Modeling and cleaning RNA-seq data significantly improve detection of differentially expressed genes

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1471-2105

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Modeling and cleaning RNA-seq data significantly improve detection of differentially expressed genes ; volume:23 ; number:1 ; day:16 ; month:11 ; year:2022 ; pages:1-14 ; date:12.2022
BMC bioinformatics ; 23, Heft 1 (16.11.2022), 1-14, 12.2022

Creator: Deyneko, Igor V.
Mustafaev, Orkhan N.
Tyurin, Alexander А
Zhukova, Ksenya V.
Varzari, Alexander
Goldenkova-Pavlova, Irina V.

Contributor: SpringerLink (Online service)

DOI: 10.1186/s12859-022-05023-z

URN: urn:nbn:de:101:1-2023012909035807651299

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:28 AM CEST

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Deyneko, Igor V.
Mustafaev, Orkhan N.
Tyurin, Alexander А
Zhukova, Ksenya V.
Varzari, Alexander
Goldenkova-Pavlova, Irina V.
SpringerLink (Online service)

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Modeling and cleaning RNA-seq data significantly improve detection of differentially expressed genes

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Other Objects (12)

Robustness of single-cell RNA-seq for identifying differentially expressed genes

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Blood RNA-Seq profiling reveals a set of circular RNAs differentially expressed in frail individuals

Detecting multivariate differentially expressed genes

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