OVESEGtest: OVESEG-test

Description Usage Arguments Details Value Examples

Description

This function performs OVESEG-test to assess significance of molecular markers.

Usage

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OVESEGtest(y, group, weights = NULL, alpha = "moderated",
  NumPerm = 999, seed = 111, detail.return = TRUE,
  BPPARAM = bpparam())

Arguments

y

a numeric matrix containing log-expression or logCPM (log2-counts per million) values. Data frame or SummarizedExperiment object will be internally coerced into a matrix. Rows correspond to probes and columns to samples. Missing values are not permitted.

group

categorical vector or factor giving group membership of columns of y. At least two categories need to be presented.

weights

optional numeric matrix containing prior weights for each spot.

alpha

parameter specifying within-group variance estimator to be used. 'moderated': empirical Bayes moderated variance estimator as used in eBayes. Numeric value: a constant value added to pooled variance estimator (α + σ). NULL: no estimator; all variances are set to be 1.

NumPerm

an integer specifying the number of permutation resamplings (default 999).

seed

an integer seed for the random number generator.

detail.return

a logical indicating whether more details about posterior probability estimation will be returned.

BPPARAM

a BiocParallelParam object indicating whether parallelization should be used for permutation resamplings. The default is bpparam().

Details

OVESEG-test is a statistically-principled method that can detect tissue/cell-specific marker genes among many subtypes. OVESEG-test statistics are designed to mathematically match the definition of molecular markers, and a novel permutation scheme are employed to estimate the corresponding distribution under null hypotheses where the expression patterns of non-markers can be highly complex.

Value

a list containing the following components:

pv.overall

a vector of p-values calculated by all permutations regardless of upregulated subtypes.

pv.oneside

a vector of subtype-specific p-values calculated specifically for the upregulated subtype of each probe.

pv.oneside.max

subtype-specific p-values when observed test statistic equal to zero.

pv.multiside

pv.oneside*K (K-time comparison correction) and truncated at 1.

W

a matrix of posterior probabilities for each component null hypothesis given an observed probe. Rows correspond to probes and columns to one hypothesis.

label

a vector of group labels.

groupOrder

a matrix with each row being group indexes ordered based on decreasing expression levels. Group indexes are positions in label.

F.p.value

a matrix with each column giving p-values corresponding to F-statistics on certain groups.

lfdr

a matrix with each column being local false discovery rates estimated based on one column of weighted F.p.value matrix.

fit

a MArrayLM fitted model object produced by lmFit.

F.p.value, lfdr and fit are returned only when detail.return is TRUE.

Examples

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data(RocheBT)
rtest <- OVESEGtest(RocheBT$y, RocheBT$group, NumPerm=99,
                    BPPARAM=BiocParallel::SerialParam())
## Not run: 
#parallel computing
rtest <- OVESEGtest(RocheBT$y, RocheBT$group, NumPerm=99,
                    BPPARAM=BiocParallel::SnowParam())

## End(Not run)

Lululuella/OVESEG documentation built on May 21, 2019, 2:28 a.m.