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Nevin Manimala Statistics

Protocol to analyze dysregulation of the eIF4F complex in human cancers using R software and large public datasets

STAR Protoc. 2022 Dec 16;3(4):101880. doi: 10.1016/j.xpro.2022.101880. Epub 2022 Dec 12.

ABSTRACT

Understanding dysregulation of the eukaryotic initiation factor 4F (eIF4F) complex across tumor types is critical to cancer treatment development. We present a protocol and accompanying R package “eIF4F.analysis”. We describe analysis of copy number status, gene abundance and stoichiometry, survival probability, expression covariation, correlating genes, mRNA/protein correlation, and protein co-expression. Using publicly available large multi-omics data, eIF4F.analysis permits computationally derived and statistically powerful inferences regarding initiation factor regulation in human cancers and clinical relevance of protein interactions within the eIF4F complex. For complete details on the use and execution of this protocol, please refer to Wu and Wagner (2021).1.

PMID:36595939 | DOI:10.1016/j.xpro.2022.101880

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