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Linking co-expression modules with phenotypes.
Kumar, Rakesh; Ojha, Krishna Kumar; Yadav, Harlokesh Narayan; Singh, Vijay Kumar.
Afiliación
  • Kumar R; Department of Bioinformatics, Central University of South Bihar, Gaya, Bihar 824236, India.
  • Ojha KK; Department of Bioinformatics, Central University of South Bihar, Gaya, Bihar 824236, India.
  • Yadav HN; Department of Pharmacology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi - 110029, India.
  • Singh VK; Department of Bioinformatics, Central University of South Bihar, Gaya, Bihar 824236, India.
Bioinformation ; 18(4): 438-441, 2022.
Article en En | MEDLINE | ID: mdl-36909689
ABSTRACT
The method for quantifying the association between co-expression module and clinical trait of interest requires application of dimensionality reduction to summaries modules as one dimensional (1D) vector. However, these methods are often linked with information loss. The amount of information lost depends upon the percentage of variance captured by the reduced 1D vector. Therefore, it is of interest to describe a method using analysis of rank (AOR) to assess the association between module and clinical trait of interest. This method works with clinical traits represented as binary class labels and can be adopted for clinical traits measured in continuous scale by dividing samples in two groups around median value. Application of the AOR method on test data for muscle gene expression profiles identifies modules significantly associated with diabetes status.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Bioinformation Año: 2022 Tipo del documento: Article País de afiliación: India

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Bioinformation Año: 2022 Tipo del documento: Article País de afiliación: India
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