kpmt (version 0.1.0)

kpmt: Known Population Median Test

Description

Performs the known population median test.

Usage

kpmt(pop, obs = NULL, med = NULL, size = NULL, tail = "two-sided",
  verbose = FALSE)

Arguments

pop

[data frame, matrix, vector] numeric values for the whole population. If a data frame or matrix is given, it should have format:

• rownames = population member names (e.g. gene names)

• colnames = features to test (e.g. relative codon usage, UTR length, MFE, etc.)

For a data frame or matrix, the test will be performed on each column, separately. If a named vector is given, it should have format:

• names = population member names.

• values = numeric values of the feature.

obs

[character vector or named list of character vectors] a character vector of population member names, or a named list of character vectors of population member names.

1. If obs is a list, then each list element name should correspond to a feature name of pop.

2. If obs is a vector, then it is considered to be the same sample for each population feature.

3. if size = NULL, then obs is considered to be a sample of population member names

4. if size is non-NULL, then obs is considered to be the observed median values per column of pop. (length obs must be equal to number of features in pop)

med

[number or vector] pre-computed minimal medians of pop.

size

[integer] size of the set which generated the observed median. If obs is a sample, i.e. contains population member names, then size must be NULL.

tail

["two-sided", "lower", "upper"] if NULL, then the minimum of lower and upper will be reported.

verbose

display extra messages for tracking execution.

Value

data frame with columns:

• "name" a column from pop

• "median.sample" min median of the sample

• "median.all" min median of the whole population

• "median.background" min median of the non-sampled members.

• "logp" log of p.value if sample median is different from all

• "p.value" p.value if sample median is different from all

• "FDR" only if > 30 features, i.e columns of pop

each row is a different population feature, i.e. column of pop.

Examples

# NOT RUN {
data(genefeat)
data(GO0007186)
res  <-  kpmt( pop = genefeat , obs = GO0007186 )
# }