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HaSAPPy: A tool for candidate identification in pooled forward genetic screens of haploid mammalian cells
Haploid cells are increasingly used for screening of complex pathways in animal genomes. Hemizygous mutations introduced through viral insertional mutagenesis can be directly selected for phenotypic changes. Here we present HaSAPPy a tool for analysing sequencing datasets of screens using insertiona...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5798846/ https://www.ncbi.nlm.nih.gov/pubmed/29337991 http://dx.doi.org/10.1371/journal.pcbi.1005950 |
Sumario: | Haploid cells are increasingly used for screening of complex pathways in animal genomes. Hemizygous mutations introduced through viral insertional mutagenesis can be directly selected for phenotypic changes. Here we present HaSAPPy a tool for analysing sequencing datasets of screens using insertional mutations in large pools of haploid cells. Candidate gene prediction is implemented through identification of enrichment of insertional mutations after selection by simultaneously evaluating several parameters. We have developed HaSAPPy for analysis of genetic screens for silencing factors of X chromosome inactivation in haploid mouse embryonic stem cells. To benchmark the performance, we further analyse several datasets of genetic screens in human haploid cells for which candidates have been validated. Our results support the effective candidate prediction strategy of HaSAPPy. HaSAPPy is implemented in Python, licensed under the MIT license, and is available from https://github.com/gdiminin/HaSAPPy. |
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