MOTIFBREAKR | R Documentation |
motifbreakR is a package to predict how much a SNP will disrupt
a transcription factor binding motif (if it falls within one).
Notes:
BSgenomeUsers must manually run library(BSgenome)
before running any motifbreakR functions
to successfully use this tool.
threshold=
If filterp=TRUE
, this argument indicates the p-value threshold.
If filterp=FALSE
, this argument instead indicates the pct threshold.
MOTIFBREAKR(
rsid_list,
results_dir = file.path(tempdir(), "results"),
pwmList = NULL,
pwmList_max = NULL,
genome_build = NULL,
organism = "Hsapiens",
threshold = 0.85,
show.neutral = FALSE,
method = "default",
calculate_pvals = TRUE,
force_new = FALSE,
background = c(A = 0.25, C = 0.25, G = 0.25, T = 0.25),
granularity = NULL,
nThread = 1,
verbose = TRUE
)
rsid_list |
RSIDs of SNPs to test for motif disruption between the reference and alternative alleles.. |
results_dir |
Directory where results should be saved
as a file named:
<results_dir>/_genome_wide/motifbreakR/motifbreakR_results.rds.
If |
pwmList |
An object of class |
pwmList_max |
Limit the maximum number of PWM datasets tested
(e.g. |
genome_build |
Genome build to use. |
organism |
Only include datasets in the |
threshold |
Numeric; the maximum p-value for a match to be called or a minimum score threshold |
show.neutral |
Logical; include neutral changes in the output |
method |
Character; one of |
calculate_pvals |
Calculate p-values for all SNPs tested. WARNING: May take a long time if many SNPs and/or PWM are selected. |
force_new |
If results of the same name already exist,
overwrite them with new analyses ( |
background |
Numeric Vector; the background probabilities of the nucleotides |
granularity |
Numeric Vector; the granularity to which to round the PWM,
larger values compromise full accuracy for speed of calculation. A value of
|
nThread |
Number of threads to parallelize analyses across. |
verbose |
Print messages. |
Motif disruption predictions in GRanges format.
Other motifbreakR:
MOTIFBREAKR_filter_by_metadata()
,
MOTIFBREAKR_summarize()
library(BSgenome) ## <-- IMPORTANT!
#### Example fine-mapping results ####
merged_DT <- echodata::get_Nalls2019_merged()
#### Run motif analyses ####
mb_res <- MOTIFBREAKR(rsid_list = c("rs11175620"),
# limit the number of datasets tested
# for demonstration purposes only
pwmList_max = 4,
calculate_pvals = FALSE)
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