cosine.similarity.iterative {OmicsQC} | R Documentation |
This function takes quality.scores, trims it and fits it to the distribution given. It then iteratively tests the largest datapoint compared a null distribution of size no.simulations. If the largest datapoint has a significant p-value it tests the 2nd largest one and so on. The function supports the following distributions:
'weibull'
'norm'
'gamma'
'exp'
'lnorm'
'cauchy'
'logis'
cosine.similarity.iterative(
quality.scores,
no.simulations,
distribution = c("lnorm", "weibull", "norm", "gamma", "exp", "cauchy", "logis"),
trim.factor = 0.05,
alpha.significant = 0.05
)
quality.scores |
A dataframe with columns 'Sum' (of scores) and 'Sample', i.e. the output of accumulate.zscores |
no.simulations |
The number of datasets to simulate |
distribution |
A distribution to test, will default to 'lnorm' |
trim.factor |
What fraction of values of each to trim to get parameters without using extremes |
alpha.significant |
Alpha value for significance |
Results in the form of a named list
Number of nominated outliers
Outlier IDs, corresponding to Sample
column of quality.scores