FIREWORKS: a bottom-up approach to integrative coessentiality network analysis.
Life Sci Alliance
; 4(2)2021 02.
Article
em En
| MEDLINE
| ID: mdl-33328249
ABSTRACT
Genetic coessentiality analysis, a computational approach which identifies genes sharing a common effect on cell fitness across large-scale screening datasets, has emerged as a powerful tool to identify functional relationships between human genes. However, widespread implementation of coessentiality to study individual genes and pathways is limited by systematic biases in existing coessentiality approaches and accessibility barriers for investigators without computational expertise. We created FIREWORKS, a method and interactive tool for the construction and statistical analysis of coessentiality networks centered around gene(s) provided by the user. FIREWORKS incorporates a novel bias reduction approach to reduce false discoveries, enables restriction of coessentiality analyses to custom subsets of cell lines, and integrates multiomic and drug-gene interaction datasets to investigate and target contextual gene essentiality. We demonstrate the broad utility of FIREWORKS through case vignettes investigating gene function and specialization, indirect therapeutic targeting of "undruggable" proteins, and context-specific rewiring of genetic networks.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Software
/
Regulação da Expressão Gênica
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Biologia Computacional
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Genômica
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Redes Reguladoras de Genes
Limite:
Humans
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Article