allele.
Professor Stephen Mount, Dean's Representative
Date/time: Thursday, November 13th from 12pm - 2pm
Location: AVW 1146 (A. V. Williams building)
Title: Algorithms for Germline Genotyping and Methylation Deconvolution
Abstract: One of the fundamental problems in nature is to assemble small blocks into known patterns, using a large reference set of known patterns. The complexity of the problem is at least an order of magnitude higher if the reference set is not fully known.
Genotyping germline genes involves assembling sequencing reads into known sequences of genes known as alleles and determining their number of copies in the genomes of individuals. The first part of the thesis presents methods to genotype complex and highly polymorphic germline loci. First, we present ImmunoTyper-SR, an algorithmic approach to genotype and analyze copy numbers of the germline immunoglobulin and T cell receptor genes using Illumina whole genome sequencing (WGS) data. ImmunoTyper-SR is based on a novel combinatorial optimization formulation that aims to minimize the total edit distance between reads and their assigned IGH alleles from a given database, with constraints on the number and distribution of reads across each called allele.
The second part of the talk focuses on genotyping highly polymorphic locus of pharmacogenes, the set of genes that determine metabolism rate of pharmaceutical drugs. We present Aldy 4, a fast and highly accurate combinatorial optimization method, to genotype a large set of pharmacogenes. Aldy 4 also detects structural variants such as copy number changes of genes and gene fusion events with the neighboring pseudogenes. It works by implementing a series of integer linear programs while hierarchically resolving the structure of the gene present first and then the genomic variants next. When presented with long read data, Aldy 4 also uses the phasing data to disambiguate between multiple equally likely solutions.
The final part of the talk focuses on inferring and interpreting data originating from evolutionary processes in somatic cells. DNA methylation is the biological process by which methyl groups are added to certain nucleotides in the DNA that dictate the activity of genes. We present Qombucha, a method for deconvolving bulk DNA methylation data from patient samples into constituent proportions of known cell types. Since the reference cell profiles are only partially known, we also simultaneously fill in the gaps in the methylation values of the representatives of the cell types.
The final part of the talk focuses on inferring and interpreting data originating from evolutionary processes in somatic cells. DNA methylation is the biological process by which methyl groups are added to certain nucleotides in the DNA that dictate the activity of genes. We present Qombucha, a method for deconvolving bulk DNA methylation data from patient samples into constituent proportions of known cell types. Since the reference cell profiles are only partially known, we also simultaneously fill in the gaps in the methylation values of the representatives of the cell types.
