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Network analysis of gene essentiality in functional genomics experiments

Many genomic techniques have been developed to study gene essentiality genome-wide, such as CRISPR and shRNA screens. Our analyses of public CRISPR screens suggest protein interaction networks, when integrated with gene expression or histone marks, are highly predictive of gene essentiality. Meanwhi...

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Detalles Bibliográficos
Autores principales: Jiang, Peng, Wang, Hongfang, Li, Wei, Zang, Chongzhi, Li, Bo, Wong, Yinling J., Meyer, Cliff, Liu, Jun S., Aster, Jon C., Liu, X. Shirley
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4627418/
https://www.ncbi.nlm.nih.gov/pubmed/26518695
http://dx.doi.org/10.1186/s13059-015-0808-9
Descripción
Sumario:Many genomic techniques have been developed to study gene essentiality genome-wide, such as CRISPR and shRNA screens. Our analyses of public CRISPR screens suggest protein interaction networks, when integrated with gene expression or histone marks, are highly predictive of gene essentiality. Meanwhile, the quality of CRISPR and shRNA screen results can be significantly enhanced through network neighbor information. We also found network neighbor information to be very informative on prioritizing ChIP-seq target genes and survival indicator genes from tumor profiling. Thus, our study provides a general method for gene essentiality analysis in functional genomic experiments (http://nest.dfci.harvard.edu). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-015-0808-9) contains supplementary material, which is available to authorized users.