Individualcomparison {BloodGen3Module} | R Documentation |
The Individualcomparison function will perform individual sample comparison analysis in reference to a control sample or group of samples, with the results are expressed “at the module level” as percent of genes increased or decreased.
Individualcomparison( data.matrix, sample_info = NULL, FC = NULL, DIFF = NULL, Group_column = NULL, Ref_group = NULL, SummarizedExperiment = TRUE )
data.matrix |
Matrix of normalized expression data (not Log2 transformed).Row names are required to be valid Gene Symbols. Columns names are sample IDs or data.matrix can also be given a summarizedexperiment object and assigned data.matrix and sample_info accordingly from the object. |
sample_info |
A dataframe with sample annotation. |
FC |
Numeric value specifying the foldchange cut off that will be applied to define increase or decrease of a given transcript compared to the reference group |
DIFF |
Numeric value specifying the difference cut off that will be applied to define increase or decrease of a given transcript compared to the reference group |
Group_column |
Character vector identical to the column name from sample_info dataframe that specifies group annotation used for the analysis |
Ref_group |
Character vector specifying value within the group column that will be used as Reference group |
SummarizedExperiment |
Output data as the SummarizedExperiment class when SummarizedExperiment = TRUE |
Expression matrix and sample annotation file are required in order to perform this analysis.
The sample annotation file must be loaded using a specific name = "sample_info".
The names of the columns for the conditions used in the analysis must be specified
The default cutoff is set at FC =1.5 and DIFF =10
A matrix of the percentahe of module response at individual level and SummarizedExperiment object
Darawan Rinchai drinchai@gmail.com
## data could be downloaded from ExperimentHub("GSE13015") library(ExperimentHub) library(SummarizedExperiment) dat = ExperimentHub() res = query(dat , "GSE13015") GSE13015 = res[["EH5429"]] Individual_df = Individualcomparison(GSE13015, sample_info = NULL, FC = 1.5, DIFF = 10, Group_column = "Group_test", Ref_group = "Control")