View source: R/GenePvalsFromEset.R

ct.generateResults | R Documentation |

This is a wrapper function that enables direct generation of target-level p-values from a crispr screen.

ct.generateResults( fit, annotation, RRAalphaCutoff = 0.1, permutations = 1000, contrast.term = NULL, scoring = c("combined", "pvalue", "fc"), alt.annotation = NULL, permutation.seed = NULL )

`fit` |
An object of class |

`annotation` |
An annotation file for the experiment. gRNAs are annotated by
row, and must minimally contain columns |

`RRAalphaCutoff` |
A cutoff to use when defining gRNAs with significantly altered abundance during the RRAa aggregation step, which may be specified
as a single numeric value on the unit interval or as a logical vector. When supplied as a logical vector (of length equal to Note that this function uses directional tests to identify enriched or depleted targets, and when RRAalphaCutoff is provided as a logical vector the interpretation of the various aggregation statistics is going to be dependent on the specific criteria used to select reagents for inclusion. |

`permutations` |
The number of permutations to use during the RRAa aggregation step. |

`contrast.term` |
If a fit object with multiple coefficients is passed in, a string indiating the coefficient of interest. |

`scoring` |
The gRNA ranking method to use in RRAa aggregation. May take one of three values: |

`alt.annotation` |
Libraries targeting ambiguous biological elements (e.g., alternative promoters to a gene where the boundaries between elelments is contested) may contain reagents that are plausibly annotated to a finite set of possible targets. To accomodate this, users may supply an alternative reagent annotation in the form of a named list of vectors, where each list element corresponds something coercible to a to a character vector of associated targets that will ultimately be assembled into the 'geneSymbol' column of the 'resultsDF' object. Each of these character vectors should be named identically to a row of the supplied fit object (e.g., the 'row.names'). It is assumed that the 'geneID' values are assigned unambiguously to the reagents, and are passed through directly. |

`permutation.seed` |
numeric seed for permutation reproducibility.
Default: |

A dataframe containing gRNA-level and target-level statistics. In addition to the information present in the supplied annotation object, the returned object indicates P-values and Q-values for the depletion and enrichment of each gRNA and associated target, the median log2 fold change estimate among all gRNAs associated with the target, and Rho statistics that are calculated internally by the RRAa algorithm that may be useful in ranking targets that are considered significant at a given alpha or false discovery threshold.

A 'resultsDF' formatted dataframe containing gene-level statistics.

Russell Bainer

data('fit') data('ann') output <- ct.generateResults(fit, ann, permutations = 10) head(output) p = seq(0, 1, length.out=20) fc = seq(-3, 3, length.out=20) fc[2] = NA fc[3] = -20 stats = data.frame( Depletion.P=p, Enrichment.P=rev(p), fc=fc ) ct.applyAlpha(stats,scoring='combined')

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