ASErawfit: Single Study Based Statistics for Allele Specific Events

In iASeq: iASeq: integrating multiple sequencing datasets for detecting allele-specific events

Description

This function produces standard statistics for allele-specific events based on a single RNAseq or ChIPseq study. It first pools replicates within a given study to sum the read counts for the reference allele and the non-reference allele. Then based on the pooled read counts, it calculates naive z statistic, naive Bayes statistic and empirical Bayes statistic.

Usage

ASErawfit(exprs,studyid,repid,refid)

Arguments

exprs	A matrix, each row of the matrix corresponds to a heterozygotic SNP and each column of the matrix corresponds to the reads count for either the reference allele or non-reference allele in a replicate of a study.
studyid	The group label for each column of exprs matrix. all columns in the same study have the same studyid.
repid	The sample label for each column of exprs matrix. The two columns within the same sample, one for reference allele and the other for non-reference allele, have the same repid. In other words, repid discriminates the different replicates within the same study.
refid	The reference allele label for each column of exprs matrix. Please code 0 for reference allele columns and 1 for non-reference allele columns to make the interpretation of over expressed (or bound) to be skewing to the reference allele. Otherwise, just interpret the other way round.

Details

One should indicate the studyid, repid and refid for each column clearly.

Value

z	Naive z statistic. A matrix, each row of the matrix corresponds to a heteroygpotic SNP of the input matrix ('exprs') and each column corresponds to a study.
b	Naive Bayes statistic. A matrix, each row of the matrix corresponds to a heteroygpotic SNP of the input matrix ('exprs') and each column corresponds to a study.
B	Empirical Bayes statistic. A matrix, each row of the matrix corresponds to a heteroygpotic SNP of the input matrix ('exprs') and each column corresponds to a study.
c0d	α parameter for the null beta prior distribution for pooled counts for each study. A vector whose length equals to the number of studies.
d0d	β parameter for the null beta prior distribution for pooled counts for each study. A vector whose length equals to the number of studies.
p0d	Mean of the null beta prior distribution for pooled counts for each study. A vector whose length equals to the number of studies.
p0dz	Raw mean of the reference allele proportion. A vector whose length equals to the number of studies.

Author(s)

Yingying Wei

References

Yingying Wei, Xia Li, Qianfei Wang, Hongkai Ji (2012) iASeq: integrating multiple ChIP-seq datasets for detecting allele-specific binding.

See Also

sampleASE

Examples

data(sampleASE)
raw.fitted<-ASErawfit(sampleASE_exprs,sampleASE_studyid,sampleASE_repid,sampleASE_refid)

iASeq documentation built on Nov. 8, 2020, 5:36 p.m.