Version 6 (modified by t.pham@…, 9 years ago) (diff) |
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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.