update_eset.feature: Reassign featureData slot of ExpressionSet and Update feature...

In jyyulab/NetBID: Network-based Bayesian Inference of Drivers, version 2

Reassign featureData slot of ExpressionSet and Update feature information

Description

update_eset.feature reassigns the featureData slot of ExpressionSet object based on user's demand. It is mainly used for gene ID conversion.

Usage

update_eset.feature(
  use_eset = NULL,
  use_feature_info = NULL,
  from_feature = NULL,
  to_feature = NULL,
  merge_method = "median",
  distribute_method = "equal"
)

Arguments

use_eset	ExpressionSet class object.
use_feature_info	data.frame, a data frame contains feature information, it can be obtained by calling fData function.
from_feature	character, orginal ID. Must be one of the column names in use_feature_info and correctly characterize the use_eset's row names.
to_feature	character, target ID. Must be one of the column names in use_feature_info.
merge_method	character, the agglomeration method to be used for merging gene expression value. This should be one of, "median", "mean", "max" or "min". Default is "median".
distribute_method	character, the agglomeration method to be used for distributing the gene expression value. This should be one of, "mean" or "equal". Default is "equal".

Details

User can pass a conversion table to use_eset for the ID conversion. A conversion table can be obtained from the original featureDta slot (if one called the load.exp.GEO function and set getGPL==TRUE) or by running the get_IDtransfer function. The mapping between original ID and target ID can be summerised into 4 categories. 1) One-to-one, simply replaces the original ID with target ID; 2) Many-to-one, the expression value for the target ID will be merged from its original ID; 3) One-to-many, the expression value for the original ID will be distributed to the matched target IDs; 4) Many-to-many, apply part 3) first, then part 2).

Value

Return an ExressionSet object with updated feature information.

Examples

mat1 <- matrix(rnorm(10000),nrow=1000,ncol=10)
colnames(mat1) <- paste0('Sample',1:ncol(mat1))
rownames(mat1) <- paste0('Gene',1:nrow(mat1))
eset <- generate.eset(exp_mat=mat1)
test_transfer_table <- data.frame(
                       'Gene'=c('Gene1','Gene1','Gene2','Gene3','Gene4'),
                       'Transcript'=c('T11','T12','T2','T3','T3'))
new_eset <- update_eset.feature(use_eset=eset,
                                use_feature_info=test_transfer_table,
                                from_feature='Gene',
                                to_feature='Transcript',
                                merge_method='median',
                                distribute_method='equal'
                                )
print(Biobase::exprs(eset)[test_transfer_table$Gene,])
print(Biobase::exprs(new_eset))

jyyulab/NetBID documentation built on Dec. 23, 2024, 6:34 a.m.