Description Usage Arguments Value Author(s) Examples
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.
1 2 3 4 5 6 7 | 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
1 2 3 4 5 6 7 8 | 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)
|
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