Finds the optimal combination of non-redundant guideRNAs.

addCombinations(guideSet, max_guides = 5, greedy = TRUE,
  iterations = 10, alpha = 100, force = FALSE)

Arguments

max_guides

Numeric. Maximum number of distinct guides to consider when calculating combinations. Do not use a higher number than experimentally feasible.

greedy

Logical. If TRUE (the default), performs an additional greedy search optimization for selected guide combinations.

iterations

Integer > 0. Number of greedy search iterations (10 by default).

alpha

Numeric. Off-target score coefficient. Large alpha penalizes combinations with high off-target score while alpha = 0 ignores off-targets and picks combinations with highest on-target binding. Defaults to 10.

force

Logical. If TRUE, overwrites existing combinations.

guideSet.

guideSet object containing guides.

method

String. Method of how to pick the best guideRNA per cluster.

coeff

Integer. If method is regression, coeff modifies the slope of the linear regression.

Value

Returns a guideSet object contaning combinations.

See also

Examples

if (FALSE) { gs <- createGuideSet(Hsapiens, tes = te_annotation_df) gs <- addTargets(gs, targets = 'LTR13A') gs <- addGuides(gs, guide_length = 16) gs <- addCombinations(gs, max_guides = 8) gs <- plotCombinations(gs) }