Description Usage Arguments Details Value Author(s) References See Also Examples
The filter consists of a biological filter and a statistical variance filter and aims to remove obvious contaminants in AP-MS data.
1 2 |
mat |
matrix of spectral counts, proteins in rows and samples in columns. |
baittab |
a data.frame. The baittable as required for SAINT, classifying control and bait samples. |
func |
method to use for filtering, must be one of |
var.cutoff |
percentile (between 0 and 1) or |
limit |
minimal number of expected true interaction proteins in the data. |
If filter.method="noVar"
, only the biological filter is conducted.
The biological and statistical filter are applied, if filter.method="IQR"
, here the variance is calculated by the inter-quartile-range, or if filter.method="overallVar"
, here the variance is calculated across all samples.
The var.cutoff
defines the fraction of proteins with the lowest overall variance, which are considered as contaminants and are removed.
var.cutoff=NA
refers to a cutoff defined by the mean of the shortest intervall containing 50% of the data (default). Alternatively, a quantile can be set as cutoff, e.g. a cutoff of 0.5 filters 50% of the data showing the smallest overall variance or IQR.
The parameter limit
assures, that filtering results in a number of proteins above the number of expected true interaction proteins.
It is recommended to set the parameters var.cutoff
and limit
according to biological knowledge, if available.
filtered matrix of spectral counts
Martina Fischer
Bourgon R, Gentleman R, Huber W. Independent filtering increases detection power for high-throughput experiments. Proceedings of the National Academy of Sciences 2010.
1 2 3 4 5 6 7 8 9 10 | #input data
intfile <- system.file("extdata", "inttable.txt", package="apmsWAPP")
counts <- int2mat(read.table(intfile))
baitfile <- system.file("extdata", "baittab.txt", package="apmsWAPP")
baittab <- read.table(baitfile)
dim(counts)
# Filtering:
counts.filtered <- varFilter(counts, baittab, func = "overallVar",
var.cutoff = 0.3, limit = 0)
dim(counts.filtered)
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