Author

J. Sacchettini

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Microbiology· 2 Evolutionary Biology· 1

Signature Assays, Organisms & Methods

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Assay:whole-genome sequencing· 3 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:chromatin & epigenetic regulation· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:GWAS / association mapping· 1 Organism:human· 1

Frequent Co-Authors

L. Freschi· 2 shared M. R. Farhat· 2 shared R. Calderon· 2 shared T. Ioerger· 2 shared A. Dixit· 1 shared A. Sloutsky· 1 shared B. de Jong· 1 shared B. Mathema· 1 shared

Activity by Year

2018-2018 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersEvolutionary Biology

L. Freschi

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Mutations in Rv2983 as a novel determinant of resistance to nitroimidazole drugs in Mycobacterium tuberculosis

D. Rifat, S.-Y. Li, T. Ioerger, J.-P. Lanoix, J. Lee, G. Bashiri, J. Sacchettini, E. Nuermberger

This paper identifies Rv2983 as a novel gene conferring resistance to nitroimidazole drugs in Mycobacterium tuberculosis and highlights the challenges in detecting such resistance.

bioRxiv · Oct 31, 2018 · PreprintMicrobiology

Genome wide association with quantitative resistance phenotypes in Mycobacterium tuberculosis reveals novel resistance genes and regulatory regions

M. R. Farhat, L. Freschi, R. Calderon, T. Ioerger, M. Snyder, C. J. Meehan, B. de Jong, L. Rigouts, A. Sloutsky, D. Kaur, S. Sunyaev, D. van Soolingen, J. Shendure, J. Sacchettini, M. Murray

This study identifies novel resistance genes and regulatory regions in Mycobacterium tuberculosis using genome-wide association analysis of drug resistance phenotypes.

bioRxiv · Oct 1, 2018Evolutionary Biology

Genotypic clustering does not imply recent tuberculosis transmission in a high prevalence setting: A genomic epidemiology study in Lima, Peru

A. Dixit, L. Freschi, R. Vargas, R. Calderon, J. Sacchettini, F. Drobniewski, J. T. Galea, C. Contreras, R. Yataco, Z. Zhang, L. Lecca, S.-O. Kolokotronis, B. Mathema, M. R. Farhat

This study uses genomic data to show that TB clusters identified by traditional methods may persist for decades, and WGS reveals genetic factors that may enhance transmissibility.

bioRxiv · Sep 16, 2018Microbiology