hbadeals: Hierarchical Bayesian Analysis of Differential Expression and...

In TheJacksonLaboratory/HBA-DEALS: Hierarchical Bayesian Analysis of Differential Expression and ALternative SPlicing (HBA-DEALS)

Hierarchical Bayesian Analysis of Differential Expression and ALternative SPlicing (HBA-DEALS)

Description

The function determines differential expression and transcript proportions between two experimental conditions. It takes as input a table that contains the gene names in its first column, the transcript names in its second column, and the corresponding transcript counts under every sample in the rest of its columns. In addition, it takes as input an ordered numeric vector of 1's and 2's, where 1 indicates that the corresponding sample belongs to the first experimental condition and 2 to the second. The function returns a table that provides 1-probability values for differential expression of each gene, and either differential splicing for the gene or differential proportion for each transcript.

Usage

hbadeals(countsData,labels,n.cores,isoform.level,mcmc.iter=3000,mcmc.warmup=4000,hierarchy='auto',lib.size=NULL,mtc=FALSE)

Arguments

countsData	A table of gene names, transcript names and transcript counts in each sample. At least two transcripts must correspond to each gene.
labels	An ordered vector of 1's and 2's. Its length is ncol(countsdata)-2. Each entry indicates whether the corresponding sample/column of countsData belongs to the first experimental condition or the second.
n.cores	The number of cores to use in the calculation. It is recommended to dedicate as many cores as possible.
isoform.level	Should 1-probability of differential proportion for each transcript be returned. FALSE by deafult, which returns 1-probability of differential splicing for each gene.
mcmc.iter	The number of iterations of the MCMC algorithm after warmup.
mcmc.warmup	The number of warmup iterations of the MCMC algorithm.
hierarchy	Determines whether a hierarchical model will be used (hierarchy='yes'), a flat one (hierarchy='no') or will the decision will be made automatically (hierarchy='auto')
lib.size	A numeric vector containing total library sizes for each sample. If not provided, the default is columnwise count totals.
mtc	A logical argument (default FALSE) that indicates whether the output probabilities should be corrected for multiple comparisons.

Value

The table returned by this function contains 4 columns. The first column is the gene name, the second is the transcript name, the third is the fold change, and the fourth is 1-probability of differential expression or proportion(splicing). Entries that refer to expression have 'Expression' in their second column. If isoform.level is FALSE, entries that refer to differential splicing of the gene will have 'Splicing' in their second column entry. The fold change for expression is given as log2 fold change, and for splicing as fold change.

Author(s)

Guy Karlebach, Peter N Robinson

References

Karlebach, Guy and Hansen, Peter and Veiga, Diogo Ft and Steinhaus, Robin and Danis, Daniel and Li, Sheng and Anczukow, Olga and Robinson, Peter N., "HBA-DEALS: accurate and simultaneous identification of differential expression and splicing using hierarchical Bayesian analysis", Genome biology, 2020

Examples

simulate(rseed=1,fc=3,equal = TRUE)
n.samples=4 #per condition
countsData=read.table('counts.txt',sep='\t',header=FALSE)
labels=c(rep(1,n.samples),rep(2,n.samples))
res=hbadeals(countsData,labels,mtc=TRUE)

TheJacksonLaboratory/HBA-DEALS documentation built on June 28, 2023, 10:32 a.m.