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GeneFishing to reconstruct context specific portraits of biological processes. | LitMetric

AI Article Synopsis

  • * GeneFishing utilizes techniques such as dimensionality reduction and clustering to identify genes linked to specific biological processes, demonstrating its effectiveness with a case study on cholesterol metabolism that revealed previously unknown gene connections.
  • * Overall, GeneFishing shows promise as a versatile tool for uncovering complex biological relationships, successfully identifying notable genes across different tissues and validating new findings in cholesterol metabolism through experimental evidence.

Article Abstract

Rapid advances in genomic technologies have led to a wealth of diverse data, from which novel discoveries can be gleaned through the application of robust statistical and computational methods. Here, we describe GeneFishing, a semisupervised computational approach to reconstruct context-specific portraits of biological processes by leveraging gene-gene coexpression information. GeneFishing incorporates multiple high-dimensional statistical ideas, including dimensionality reduction, clustering, subsampling, and results aggregation, to produce robust results. To illustrate the power of our method, we applied it using 21 genes involved in cholesterol metabolism as "bait" to "fish out" (or identify) genes not previously identified as being connected to cholesterol metabolism. Using simulation and real datasets, we found that the results obtained through GeneFishing were more interesting for our study than those provided by related gene prioritization methods. In particular, application of GeneFishing to the GTEx liver RNA sequencing (RNAseq) data not only reidentified many known cholesterol-related genes, but also pointed to glyoxalase I () as a gene implicated in cholesterol metabolism. In a follow-up experiment, we found that knockdown in human hepatoma cell lines increased levels of cellular cholesterol ester, validating a role for in cholesterol metabolism. In addition, we performed pantissue analysis by applying GeneFishing on various tissues and identified many potential tissue-specific cholesterol metabolism-related genes. GeneFishing appears to be a powerful tool for identifying related components of complex biological systems and may be used across a wide range of applications.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754596PMC
http://dx.doi.org/10.1073/pnas.1820340116DOI Listing

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