| Title: | Multi-locus multi-purpose Crispr/Cas design |
|---|---|
| Description: | This package is for designing Crispr/Cas9 and Prime Editing experiments. It contains functions to (1) define and transform genomic targets, (2) find spacers (4) count offtarget (mis)matches, and (5) compute Doench2016/2014 targeting efficiency. Care has been taken for multicrispr to scale well towards large target sets, enabling the design of large Crispr/Cas9 libraries. |
| Authors: | Aditya Bhagwat [aut, cre], Richie ´Cotton [aut], Rene Wiegandt [ctb], Mette Bentsen [ctb], Jens Preussner [ctb], Michael Lawrence [ctb], Hervé Pagès [ctb], Johannes Graumann [sad], Mario Looso [sad, rth] |
| Maintainer: | Aditya Bhagwat <[email protected]> |
| License: | GPL-2 |
| Version: | 1.15.0 |
| Built: | 2024-07-22 05:22:56 UTC |
| Source: | https://github.com/bioc/multicrispr |
Add genome matches
add_genome_matches( spacers, bsgenome = getBSgenome(genome(spacers)[1]), mismatches = 2, pam = "NGG", offtargetmethod = c("bowtie", "pdict")[1], outdir = OUTDIR, indexedgenomesdir = INDEXEDGENOMESDIR, verbose = TRUE )add_genome_matches( spacers, bsgenome = getBSgenome(genome(spacers)[1]), mismatches = 2, pam = "NGG", offtargetmethod = c("bowtie", "pdict")[1], outdir = OUTDIR, indexedgenomesdir = INDEXEDGENOMESDIR, verbose = TRUE )
spacers |
GRanges |
bsgenome |
BSgenome |
mismatches |
number |
pam |
string |
offtargetmethod |
'bowtie' or 'pdict' |
outdir |
bowtie output directory |
indexedgenomesdir |
directory with indexed genomes |
verbose |
TRUE (default) or FALSE |
GRanges
require(magrittr) file <- system.file('extdata/SRF.bed', package='multicrispr') bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 targets0 <- bed_to_granges(file, 'mm10') targets <- extend(targets0) spacers <- find_spacers(targets, bsgenome, complement = FALSE, ontargetmethod = NULL, offtargetmethod = NULL) spacers %<>% extract(1:100) spacers %<>% add_genome_matches(bsgenome)require(magrittr) file <- system.file('extdata/SRF.bed', package='multicrispr') bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 targets0 <- bed_to_granges(file, 'mm10') targets <- extend(targets0) spacers <- find_spacers(targets, bsgenome, complement = FALSE, ontargetmethod = NULL, offtargetmethod = NULL) spacers %<>% extract(1:100) spacers %<>% add_genome_matches(bsgenome)
Add inverse strand
add_inverse_strand(gr, verbose = FALSE, plot = FALSE, ...)add_inverse_strand(gr, verbose = FALSE, plot = FALSE, ...)
gr |
|
verbose |
TRUE or FALSE (default) |
plot |
TRUE or FALSE (default) |
... |
|
# PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) add_inverse_strand(gr, plot = TRUE) # TFBS example #------------- bedfile <- system.file('extdata/SRF.bed', package='multicrispr') gr <- bed_to_granges(bedfile, genome = 'mm10') add_inverse_strand(gr)# PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) add_inverse_strand(gr, plot = TRUE) # TFBS example #------------- bedfile <- system.file('extdata/SRF.bed', package='multicrispr') gr <- bed_to_granges(bedfile, genome = 'mm10') add_inverse_strand(gr)
Add sequence to GRanges
add_seq(gr, bsgenome, verbose = FALSE, as.character = TRUE)add_seq(gr, bsgenome, verbose = FALSE, as.character = TRUE)
gr |
|
bsgenome |
|
verbose |
TRUE or FALSE (default) |
as.character |
TRUE (default) or FALSE |
# PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) (gr %<>% add_seq(bsgenome)) # TFBS example #------------- bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 bedfile <- system.file('extdata/SRF.bed', package='multicrispr') gr <- bed_to_granges(bedfile, 'mm10') (gr %<>% add_seq(bsgenome))# PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) (gr %<>% add_seq(bsgenome)) # TFBS example #------------- bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 bedfile <- system.file('extdata/SRF.bed', package='multicrispr') gr <- bed_to_granges(bedfile, 'mm10') (gr %<>% add_seq(bsgenome))
Add target matches
add_target_matches( spacers, targets, bsgenome, mismatches = 2, pam = "NGG", outdir = OUTDIR, verbose = TRUE )add_target_matches( spacers, targets, bsgenome, mismatches = 2, pam = "NGG", outdir = OUTDIR, verbose = TRUE )
spacers |
GRanges |
targets |
GRanges |
bsgenome |
BSgenome |
mismatches |
number |
pam |
string |
outdir |
bowtie output directory |
verbose |
TRUE (default) or FALSE |
GRanges
require(magrittr) file <- system.file('extdata/SRF.bed', package='multicrispr') bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 targets0 <- bed_to_granges(file, 'mm10') targets <- extend(targets0) spacers <- find_spacers(targets, bsgenome, complement = FALSE, ontargetmethod = NULL, offtargetmethod = NULL) spacers %<>% add_target_matches(targets, bsgenome)require(magrittr) file <- system.file('extdata/SRF.bed', package='multicrispr') bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 targets0 <- bed_to_granges(file, 'mm10') targets <- extend(targets0) spacers <- find_spacers(targets, bsgenome, complement = FALSE, ontargetmethod = NULL, offtargetmethod = NULL) spacers %<>% add_target_matches(targets, bsgenome)
Read bedfile into GRanges
bed_to_granges( bedfile, genome, txdb = NULL, do_order = TRUE, plot = TRUE, verbose = TRUE )bed_to_granges( bedfile, genome, txdb = NULL, do_order = TRUE, plot = TRUE, verbose = TRUE )
bedfile |
file path |
genome |
string: UCSC genome name (e.g. 'mm10') |
txdb |
NULL (default) or |
do_order |
TRUE (default) or FALSE: order on seqnames and star? |
plot |
TRUE (default) or FALSE: plot karyogram? |
verbose |
TRUE (default) or FALSE |
char_to_granges, genes_to_granges
bedfile <- system.file('extdata/SRF.bed', package = 'multicrispr') bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 (gr <- bed_to_granges(bedfile, genome='mm10'))bedfile <- system.file('extdata/SRF.bed', package = 'multicrispr') bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 (gr <- bed_to_granges(bedfile, genome='mm10'))
Convert character vector into GRanges
char_to_granges(x, bsgenome)char_to_granges(x, bsgenome)
x |
character vector |
bsgenome |
bed_to_granges, genes_to_granges
require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 x <- c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+') # ins gr <- char_to_granges(x, bsgenome) plot_intervals(gr, facet_var = c('targetname', 'seqnames'))require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 x <- c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+') # ins gr <- char_to_granges(x, bsgenome) plot_intervals(gr, facet_var = c('targetname', 'seqnames'))
Double flank
double_flank( gr, upstart = -200, upend = -1, downstart = 1, downend = 200, strandaware = TRUE, plot = FALSE, linetype_var = "set", ... )double_flank( gr, upstart = -200, upend = -1, downstart = 1, downend = 200, strandaware = TRUE, plot = FALSE, linetype_var = "set", ... )
gr |
|
upstart |
upstream flank start in relation to start(gr) |
upend |
upstream flank end in relation to start(gr) |
downstart |
downstream flank start in relation to end(gr) |
downend |
downstream flank end in relation to end(gr) |
strandaware |
TRUE (default) or FALSE |
plot |
TRUE or FALSE (default) |
linetype_var |
gr var mapped to linetype |
... |
passed to plot_intervals |
# Prime Editing example #---------------------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) double_flank(gr, -10, -1, +1, +20, plot = TRUE) # TFBS example #------------- bedfile <- system.file('extdata/SRF.bed', package='multicrispr') gr <- bed_to_granges(bedfile, genome = 'mm10', plot = FALSE) double_flank(gr, plot = TRUE)# Prime Editing example #---------------------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) double_flank(gr, -10, -1, +1, +20, plot = TRUE) # TFBS example #------------- bedfile <- system.file('extdata/SRF.bed', package='multicrispr') gr <- bed_to_granges(bedfile, genome = 'mm10', plot = FALSE) double_flank(gr, plot = TRUE)
Extend target ranges to span in which to look for spacer-pam seqs
extend_for_pe( gr, bsgenome, nrt = 16, spacer = strrep("N", 20), pam = "NGG", plot = FALSE )extend_for_pe( gr, bsgenome, nrt = 16, spacer = strrep("N", 20), pam = "NGG", plot = FALSE )
gr |
|
bsgenome |
|
nrt |
number: reverse transcription length |
spacer |
string: spacer pattern in extended IUPAC alphabet |
pam |
string: pam pattern in extended IUPAC alphabet |
plot |
TRUE (default) or FALSE |
Extend target ranges to find nearby spacers for prime editing
require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c( PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome = bsgenome) find_primespacers(gr, bsgenome) (grext <- extend_for_pe(gr)) find_spacers(grext, bsgenome, complement = FALSE)require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c( PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome = bsgenome) find_primespacers(gr, bsgenome) (grext <- extend_for_pe(gr)) find_spacers(grext, bsgenome, complement = FALSE)
Extend prime editing target to find GG sites in accessible neighbourhood
extend_pe_to_gg(gr, nrt = 16, plot = FALSE)extend_pe_to_gg(gr, nrt = 16, plot = FALSE)
gr |
target |
nrt |
n RT nucleotides (default 16, recommended 10-16) |
plot |
TRUE or FALSE (default) |
Extends each target range to the area in which to search for a prime editing GG duplet, as shown in the sketch below.
===============> —-GG———> —-GG———> ** <———GG— <———GG—- <===============
# PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) extend_pe_to_gg(gr, plot = TRUE)# PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) extend_pe_to_gg(gr, plot = TRUE)
Extract subranges that match pattern
extract_matchranges(gr, bsgenome, pattern, plot = FALSE)extract_matchranges(gr, bsgenome, pattern, plot = FALSE)
gr |
|
bsgenome |
|
pattern |
string: search pattern in extended IUPAC alphabet |
plot |
TRUE or FALSE (default) |
# PE example #------------ require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) gr %<>% extend_for_pe() pattern <- strrep('N',20) %>% paste0('NGG') extract_matchranges(gr, bsgenome, pattern, plot = TRUE) # TFBS examples #-------------- bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 bedfile <- system.file('extdata/SRF.bed', package='multicrispr') gr <- bed_to_granges(bedfile, 'mm10') %>% extend() extract_matchranges(gr, bsgenome, pattern = strrep('N',20) %>% paste0('NGG'))# PE example #------------ require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) gr %<>% extend_for_pe() pattern <- strrep('N',20) %>% paste0('NGG') extract_matchranges(gr, bsgenome, pattern, plot = TRUE) # TFBS examples #-------------- bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 bedfile <- system.file('extdata/SRF.bed', package='multicrispr') gr <- bed_to_granges(bedfile, 'mm10') %>% extend() extract_matchranges(gr, bsgenome, pattern = strrep('N',20) %>% paste0('NGG'))
Extract subranges from a GRanges-class object
extract_subranges(gr, ir, plot = FALSE)extract_subranges(gr, ir, plot = FALSE)
gr |
|
ir |
|
plot |
TRUE or FALSE (default) |
# Extract a subrange gr <- GenomicRanges::GRanges(c(A = 'chr1:1-100:+', B = 'chr1:1-100:-')) gr$targetname <- 'AB' ir <- IRanges::IRanges(c(A = '1-10', A = '11-20', B = '1-10', B = '11-20')) extract_subranges(gr, ir, plot = TRUE) # Return empty GRanges for empty IRanges extract_subranges(GenomicRanges::GRanges('chr1:345-456'), IRanges::IRanges())# Extract a subrange gr <- GenomicRanges::GRanges(c(A = 'chr1:1-100:+', B = 'chr1:1-100:-')) gr$targetname <- 'AB' ir <- IRanges::IRanges(c(A = '1-10', A = '11-20', B = '1-10', B = '11-20')) extract_subranges(gr, ir, plot = TRUE) # Return empty GRanges for empty IRanges extract_subranges(GenomicRanges::GRanges('chr1:345-456'), IRanges::IRanges())
Find GG
find_gg(gr)find_gg(gr)
gr |
# PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) gr %<>% extend_pe_to_gg(plot = TRUE) %>% add_seq(bsgenome) find_gg(gr)# PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) gr %<>% extend_pe_to_gg(plot = TRUE) %>% add_seq(bsgenome) find_gg(gr)
Find prime editing spacers around target ranges
find_primespacers( gr, bsgenome, edits = get_plus_seq(bsgenome, gr), nprimer = 13, nrt = 16, ontargetmethod = c("Doench2014", "Doench2016")[1], offtargetmethod = c("bowtie", "pdict")[1], mismatches = 0, nickmatches = 2, indexedgenomesdir = INDEXEDGENOMESDIR, outdir = OUTDIR, verbose = TRUE, plot = TRUE, ... )find_primespacers( gr, bsgenome, edits = get_plus_seq(bsgenome, gr), nprimer = 13, nrt = 16, ontargetmethod = c("Doench2014", "Doench2016")[1], offtargetmethod = c("bowtie", "pdict")[1], mismatches = 0, nickmatches = 2, indexedgenomesdir = INDEXEDGENOMESDIR, outdir = OUTDIR, verbose = TRUE, plot = TRUE, ... )
gr |
|
bsgenome |
|
edits |
character vector: desired edits on '+' strand.
If named, names should be identical to those of |
nprimer |
n primer nucleotides (default 13, max 17) |
nrt |
n rev transcr nucleotides (default 16, recomm. 10-16) |
ontargetmethod |
'Doench2014' or 'Doench2016': on-target scoring method |
offtargetmethod |
'bowtie' or 'pdict' |
mismatches |
no of primespacer mismatches (default 0, to suppress offtarget analysis: -1) |
nickmatches |
no of nickspacer offtarget mismatches (default 2, to suppresses offtarget analysis: -1) |
indexedgenomesdir |
directory with indexed genomes
(as created by |
outdir |
directory whre offtarget analysis output is written |
verbose |
TRUE (default) or FALSE |
plot |
TRUE (default) or FALSE |
... |
passed to plot_intervals |
Below the architecture of a prime editing site. Edits can be performed anywhere in the revtranscript area.
spacer pam ——————–=== primer revtranscript ————-================ 1..............17....GG.......... .....................CC.......... ———-extension———-
GRanges-class with prime editing spacer
ranges and following mcols:
* crisprspacer: N20 spacers
* crisprpam: NGG PAMs
* crisprprimer: primer (on PAM strand)
* crisprtranscript: reverse transcript (on PAM strand)
* crisprextension: 3' extension of gRNA
contains: reverse transcription template + primer binding site
sequence can be found on non-PAM strand
* crisprextrange: genomic range of crispr extension
* Doench2016|4: on-target efficiency scores
* off0, off1, off2: number of offtargets with 0, 1, 2 mismatches
* off: total number of offtargets: off = off0 + off1 + ...
* nickrange: nickspacer range
* nickspacer: nickspacer sequence
* nickDoench2016|4: nickspacer Doench scores
* nickoff: nickspacer offtarget counts
find_spacers to find standard crispr sites
# Find PE spacers for 4 clinically relevant loci (Anzalone et al, 2019) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c( PRNP = 'chr20:4699600:+', # snp: prion disease HBB = 'chr11:5227002:-', # snp: sickle cell anemia HEXA = 'chr15:72346580-72346583:-', # del: tay sachs disease CFTR = 'chr7:117559593-117559595:+'), # ins: cystic fibrosis bsgenome) spacers <- find_primespacers(gr, bsgenome) spacers <- find_spacers(extend_for_pe(gr), bsgenome, complement = FALSE) # Edit PRNP locus for resistance against prion disease (Anzalone et al, 2019) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+'), bsgenome) find_primespacers(gr, bsgenome) find_primespacers(gr, bsgenome, edits = 'T')# Find PE spacers for 4 clinically relevant loci (Anzalone et al, 2019) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c( PRNP = 'chr20:4699600:+', # snp: prion disease HBB = 'chr11:5227002:-', # snp: sickle cell anemia HEXA = 'chr15:72346580-72346583:-', # del: tay sachs disease CFTR = 'chr7:117559593-117559595:+'), # ins: cystic fibrosis bsgenome) spacers <- find_primespacers(gr, bsgenome) spacers <- find_spacers(extend_for_pe(gr), bsgenome, complement = FALSE) # Edit PRNP locus for resistance against prion disease (Anzalone et al, 2019) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+'), bsgenome) find_primespacers(gr, bsgenome) find_primespacers(gr, bsgenome, edits = 'T')
Find crispr spacers in targetranges
find_spacers( gr, bsgenome, spacer = strrep("N", 20), pam = "NGG", complement = TRUE, ontargetmethod = c("Doench2014", "Doench2016")[1], offtargetmethod = c("bowtie", "pdict")[1], offtargetfilterby = character(0), subtract_targets = FALSE, mismatches = 2, indexedgenomesdir = INDEXEDGENOMESDIR, outdir = OUTDIR, verbose = TRUE, plot = TRUE, ... )find_spacers( gr, bsgenome, spacer = strrep("N", 20), pam = "NGG", complement = TRUE, ontargetmethod = c("Doench2014", "Doench2016")[1], offtargetmethod = c("bowtie", "pdict")[1], offtargetfilterby = character(0), subtract_targets = FALSE, mismatches = 2, indexedgenomesdir = INDEXEDGENOMESDIR, outdir = OUTDIR, verbose = TRUE, plot = TRUE, ... )
gr |
|
bsgenome |
|
spacer |
string: spacer pattern in extended IUPAC alphabet |
pam |
string: pam pattern in extended IUPAC alphabet |
complement |
TRUE (default) or FALSE: also search in compl ranges? |
ontargetmethod |
'Doench2016','Doench2016' or NULL (no on-target score) |
offtargetmethod |
'bowtie', 'pdict', or NULL (no offtarget analysis) |
offtargetfilterby |
filter for best off-target counts by this variable |
subtract_targets |
TRUE or FALSE (default): whether to subtract target (mis)matches from offtarget counts |
mismatches |
0-3: allowed mismatches in offtargetanalysis (choose mismatch=-1 to suppress offtarget analysis) |
indexedgenomesdir |
directory with Bowtie-indexed genomes
(as produced with |
outdir |
directory where bowtie analysis results are written to |
verbose |
TRUE (default) or FALSE |
plot |
TRUE (default) or FALSE |
... |
passed to plot_intervals |
find_primespacers to find prime editing spacers
# PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) plot_intervals(gr) find_primespacers(gr, bsgenome) find_spacers(extend_for_pe(gr), bsgenome, complement=FALSE, mismatches=0) # complement = FALSE because extend_for_pe already # adds reverse complements and does so in a strand-specific # manner # TFBS example #------------- bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 bedfile <- system.file('extdata/SRF.bed', package='multicrispr') gr <- bed_to_granges(bedfile, 'mm10') %>% extend() gr %<>% extract(1:100) find_spacers(gr, bsgenome, subtract_targets = TRUE)# PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) plot_intervals(gr) find_primespacers(gr, bsgenome) find_spacers(extend_for_pe(gr), bsgenome, complement=FALSE, mismatches=0) # complement = FALSE because extend_for_pe already # adds reverse complements and does so in a strand-specific # manner # TFBS example #------------- bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 bedfile <- system.file('extdata/SRF.bed', package='multicrispr') gr <- bed_to_granges(bedfile, 'mm10') %>% extend() gr %<>% extract(1:100) find_spacers(gr, bsgenome, subtract_targets = TRUE)
Convert geneids into GRanges
genes_to_granges(geneids, txdb, complement = TRUE, plot = TRUE, verbose = TRUE) genefile_to_granges(file, txdb, complement = TRUE, plot = TRUE)genes_to_granges(geneids, txdb, complement = TRUE, plot = TRUE, verbose = TRUE) genefile_to_granges(file, txdb, complement = TRUE, plot = TRUE)
geneids |
Gene identifier vector |
txdb |
|
complement |
TRUE (default) or FALSE: add complementary strand? |
plot |
TRUE (default) or FALSE |
verbose |
TRUE (default) or FALSE |
file |
Gene identifier file (one per row) |
char_to_granges, bed_to_granges
# Entrez #------- genefile <- system.file('extdata/SRF.entrez', package='multicrispr') geneids <- as.character(read.table(genefile)[[1]]) txdb <- getFromNamespace('TxDb.Mmusculus.UCSC.mm10.knownGene', 'TxDb.Mmusculus.UCSC.mm10.knownGene') (gr <- genes_to_granges(geneids, txdb)) (gr <- genefile_to_granges(genefile, txdb)) # Ensembl #-------- # txdb <- AnnotationHub::AnnotationHub()[["AH75036"]] # genefile <- system.file('extdata/SRF.ensembl', package='multicrispr') # geneids <- as.character(read.table(genefile)[[1]]) # (gr <- genes_to_granges(geneids, txdb)) # (gr <- genefile_to_granges(genefile, txdb))# Entrez #------- genefile <- system.file('extdata/SRF.entrez', package='multicrispr') geneids <- as.character(read.table(genefile)[[1]]) txdb <- getFromNamespace('TxDb.Mmusculus.UCSC.mm10.knownGene', 'TxDb.Mmusculus.UCSC.mm10.knownGene') (gr <- genes_to_granges(geneids, txdb)) (gr <- genefile_to_granges(genefile, txdb)) # Ensembl #-------- # txdb <- AnnotationHub::AnnotationHub()[["AH75036"]] # genefile <- system.file('extdata/SRF.ensembl', package='multicrispr') # geneids <- as.character(read.table(genefile)[[1]]) # (gr <- genes_to_granges(geneids, txdb)) # (gr <- genefile_to_granges(genefile, txdb))
GRanges <-> data.table
gr2dt(gr) dt2gr(dt, seqinfo)gr2dt(gr) dt2gr(dt, seqinfo)
gr |
|
dt |
data.table |
seqinfo |
data.table (gr2dt) or GRanges (dt2gr)
bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) (dt <- gr2dt(gr)) (gr <- dt2gr(dt, BSgenome::seqinfo(bsgenome)))bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) (dt <- gr2dt(gr)) (gr <- dt2gr(dt, BSgenome::seqinfo(bsgenome)))
Has been indexed?
has_been_indexed(bsgenome, indexedgenomesdir = INDEXEDGENOMESDIR)has_been_indexed(bsgenome, indexedgenomesdir = INDEXEDGENOMESDIR)
bsgenome |
BSgenome |
indexedgenomesdir |
directory with indexed genomes |
TRUE or FALSE
bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 has_been_indexed(bsgenome)bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 has_been_indexed(bsgenome)
Bowtie index genome
index_genome( bsgenome, indexedgenomesdir = INDEXEDGENOMESDIR, download = TRUE, overwrite = FALSE )index_genome( bsgenome, indexedgenomesdir = INDEXEDGENOMESDIR, download = TRUE, overwrite = FALSE )
bsgenome |
|
indexedgenomesdir |
string: directory with bowtie-indexed genome |
download |
TRUE (default) or FALSE: whether to download pre-indexed version if available |
overwrite |
TRUE or FALSE (default) |
Checks whether already available locally. If not, checks whether indexed version can be downloaded from our s3 storage. If not, builds the index with bowtie. This can take a few hours, but is a one-time operation.
invisible(genomdir)
bsgenome <- BSgenome.Scerevisiae.UCSC.sacCer1::Scerevisiae index_genome(bsgenome, indexedgenomesdir = tempdir())bsgenome <- BSgenome.Scerevisiae.UCSC.sacCer1::Scerevisiae index_genome(bsgenome, indexedgenomesdir = tempdir())
Bowtie index targets
index_targets( targets, bsgenome = getBSgenome(genome(targets)[1]), outdir = OUTDIR, verbose = TRUE )index_targets( targets, bsgenome = getBSgenome(genome(targets)[1]), outdir = OUTDIR, verbose = TRUE )
targets |
|
bsgenome |
|
outdir |
string: output directory |
verbose |
TRUE (default) or FALSE |
invisible(targetdir)
require(magrittr) bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 bedfile <- system.file('extdata/SRF.bed', package = 'multicrispr') targets <- extend(bed_to_granges(bedfile, genome = 'mm10')) index_targets(targets, bsgenome)require(magrittr) bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 bedfile <- system.file('extdata/SRF.bed', package = 'multicrispr') targets <- extend(bed_to_granges(bedfile, genome = 'mm10')) index_targets(targets, bsgenome)
Interval plot GRanges
plot_intervals( gr, xref = "targetname", y = default_y(gr), nperchrom = 2, nchrom = 4, color_var = "targetname", facet_var = "seqnames", linetype_var = default_linetype(gr), size_var = default_size_var(gr), alpha_var = default_alpha_var(gr), title = NULL, scales = "free" )plot_intervals( gr, xref = "targetname", y = default_y(gr), nperchrom = 2, nchrom = 4, color_var = "targetname", facet_var = "seqnames", linetype_var = default_linetype(gr), size_var = default_size_var(gr), alpha_var = default_alpha_var(gr), title = NULL, scales = "free" )
gr |
|
xref |
gr var used for scaling x axis |
y |
'names' (default) or name of gr variable |
nperchrom |
number (default 1): n head (and n tail) targets shown per chromosome |
nchrom |
number (default 6) of chromosomes shown |
color_var |
'seqnames' (default) or other gr variable |
facet_var |
NULL(default) or gr variable mapped to facet |
linetype_var |
NULL (default) or gr variable mapped to linetype |
size_var |
NULL (default) or gr variable mapped to size |
alpha_var |
NULL or gr variable mapped to alpha |
title |
NULL or string: plot title |
scales |
'free', 'fixed', etc |
ggplot object
# SRF sites require(magrittr) bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 bedfile <- system.file('extdata/SRF.bed', package = 'multicrispr') targets <- bed_to_granges(bedfile, 'mm10', plot = FALSE) plot_intervals(targets) # PE targets bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', HBB = 'chr11:5227002:-', HEXA = 'chr15:72346580-72346583:-', CFTR = 'chr7:117559593-117559595:+'), bsgenome) spacers <- find_primespacers(gr, bsgenome, plot = FALSE) plot_intervals(gr) plot_intervals(extend_for_pe(gr)) plot_intervals(spacers) # Empty gr plot_intervals(GenomicRanges::GRanges())# SRF sites require(magrittr) bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 bedfile <- system.file('extdata/SRF.bed', package = 'multicrispr') targets <- bed_to_granges(bedfile, 'mm10', plot = FALSE) plot_intervals(targets) # PE targets bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', HBB = 'chr11:5227002:-', HEXA = 'chr15:72346580-72346583:-', CFTR = 'chr7:117559593-117559595:+'), bsgenome) spacers <- find_primespacers(gr, bsgenome, plot = FALSE) plot_intervals(gr) plot_intervals(extend_for_pe(gr)) plot_intervals(spacers) # Empty gr plot_intervals(GenomicRanges::GRanges())
Karyo/Interval Plot GRanges(List)
plot_karyogram(grlist, title = unique(genome(grlist)))plot_karyogram(grlist, title = unique(genome(grlist)))
grlist |
|
title |
plot title |
list
# Plot GRanges bedfile <- system.file('extdata/SRF.bed', package = 'multicrispr') gr <- bed_to_granges(bedfile, 'mm10', plot = FALSE) plot_karyogram(gr) # Plot GRangesList flanks <- up_flank(gr, stranded=FALSE) grlist <- GenomicRanges::GRangesList(sites = gr, flanks = flanks) plot_karyogram(grlist)# Plot GRanges bedfile <- system.file('extdata/SRF.bed', package = 'multicrispr') gr <- bed_to_granges(bedfile, 'mm10', plot = FALSE) plot_karyogram(gr) # Plot GRangesList flanks <- up_flank(gr, stranded=FALSE) grlist <- GenomicRanges::GRangesList(sites = gr, flanks = flanks) plot_karyogram(grlist)
Add Doench2014 or Doench2016 on-target efficiency scores
score_ontargets( spacers, bsgenome, ontargetmethod = c("Doench2014", "Doench2016")[1], chunksize = 10000, verbose = TRUE, plot = TRUE, ... )score_ontargets( spacers, bsgenome, ontargetmethod = c("Doench2014", "Doench2016")[1], chunksize = 10000, verbose = TRUE, plot = TRUE, ... )
spacers |
|
bsgenome |
|
ontargetmethod |
'Doench2014' (default) or 'Doench2016' (requires non-NULL argument python, virtualenv, or condaenv) |
chunksize |
Doench2016 is executed in chunks of chunksize |
verbose |
TRUE (default) or FALSE |
plot |
TRUE (default) or FALSE |
... |
passed to |
add_ontargets adds efficiency scores
filter_ontargets adds efficiency scores and filters on them
numeric vector
Doench 2014, Rational design of highly active sgRNAs for CRISPR-Cas9-mediated gene inactivation. Nature Biotechnology, doi: 10.1038/nbt.3026
Doench 2016, Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nature Biotechnology, doi: 10.1038/nbt.3437
Python module azimuth: github/MicrosoftResearch/azimuth
# Install azimuth #---------------- ## With reticulate # require(reticulate) # conda_create('azienv', c('python=2.7')) # use_condaenv('azienv') # py_install(c('azimuth', 'scikit-learn==0.17.1', 'biopython=='1.76'), # 'azienv', pip = TRUE) ## Directly # conda create --name azienv python=2.7 # conda activate azienv # pip install scikit-learn==0.17.1 # pip install biopython==1.76 # pip install azimuth # PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 targets <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) spacers <- find_primespacers(targets, bsgenome, ontargetmethod=NULL, offtargetmethod=NULL) spacers %<>% score_ontargets(bsgenome, 'Doench2014') # reticulate::use_condaenv('azienv') # reticulate::import('azimuth') # spacers %<>% score_ontargets(bsgenome, 'Doench2016') # TFBS example #------------- bedfile <- system.file('extdata/SRF.bed', package = 'multicrispr') bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 targets <- extend(bed_to_granges(bedfile, 'mm10')) spacers <- find_spacers(targets, bsgenome, ontargetmethod=NULL, offtargetmethod=NULL) spacers %<>% score_ontargets(bsgenome, 'Doench2014') # reticulate::use_condaenv('azienv') # reticulate::import('azimuth') # spacers %>% score_ontargets(bsgenome, 'Doench2016')# Install azimuth #---------------- ## With reticulate # require(reticulate) # conda_create('azienv', c('python=2.7')) # use_condaenv('azienv') # py_install(c('azimuth', 'scikit-learn==0.17.1', 'biopython=='1.76'), # 'azienv', pip = TRUE) ## Directly # conda create --name azienv python=2.7 # conda activate azienv # pip install scikit-learn==0.17.1 # pip install biopython==1.76 # pip install azimuth # PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 targets <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'), # ins bsgenome) spacers <- find_primespacers(targets, bsgenome, ontargetmethod=NULL, offtargetmethod=NULL) spacers %<>% score_ontargets(bsgenome, 'Doench2014') # reticulate::use_condaenv('azienv') # reticulate::import('azimuth') # spacers %<>% score_ontargets(bsgenome, 'Doench2016') # TFBS example #------------- bedfile <- system.file('extdata/SRF.bed', package = 'multicrispr') bsgenome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10 targets <- extend(bed_to_granges(bedfile, 'mm10')) spacers <- find_spacers(targets, bsgenome, ontargetmethod=NULL, offtargetmethod=NULL) spacers %<>% score_ontargets(bsgenome, 'Doench2014') # reticulate::use_condaenv('azienv') # reticulate::import('azimuth') # spacers %>% score_ontargets(bsgenome, 'Doench2016')
Returns extensions, upstream flanks, or downstream flanks
up_flank( gr, start = -200, end = -1, strandaware = TRUE, bsgenome = NULL, verbose = FALSE, plot = FALSE, linetype_var = "set", ... ) down_flank( gr, start = 1, end = 200, strandaware = TRUE, bsgenome = NULL, verbose = FALSE, plot = FALSE, linetype_var = "set", ... ) extend( gr, start = -22, end = 22, strandaware = TRUE, bsgenome = NULL, verbose = FALSE, plot = FALSE, linetype_var = "set", ... )up_flank( gr, start = -200, end = -1, strandaware = TRUE, bsgenome = NULL, verbose = FALSE, plot = FALSE, linetype_var = "set", ... ) down_flank( gr, start = 1, end = 200, strandaware = TRUE, bsgenome = NULL, verbose = FALSE, plot = FALSE, linetype_var = "set", ... ) extend( gr, start = -22, end = 22, strandaware = TRUE, bsgenome = NULL, verbose = FALSE, plot = FALSE, linetype_var = "set", ... )
gr |
|
start |
number or vector (same length as gr): start definition, relative to gr start (up_flank, extend) or gr end (down_flank). |
end |
number or vector (same length as gr): end definition, relative to gr start (up_flank) or gr end (extend, down_flank). |
strandaware |
TRUE (default) or FALSE: consider strand information? |
bsgenome |
NULL (default) or |
verbose |
TRUE or FALSE (default) |
plot |
TRUE or FALSE (default) |
linetype_var |
string: gr var mapped to linetype |
... |
passed to |
up_flank returns upstream flanks, in relation to start(gr).
down_flank returns downstream flanks, in relation to end(gr).
extend returns extensions, in relation to start(gr) and end(gr)
# PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'),# ins bsgenome = bsgenome) gr %>% up_flank( -22, -1, plot=TRUE) gr %>% up_flank( c(-10,-20,-30,-40), -1, plot=TRUE) gr %>% up_flank( -22, -1, plot=TRUE, strandaware=FALSE) gr %>% down_flank(+1, +22, plot=TRUE) gr %>% down_flank(+1, c(10, 20, 30, 40), plot=TRUE) gr %>% down_flank(+1, +22, plot=TRUE, strandaware=FALSE) gr %>% extend( -10, +20, plot=TRUE) gr %>% extend( -10, +20, plot=TRUE, strandaware=FALSE) # TFBS example #------------- bedfile <- system.file('extdata/SRF.bed', package='multicrispr') gr <- bed_to_granges(bedfile, genome = 'mm10') gr %>% extend(plot = TRUE) gr %>% up_flank(plot = TRUE) gr %>% down_flank(plot = TRUE)# PE example #----------- require(magrittr) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c(PRNP = 'chr20:4699600:+', # snp HBB = 'chr11:5227002:-', # snp HEXA = 'chr15:72346580-72346583:-', # del CFTR = 'chr7:117559593-117559595:+'),# ins bsgenome = bsgenome) gr %>% up_flank( -22, -1, plot=TRUE) gr %>% up_flank( c(-10,-20,-30,-40), -1, plot=TRUE) gr %>% up_flank( -22, -1, plot=TRUE, strandaware=FALSE) gr %>% down_flank(+1, +22, plot=TRUE) gr %>% down_flank(+1, c(10, 20, 30, 40), plot=TRUE) gr %>% down_flank(+1, +22, plot=TRUE, strandaware=FALSE) gr %>% extend( -10, +20, plot=TRUE) gr %>% extend( -10, +20, plot=TRUE, strandaware=FALSE) # TFBS example #------------- bedfile <- system.file('extdata/SRF.bed', package='multicrispr') gr <- bed_to_granges(bedfile, genome = 'mm10') gr %>% extend(plot = TRUE) gr %>% up_flank(plot = TRUE) gr %>% down_flank(plot = TRUE)
Write GRanges to file
write_ranges(gr, file, verbose = TRUE) read_ranges(file, bsgenome)write_ranges(gr, file, verbose = TRUE) read_ranges(file, bsgenome)
gr |
|
file |
file |
verbose |
TRUE (default) or FALSE |
bsgenome |
GRanges-class for read_ranges
# Find PE spacers for 4 clinically relevant loci (Anzalone et al, 2019) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c( PRNP = 'chr20:4699600:+', # snp: prion disease HBB = 'chr11:5227002:-', # snp: sickle cell anemia HEXA = 'chr15:72346580-72346583:-', # del: tay sachs disease CFTR = 'chr7:117559593-117559595:+'), # ins: cystic fibrosis bsgenome) file <- file.path(tempdir(), 'gr.txt') write_ranges(gr, file) read_ranges(file, bsgenome)# Find PE spacers for 4 clinically relevant loci (Anzalone et al, 2019) bsgenome <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38 gr <- char_to_granges(c( PRNP = 'chr20:4699600:+', # snp: prion disease HBB = 'chr11:5227002:-', # snp: sickle cell anemia HEXA = 'chr15:72346580-72346583:-', # del: tay sachs disease CFTR = 'chr7:117559593-117559595:+'), # ins: cystic fibrosis bsgenome) file <- file.path(tempdir(), 'gr.txt') write_ranges(gr, file) read_ranges(file, bsgenome)