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Welcome to project ibb


This R package contains two functions. The beta-binomial test (bb.test) can be used for significance analysis of independent samples (two or more groups). The inverted beta-binomial test (ibb.test) can be used for paired sample testing (e.g. pre-treatment and post-treatment data).


All rights reserved by the author. This software package is provided for research purposes in a non-commercial environment. Please do not redistribute.


The beta-binomial test


Description

Performs the beta-binomial test for count data.

Usage

bb.test(x, tx, group, alternative = c("two.sided", "less", "greater"), n.threads = 1)

Arguments

x: A vector or matrix of counts. When x a matrix, the test is performed row by row.

tx: A vector or matrix of the total sample counts. When tx is a matrix, the number of rows must be equal to the number of rows of x.

group: A vector of group indicators.

alternative: A character string specifying the alternative hypothesis: "two.sided" (default), "greater" or "less".

n.threads: The number of threads to be used.

Details

When n.threads is 0, the maximal number of CPU cores is used. When n.threads is -1, one CPU core less than the maximum is used, and so on.

Value

A list with a single component is returned:

p.value: The p-value of the test.

Author

Thang V. Pham <t.pham@…>

References

Pham TV, Piersma SR, Warmoes M, Jimenez CR (2010) On the beta binomial model for analysis of spectral count data in label-free tandem mass spectrometry-based proteomics. Bioinformatics, 26(3):363-369.

Examples

x <- c(1, 5, 1, 10, 9, 11, 2, 8)
tx <- c(19609, 19053, 19235, 19374, 18868, 19018, 18844, 19271)
group <- c(rep("cancer", 3), rep("normal", 5))
bb.test(x, tx, group)



The inverted beta-binomial test


Description

Performs the inverted beta-binomial test for paired count data.

Usage

ibb.test(x, tx, group, alternative = c("two.sided", "less", "greater"), n.threads = 1)

Arguments

x: A vector or matrix of counts. When x is a matrix, the test is performed row by row.

tx: A vector or matrix of the total sample counts. When tx is a matrix, the number of rows must be equal to the number of rows of x.

group: A vector of group indicators. There should be two groups of equal size. The samples are matched by the order of appearance in each group.

alternative: A character string specifying the alternative hypothesis: "two.sided" (default), "greater" or "less".

n.threads: The number of threads to be used.

Details

This test is designed for paired count data, for example data acquired before and after treatment.

Value

A list of values is returned:

p.value: The p-value of the test.

fc: An estimation of the common fold change.

Author

Thang V. Pham <t.pham@…>

Reference

Pham TV, Jimenez CR (2012) An accurate paired sample test for count data. Bioinformatics, 28(18):i596-i602.

Examples

x <- c(33, 32, 86, 51, 52, 149)
tx <- c(7742608, 15581382, 20933491, 7126839, 13842297, 14760103)
group <- c(rep("cancer", 3), rep("normal", 3))
ibb.test(x, tx, group)


Other NBIC software projects


All active NBIC software projects can be accessed from the project index.

Last modified 4 years ago Last modified on Dec 11, 2012, 1:51:30 PM