fold_change {BloodGen3Module} | R Documentation |
A function to calculate fold-change between group comparison; "Test_group" vs "Ref_group"
fold_change( df_raw = df_raw, sample_info = sample_info, Group_column = Group_column, Test_group = Test_group, Ref_group = Ref_group )
df_raw |
Matrix of normalized expression data (not Log2 transformed). Genes should be in rows and Sample ID in columns. Row names are required to be valid Gene Symbols |
sample_info |
A dataframe with sample annotation. Sample_info dataframe requires two columns: 1) a column specifying Sample ID (exactly matching Sample ID of data.matrix) and 2) a column specifying group names |
Group_column |
Character vector identical to the column name from sample_info dataframe that specifies group annotation used for the analysis |
Test_group |
Character vector specifying values within the group column (Group_column) that will be used as Test group (samples considered as cases or “intervention” group). |
Ref_group |
Character vector specifying value within the group column (Group_column) that will be used as Reference group |
A matrix of the fold change comparison between "Test_group" vs ""Ref_group"
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"]] data_matrix = assay(GSE13015) sample_ann = data.frame(colData(GSE13015)) FCgroup = fold_change(df_raw = data_matrix[c(1:5),], sample_info = sample_ann, Group_column = "Group_test", Test_group="Sepsis", Ref_group="Control")