View source: R/contrastScatter.R

ct.scatter | R Documentation |

This is a function for comparing the results of two screening experiments. Given two `summaryDF`

,
the function places them in register with one another, generates a simplified scatter plot where enrichment or depletion
in each contrast is represented by the associated "signed" log10 (*P*/*Q*)-value (where enriched signals are represented
in the positive direction and depleted signals are shown in the negative direction), and returns an invisible 'data.frame'
containing the target X-axis and Y-axis coordinates and corresponding quadrant.

This is a target-level analysis, and some minor simplifications are introduced to screen signals for the sake of clarity. Principal among these is the decision to collapse gene signals to a single directional enrichment statistic. Target-level signals are typically aggregates of many guide-level signals, it is formally possible for targets to be both significantly enriched and significantly depleted within a single screen contrast as a result of substantially divergent reagent activity. This behavior is uncommon, however, and so targets are represented by selecting the direction of enrichment or depletion associated with the most significant (*P*/*Q*)-value. This directionality is then encoded into the X-axis and Y-axis position of the target as the sign of the signal as described above.

ct.scatter( dflist, targets = c("geneSymbol", "geneID"), statistic = c("best.p", "best.q"), cutoff = 0.05, plot.it = TRUE )

`dflist` |
A (named) list of results dataframes, of length 2. See |

`targets` |
Column of the provided |

`statistic` |
Statistic to plot on each axis (after -log10 transformation). Must be 'p', 'q', or 'rho'. |

`cutoff` |
significance cutoff used to define the significance quadrants (cannot be exactly zero). |

`plot.it` |
Logical indicating whether to compose the plot on the default device. |

Invisibly, a list of length 4 containing the genes passing significance for the respective quadrants.

Russell Bainer

data('resultsDF') scat <- ct.scatter(list('FirstResult' = resultsDF[100:2100,], 'SecondResult' = resultsDF[1:2000,])) head(scat)

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