Multiple hot-deck imputation for network inference from RNA sequencing data | Zendy

Alyssa Imbert | Zendy; Armand Valsesia | Zendy; Caroline Le Gall | Zendy; Claudia Armenise | Zendy; Grégory Lefebvre | Zendy; PierreAntoine Gourraud | Zendy; Nathalie Viguerie | Zendy; Nathalie VillaVialaneix | Zendy

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Multiple hot-deck imputation for network inference from RNA sequencing data

Author(s) -

Alyssa Imbert,

Armand Valsesia,

Caroline Le Gall,

Claudia Armenise,

Grégory Lefebvre,

PierreAntoine Gourraud,

Nathalie Viguerie,

Nathalie VillaVialaneix

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx819

Subject(s) - imputation (statistics) , inference , computer science , data mining , artificial intelligence , machine learning , missing data

Network inference provides a global view of the relations existing between gene expression in a given transcriptomic experiment (often only for a restricted list of chosen genes). However, it is still a challenging problem: even if the cost of sequencing techniques has decreased over the last years, the number of samples in a given experiment is still (very) small compared to the number of genes.

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