A modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection
Mass screening diagnostics for Mycobacterium tuberculosis exist, but criticisms exist regarding the sensitivity and specificity of these tools. Here the authors use RNA-Seq and a modular bioinformatics approach using data from their own cohorts and meta-analysis of published cohorts to create a redu...
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Nature Portfolio
2018
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oai:doaj.org-article:f00dac82845249b8a6fa26d64cff32752021-12-02T15:34:17ZA modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection10.1038/s41467-018-04579-w2041-1723https://doaj.org/article/f00dac82845249b8a6fa26d64cff32752018-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-018-04579-whttps://doaj.org/toc/2041-1723Mass screening diagnostics for Mycobacterium tuberculosis exist, but criticisms exist regarding the sensitivity and specificity of these tools. Here the authors use RNA-Seq and a modular bioinformatics approach using data from their own cohorts and meta-analysis of published cohorts to create a reduced signature for detection of tuberculosis that does not detect other diseases.Akul SinghaniaRaman VermaChristine M. GrahamJo LeeTrang TranMatthew RichardsonPatrick LecinePhilippe LeissnerMatthew P. R. BerryRobert J. WilkinsonKarine KaiserMarc RodrigueGerrit WoltmannPranabashis HaldarAnne O’GarraNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-17 (2018) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Science Q |
| spellingShingle |
Science Q Akul Singhania Raman Verma Christine M. Graham Jo Lee Trang Tran Matthew Richardson Patrick Lecine Philippe Leissner Matthew P. R. Berry Robert J. Wilkinson Karine Kaiser Marc Rodrigue Gerrit Woltmann Pranabashis Haldar Anne O’Garra A modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection |
| description |
Mass screening diagnostics for Mycobacterium tuberculosis exist, but criticisms exist regarding the sensitivity and specificity of these tools. Here the authors use RNA-Seq and a modular bioinformatics approach using data from their own cohorts and meta-analysis of published cohorts to create a reduced signature for detection of tuberculosis that does not detect other diseases. |
| format |
article |
| author |
Akul Singhania Raman Verma Christine M. Graham Jo Lee Trang Tran Matthew Richardson Patrick Lecine Philippe Leissner Matthew P. R. Berry Robert J. Wilkinson Karine Kaiser Marc Rodrigue Gerrit Woltmann Pranabashis Haldar Anne O’Garra |
| author_facet |
Akul Singhania Raman Verma Christine M. Graham Jo Lee Trang Tran Matthew Richardson Patrick Lecine Philippe Leissner Matthew P. R. Berry Robert J. Wilkinson Karine Kaiser Marc Rodrigue Gerrit Woltmann Pranabashis Haldar Anne O’Garra |
| author_sort |
Akul Singhania |
| title |
A modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection |
| title_short |
A modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection |
| title_full |
A modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection |
| title_fullStr |
A modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection |
| title_full_unstemmed |
A modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection |
| title_sort |
modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection |
| publisher |
Nature Portfolio |
| publishDate |
2018 |
| url |
https://doaj.org/article/f00dac82845249b8a6fa26d64cff3275 |
| work_keys_str_mv |
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