Description Usage Arguments Author(s) See Also Examples
Functions for calculating and adjusting ratios and sample p-values. Usually, these are called by proteinRatios or peptideRatios.
1 2 3 4 5 6 7 | calculate.ratio.pvalue(lratio, variance, ratiodistr = NULL)
calculate.sample.pvalue(lratio, ratiodistr)
calculate.mult.sample.pvalue(lratio, ratiodistr, strict.pval,
lower.tail, n.possible.val, n.observed.val)
adjust.ratio.pvalue(quant.tbl, p.adjust, sign.level, globally = FALSE)
|
lratio |
log 10 protein or peptide ratios. |
ratiodistr |
Fitted ratio distribution/ |
variance |
Variance of lratios. |
strict.pval |
If FALSE, missing ratios are ignored. If TRUE, missing ratios are penalized by giving them a sample.pval of 0.5. |
lower.tail |
lower.tail of distribution? |
n.possible.val |
Number of possible ratios. |
n.observed.val |
Number of observed ratios. |
quant.tbl |
Quantification table (from proteinRatios or peptideRatios). |
p.adjust |
p-value adjustment method (see ?p.adjust). |
sign.level |
Ratio significance level. |
globally |
Whether the p-values should be adjusted over all conditions, or individually in each condition. |
Florian P. Breitwieser
1 2 3 4 5 6 7 8 9 10 11 12 | lratio <- c(-1,-1,seq(from=-1,to=1,by=.25),1,1)
variance <- c(0,1,rep(0.1,9),0,1)
ratiodistr.precise <- new("Norm",mean=0,sd=.25)
ratiodistr.wide <- new("Norm",mean=0,sd=.5)
# ratio p-value is impacted only by the variance
# sample p-value captures whether the ratio distribution is narrow ('precise')
# or wide
data.frame(lratio, variance,
ratio.pvalue=calculate.ratio.pvalue(lratio, variance),
sample.pvalue.precise=calculate.sample.pvalue(lratio,ratiodistr.precise),
sample.pvalue.wide=calculate.sample.pvalue(lratio,ratiodistr.wide))
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