Publications

2023

1. RECOMB

   Mapping the topography of spatial gene expression with interpretable deep learning

   Uthsav Chitra , Brian J Arnold , Hirak Sarkar, and 4 more authors

   bioRxiv, 2023
2. Nat Biotech

   Haplotype-aware analysis of somatic copy number variations from single-cell transcriptomes

   Teng Gao , Ruslan Soldatov , Hirak Sarkar, and 4 more authors

   Nature Biotechnology, 2023
3. Nat Comm

   Dissecting the immune suppressive human prostate tumor microenvironment via integrated single-cell and spatial transcriptomic analyses

   Taghreed Hirz , Shenglin Mei , Hirak Sarkar, and 8 more authors

   Nature Communications, 2023
4. Nat Rev

   Best practices for single-cell analysis across modalities

   Lukas Heumos , Anna C Schaar , Christopher Lance , and 8 more authors

   Nature Reviews Genetics, 2023
5. DifferentialRegulation: a Bayesian hierarchical approach to identify differentially regulated genes

   Simone Tiberi , Joël Meili , Peiying Cai , and 6 more authors

   bioRxiv, 2023

2022

1. Nat Methods

   Alevin-fry unlocks rapid, accurate and memory-frugal quantification of single-cell RNA-seq data

   Dongze He , Mohsen Zakeri , Hirak Sarkar, and 3 more authors

   Nature Methods, 2022
2. Bioinformatics

   Airpart: interpretable statistical models for analyzing allelic imbalance in single-cell datasets

   Wancen Mu , Hirak Sarkar, Avi Srivastava , and 3 more authors

   Bioinformatics, 2022

2021

1. Bioinformatics

   Compression of quantification uncertainty for scRNA-seq counts

   Scott Van Buren , Hirak Sarkar, Avi Srivastava , and 3 more authors

   Bioinformatics, 2021
2. bioRxiv

   A like-for-like comparison of lightweight-mapping pipelines for single-cell RNA-seq data pre-processing

   Mohsen Zakeri , Avi Srivastava , Hirak Sarkar, and 1 more author

   bioRxiv, 2021

2020

1. ISMB Bioinformatics

   Terminus enables the discovery of data-driven, robust transcript groups from RNA-seq data

   Hirak Sarkar, Avi Srivastava , Héctor Corrada Bravo , and 2 more authors

   Bioinformatics, 2020

   Bib

   @article{sarkar2020terminus,
     abbr2 = {Bioinformatics},
     title = {Terminus enables the discovery of data-driven, robust transcript groups from RNA-seq data},
     author = {Sarkar, Hirak and Srivastava, Avi and Bravo, H{\'e}ctor Corrada and Love, Michael I and Patro, Rob},
     journal = {Bioinformatics},
     volume = {36},
     number = {Supplement\_1},
     pages = {i102--i110},
     year = {2020},
     publisher = {Oxford University Press},
   }

2. Genome Biology

   Alignment and mapping methodology influence transcript abundance estimation

   Avi Srivastava , Laraib Malik , Hirak Sarkar, and 6 more authors

   Genome biology, 2020
3. EMNLP

   Social media attributions in the context of water crisis

   Rupak Sarkar , Hirak Sarkar, Sayantan Mahinder , and 1 more author

   arXiv preprint arXiv:2001.01697, 2020
4. ISMB Bioinformatics

   A Bayesian framework for inter-cellular information sharing improves dscRNA-seq quantification

   Avi Srivastava , Laraib Malik , Hirak Sarkar, and 1 more author

   Bioinformatics, 2020

2019

1. ISMB Bioinformatics

   Minnow: a principled framework for rapid simulation of dscRNA-seq data at the read level

   Hirak Sarkar, Avi Srivastava , and Rob Patro

   Bioinformatics, 2019

2018

1. Towards selective-alignment: Bridging the accuracy gap between alignment-based and alignment-free transcript quantification

   Hirak Sarkar, Mohsen Zakeri , Laraib Malik , and 1 more author

   In Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics , 2018
2. ISMB Bioinformatics

   A space and time-efficient index for the compacted colored de Bruijn graph

   Fatemeh Almodaresi* , Hirak Sarkar*, Avi Srivastava , and 1 more author

   Bioinformatics, 2018

2017

1. Bioinformatics

   Quark enables semi-reference-based compression of RNA-seq data

   Hirak Sarkar, and Rob Patro

   Bioinformatics, 2017
2. ISMB Bioinformatics

   Towards selective-alignment: producing accurate and sensitive alignments using quasi-mapping

   Hirak Sarkar, Mohsen Zakeri , Laraib Malik , and 1 more author

   bioRxiv, 2017

2016

1. ISMB Bioinformatics

   RapMap: a rapid, sensitive and accurate tool for mapping RNA-seq reads to transcriptomes

   Avi Srivastava , Hirak Sarkar, Nitish Gupta , and 1 more author

   Bioinformatics, 2016
2. RECOMB-seq

   Accurate, fast and lightweight clustering of de novo transcriptomes using fragment equivalence classes

   Avi Srivastava , Hirak Sarkar, Laraib Malik , and 1 more author

   arXiv preprint arXiv:1604.03250, 2016

2015

1. TCS

   Voronoi game on graphs

   Sayan Bandyapadhyay , Aritra Banik , Sandip Das , and 1 more author

   Theoretical Computer Science, 2015

2013

1. Some geometric and combinatorial properties of binary matrices related to discrete tomography

   Hirak Sarkar

   Indian Statistical Institute-Kolkata , 2013