vocal {ComICS} | R Documentation |
Variation in Cell Abundance Loci
Description
Probing immune system genetics via gene expression. VoCAL is a deconvolution-based method that utilizes transcriptome data to infer the quantities of immune-cell types, and then uses these quantitative traits to uncover the underlying DNA loci (iQTLs) assuming homozygosity (such as in the case of recombinent inbred strains).
Usage
vocal(...,reference_data,expression_data,genotyping_data,normalize_data,
T.i=5,T.e=10,eqtl_association_scores=NULL)
Arguments
... |
one or more data frames of one column, each one represents a preselected marker set that likely discriminate well between the immune-cell types given in the reference data. The number of data frames defines the number of association scores that would be combined to generate the final iQTL association score. |
reference_data |
a data frame representing immune cell expression profiles.
Each row represents an expression of a gene, and each column represents a
different immune cell type. |
expression_data |
a data frame representing RNA-seq or microarray
gene-expression profiles of a given complex tissue across a population of
genetically distinct (genotyped) individuals. Each row represents an
expression of a gene, and each column represents a genetically distinct
individual. |
genotyping_data |
a data frame where each row represents a different
locus, and each column represents a genetically distinct individual.
The genotype should be taken from homozygous individuals only.
Where the genotype is unknown |
normalize_data |
normalization type. The data will be normalized by either:
(1) "All" - subtraction of the mean expression of all strains;
(2) "None" - data is already normalized, do nothing;
(3) name of individual included in |
T.i |
numerical. significant iQTL association score |
T.e |
numerical. significant eQTL association score |
eqtl_association_scores |
(optional) a data frame where each entry
represents an association score for a gene given the genotype of all the
individuals that appear in the expression_data data frame, in a specific locus.
This eQTL analysis should be peformed over the normalized expression_data.
|
Value
a list of two martices
final_association_score |
a matrix that contains the output iQTL association
score after applying the iterative filteration procedure. Each row represents the genome
wide-association result for a specific immune trait over a range of DNA loci.
|
marker_info |
the names of all the markers removed from the different marker sets provided |
References
Steuerman Y and Gat-Viks I. Exploiting Gene-Expression Deconvolution to Probe the Genetics of the Immune System (2015), Submitted.
Examples
data(commons)
data(vocalEx)
## Not run:
results <- vocal(DCQ_mar, reference_data=immgen_dat, expression_data=lung_dat,
genotyping_data=gBXD, normalize_data="B6", eqtl_association_scores=eQTL_res)
## End(Not run)