Ibb Manual

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Package ‘ibb’
Title The (inverted) beta-binomial test for count data
Version 12.12.12
Date 2012-12-12
Author Thang V. Pham
Maintainer Thang V. Pham 
Description 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).
License All rights reserved by the author. This software package is provided for research purposes in a
non-commercial environment. Please do not redistribute.

R topics documented:
bb.test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
ibb.test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Index

bb.test

1
2
4

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 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.

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.

1

Author(s)
Thang V. 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
# example proteomics spectral count data
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)
######################
# comparing 3 groups: columns c(1, 2, 3), c(4, 5, 6), and c(7, 8) of a data file
d <- read.delim("example-3groups.txt", header = TRUE)
# compare 3 groups, using all available CPU cores
out <- bb.test(d[, 1:8], colSums(d[, 1:8]), c(rep("a", 3), rep("b", 3), rep("c", 2)),
n.threads = 0)
# write result to file
write.table(cbind(d, out$p.value), file = "example-3groups-out.txt",
sep = "\t", row.names = FALSE)

ibb.test

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.

2

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(s)
Thang V. Pham 

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

Examples
# example RNA-seq read count data
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)
######################
# columns c(1, 2, 3) are respectively paired with columns c(4, 5, 6)
d <- read.delim("example-paired.txt", header = TRUE)
# perform a paired test for all rows, using all but one CPU cores
out <- ibb.test(d[, 1:6], colSums(d[, 1:6]), c(rep("pre", 3), rep("post", 3)),
n.threads = -1)
# write result to file
write.table(cbind(d, out$fc, out$p.value), file = "example-paired-out.txt",
sep = "\t", row.names = FALSE)

3

Index
∗Topic beta-binomial
bb.test, 1
∗Topic count data
bb.test, 1
ibb.test, 2
∗Topic independent sample test
bb.test, 1
∗Topic inverted beta-binomial test
ibb.test, 2
∗Topic paired sample test
ibb.test, 2
∗Topic significance analysis
bb.test, 1
ibb.test, 2
bb.test, 1
ibb.test, 2

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