Computes target guideRNA universe and maps, annotates, and scores their genomic targets.
addGuides(guideSet, guides = NULL, n_mismatches = 0, blacklist_penalty = 10, guide_length = 19, gc_content = c(0.4, 0.8), min_Son = NULL, max_Soff = NULL, consensus_range = NULL, alpha = 100, n_clust = 11, five_prime_seq = NULL, PAM = "NGG", lower_count = 5, force = FALSE)
guides | Character. Optional vector of pre-computed guideRNA sequences to map and annotate. Will restrict downstream analysis to |
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n_mismatches | Integer from 0 through 3. Maximal number of tolerated mismatches when assessing guideRNA binding targets. Defaults to 0. |
guide_length | Single integer between 12 and 26. Basepair size of the guideRNAs. Defaults to 16. |
gc_content | Numeric vector of length two. Elements must be from 0 through 1. For example, c(0.4, 0.8) blacklists guides with GC content not between 40 and 80 percent. Passed to |
min_Son | Numeric. Minimal on target score of guides. If |
consensus_range | Data.frame with repname, start, and end columns. Scores guideRNA target binding sites outside of provided consensus range neutrally. Passed to |
alpha | Numeric. Off-target score coefficient. Large |
n_clust | Single positive integer <= 20. Number of groups to cluster guideRNAs into. Higher n_clust usually gives better results but comes with a speed penalty when computing guide combinations. Passed to |
five_prime_seq | Character. Sequence requirement for 5' start of guideRNAs, e.g. G nucleotide for transcription from U6 promoter. |
PAM | Character. Currently only 'NGG' PAM is supported. |
lower_count | Numeric. Passed to jellyfish kmer counting. Only kmers occuring at least |
force | Logical. If |
guideSet. | guideSet object containing targets. |
blacklist_penalty. | Numeric. Off-target score multiplier (10 by default) for blacklisted genomic regions. Ignored if |
min_Soff | Numeric. Maximal off target score of guides. If |
Returns a guideSet object containing guides.
if (FALSE) { gs <- createGuideSet(Hsapiens, tes = te_annotation_df) gs <- addTargets(gs, targets = 'LTR13') gs <- addGuides(gs, guide_length = 16, n_mismatches = 0, gc_content = c(0.25, 0.9), n_clust = 12) gs <- plotGuides(gs) }