scispace - formally typeset
V

Vagheesh M. Narasimhan

Researcher at Harvard University

Publications -  25
Citations -  3790

Vagheesh M. Narasimhan is an academic researcher from Harvard University. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 15, co-authored 19 publications receiving 2796 citations. Previous affiliations of Vagheesh M. Narasimhan include Wellcome Trust Sanger Institute & University of Texas at Austin.

Papers
More filters
Journal ArticleDOI

Metagenomic microbial community profiling using unique clade-specific marker genes.

TL;DR: This work presents an approach that uses clade-specific marker genes to unambiguously assign reads to microbial clades more accurately and >50× faster than current approaches, and validated the metagenomic phylogenetic analysis tool, MetaPhlAn, on terabases of short reads.
Journal ArticleDOI

BCFtools/RoH: a hidden Markov model approach for detecting autozygosity from next-generation sequencing data

TL;DR: BCFtools/RoH is presented and evaluated, an extension to the BCFtools software package, that detects regions of autozygosity in sequencing data, in particular exome data, using a hidden Markov model and it is shown that it has higher sensitivity and specificity than existing methods under a range of sequencing error rates and levels of autozykgosity.
Journal ArticleDOI

The Formation of Human Populations in South and Central Asia

Vagheesh M. Narasimhan, +145 more
- 06 Sep 2019 - 
TL;DR: It is shown that Steppe ancestry then integrated further south in the first half of the second millennium BCE, contributing up to 30% of the ancestry of modern groups in South Asia, supporting the idea that the archaeologically documented dispersal of domesticates was accompanied by the spread of people from multiple centers of domestication.
Journal ArticleDOI

Extensive Proliferation of a Subset of Differentiated, yet Plastic, Medial Vascular Smooth Muscle Cells Contributes to Neointimal Formation in Mouse Injury and Atherosclerosis Models.

TL;DR: This research presents a novel probabilistic approach that allows us to assess the importance of knowing the carrier and removal status of canine coronavirus, as a source of infection for other animals.