estimatePatterns {MPFE} | R Documentation |
Estimate distribution of methylation patterns from a table of counts from a bisulphite sequencing experiment given a non-conversion rate and a sequencing error rate.
estimatePatterns(patternCounts, epsilon=0, eta=0, column=NULL, fast=TRUE, steps=20000, reltol=1e-12)
patternCounts |
data frame with methylation patterns in first column and pattern counts in subsequent columns. |
epsilon |
non-converson rate, a value between 0 and 1. |
eta |
error rate, either a vector of numbers between 0 and 1 of length equal to the number of CpG sites or a single value between 0 and 1 for a single error rate across all sites. |
column |
a vector that specifies the indices of the columns of ‘patternCounts’ to process. Its entries are integer values from 1 to the number of pattern counts columns in ‘patternCounts’. If NULL, defaults to all columns. |
fast |
logical, if TRUE, fast version implemented (default). |
steps |
number of steps for the optimiser, passed to |
reltol |
relative tolerance for the optimiser, passed to |
The function returns a list of data frames.
The data frames contain the following columns:
pattern |
the list of input patterns (factor) |
coverage |
the number of reads for each pattern (integer) |
observedDistribution |
the observed frequencies of each pattern (numeric) |
estimatedDistribution |
the estimated frequencies (numeric) |
spurious |
indicates whether the patterns are real or spurious (logical) |
Peijie Lin, Sylvain Foret, Conrad Burden
data(patternsExample) estimatePatterns(patternsExample, epsilon=0.02, eta=0.01) estimatePatterns(patternsExample, epsilon=0.01, eta=c(0.015, 0.01, 0.01, 0.01, 0.015), column=2)