| find_peaks | R Documentation | 
Find peaks in a set of LOD curves (output from scan1()
find_peaks(
  scan1_output,
  map,
  threshold = 3,
  peakdrop = Inf,
  drop = NULL,
  prob = NULL,
  thresholdX = NULL,
  peakdropX = NULL,
  dropX = NULL,
  probX = NULL,
  expand2markers = TRUE,
  sort_by = c("column", "pos", "lod"),
  cores = 1
)
| scan1_output | An object of class  | 
| map | A list of vectors of marker positions, as produced by
 | 
| threshold | Minimum LOD score for a peak (can be a vector with
separate thresholds for each lod score column in
 | 
| peakdrop | Amount that the LOD score must drop between peaks,
if multiple peaks are to be defined on a chromosome. (Can be a vector with
separate values for each lod score column in
 | 
| drop | If provided, LOD support intervals are included in the
results, and this indicates the amount to drop in the support
interval. (Can be a vector with
separate values for each lod score column in
 | 
| prob | If provided, Bayes credible intervals are included in the
results, and this indicates the nominal coverage.
(Can be a vector with
separate values for each lod score column in
 | 
| thresholdX | Separate threshold for the X chromosome; if
unspecified, the same threshold is used for both autosomes and the
X chromosome. (Like  | 
| peakdropX | Like  | 
| dropX | Amount to drop for LOD support intervals on the X
chromosome.  Ignored if  | 
| probX | Nominal coverage for Bayes intervals on the X
chromosome.  Ignored if  | 
| expand2markers | If TRUE (and if  | 
| sort_by | Indicates whether to sort the rows by lod column, genomic position, or LOD score. | 
| cores | Number of CPU cores to use, for parallel calculations.
(If  | 
For each lod score column on each chromosome, we return a
set of peaks defined as local maxima that exceed the specified
threshold, with the requirement that the LOD score must have
dropped by at least peakdrop below the lowest of any two
adjacent peaks.
At a given peak, if there are ties, with multiple positions jointly achieving the maximum LOD score, we take the average of these positions as the location of the peak.
A data frame with each row being a single peak on a single chromosome for a single LOD score column, and with columns
lodindex - lod column index
lodcolumn - lod column name
chr - chromosome ID
pos - peak position
lod - lod score at peak
If drop or prob is provided, the results will include
two additional columns: ci_lo and ci_hi, with the
endpoints of the LOD support intervals or Bayes credible wintervals.
scan1(), lod_int(), bayes_int()
# read data
iron <- read_cross2(system.file("extdata", "iron.zip", package="qtl2"))
# insert pseudomarkers into map
map <- insert_pseudomarkers(iron$gmap, step=1)
# calculate genotype probabilities
probs <- calc_genoprob(iron, map, error_prob=0.002)
# grab phenotypes and covariates; ensure that covariates have names attribute
pheno <- iron$pheno
covar <- match(iron$covar$sex, c("f", "m")) # make numeric
names(covar) <- rownames(iron$covar)
Xcovar <- get_x_covar(iron)
# perform genome scan
out <- scan1(probs, pheno, addcovar=covar, Xcovar=Xcovar)
# find just the highest peak on each chromosome
find_peaks(out, map, threshold=3)
# possibly multiple peaks per chromosome
find_peaks(out, map, threshold=3, peakdrop=1)
# possibly multiple peaks, also getting 1-LOD support intervals
find_peaks(out, map, threshold=3, peakdrop=1, drop=1)
# possibly multiple peaks, also getting 90% Bayes intervals
find_peaks(out, map, threshold=3, peakdrop=1, prob=0.9)
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