Author

Shuvom Sadhuka

Broad InstituteORCID 0009-0001-9225-8716Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Research Focus:fine-mapping· 1 Assay:GWAS summary statistics· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Akihide Masumoto· 1 shared Akiko NagaiiD· 1 shared Bonnie BergeriD· 1 shared Carlos Albors· 1 shared Daisuke Obata· 1 shared Daniel Fridman· 1 shared Daniel G. MacArthuriD· 1 shared David R. KelleyiD· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperGenomics

Akihide Masumoto

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2 papers

Recent·Most cited

GenomicsGenome ResearchPeer-reviewedAug 4, 2023

Assessing transcriptomic re-identification risks using discriminative sequence models

Shuvom Sadhuka, Daniel Fridman, Bonnie Berger, Hyunghoon Cho

This paper introduces a discriminative sequence model to assess transcriptomic re-identification risks by improving linking attack accuracy across datasets.

10 citations

humanbulk RNA-seq

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GenomicsNature CommunicationsPeer-reviewedJun 7, 2021

Leveraging supervised learning for functionally-informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs

Qingbo S. Wang, David R. Kelley, Jacob C. Ulirsch…·Hilary K. Finucane

The paper uses supervised learning to fine-map cis-eQTLs, identifying 20,913 additional putative causal eQTLs and 310 candidate genes.

89 citationstop 1%

humanGWAS summary statistics

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