differExp_continuous {anamiR} | R Documentation |
This function will apply linear regression model to find differential expression genes or miRNAs with continuous phenotype data,and then filter the genes or miRNAs (rows) which have bigger p-value than cutoff.
differExp_continuous(se, class, log2 = FALSE, p_value.cutoff = 0.05)
se |
|
class |
string. Choose one features from all rows of phenotype data. |
log2 |
logical, if this data hasn't been log2 transformed yet, this one should be TRUE. Default is FALSE. |
p_value.cutoff |
an numeric value indicating a threshold of p-value for every genes or miRNAs (rows). Default is 0.05. |
data expression data in matrix format, with sample name in columns and gene symbol or miRNA name in rows.
lm
for fitting linear models.
## Use the internal dataset data("mirna", package = "anamiR", envir = environment()) data("pheno.mirna", package = "anamiR", envir = environment()) ## SummarizedExperiment class require(SummarizedExperiment) mirna_se <- SummarizedExperiment( assays = SimpleList(counts=mirna), colData = pheno.mirna) ## Finding differential miRNA from miRNA expression data with lm differExp_continuous( se = mirna_se, class = "Survival" )