Gscreend: modelling asymmetric count ratios in CRISPR screens to decrease experiment size and improve phenotype detection
Pooled CRISPR screens are a powerful tool to probe genotype-phenotype relationships at genome-wide scale. However, criteria for optimal design are missing, and it remains unclear how experimental parameters affect results. Here, we report that random decreases in gRNA abundance are more likely than...
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| Hauptverfasser: | , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
02 March 2020
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| In: |
Genome biology
Year: 2020, Jahrgang: 21 |
| ISSN: | 1474-760X |
| DOI: | 10.1186/s13059-020-1939-1 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1186/s13059-020-1939-1
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| Verfasserangaben: | Katharina Imkeller, Giulia Ambrosi, Michael Boutros and Wolfgang Huber |
| Zusammenfassung: | Pooled CRISPR screens are a powerful tool to probe genotype-phenotype relationships at genome-wide scale. However, criteria for optimal design are missing, and it remains unclear how experimental parameters affect results. Here, we report that random decreases in gRNA abundance are more likely than increases due to bottle-neck effects during the cell proliferation phase. Failure to consider this asymmetry leads to loss of detection power. We provide a new statistical test that addresses this problem and improves hit detection at reduced experiment size. The method is implemented in the R package gscreend, which is available at http://bioconductor.org/packages/gscreend. |
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| Beschreibung: | Gesehen am 27.04.2020 |
| Beschreibung: | Online Resource |
| ISSN: | 1474-760X |
| DOI: | 10.1186/s13059-020-1939-1 |