Tanveer Ahmad

This paper presents near-complete, haplotype-resolved assemblies of a pancreatic cancer genome and normal tissue, identifying extensive somatic variants and epigenetic changes in previously excluded regions.

Wakhan reconstructs chromosome-scale copy number profiles of tumor genomes using long-read sequencing, showing better consistency with data than existing methods.

DeepSomatic is a deep learning method for detecting somatic variants from short-read and long-read sequencing data, outperforming existing callers, especially for indels.

The paper uses long-read sequencing to analyze genomic and epigenomic changes in melanoma subclones, revealing parallel evolutionary paths and lineage-specific methylation patterns.

GenMPI provides a scalable variant calling workflow for short and long-read sequencing data using MPI, achieving linear scaling and improved performance over existing methods.

The paper describes a comprehensive genomic dataset from a tumor-normal pair with broad consent, generated using multiple sequencing technologies for benchmarking somatic variant detection.

Severus detects and characterizes somatic structural variations in tumor genomes using long reads, outperforming existing methods in accuracy and revealing clinically relevant rearrangements.

This study shows that HiFi long-read sequencing can detect clinically relevant structural variants in pediatric leukemia, improving subtype classification.

The paper introduces a scalable genomics data processing solution using Apache Arrow and Arrow Flight on an HPC system, outperforming Spark and matching MPI-based solutions in speed and efficiency.

ArrowSAM improves genomics data processing speed by using Apache Arrow for in-memory SAM format, achieving 15x and 2.4x speedups over Picard and Sambamba.