differExp_continuous: Find differential expression genes or miRNAs from given...

Description Usage Arguments Value See Also Examples

View source: R/differExp_continuous.R

Description

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.

Usage

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differExp_continuous(se, class, log2 = FALSE, p_value.cutoff = 0.05)

Arguments

se

SummarizedExperiment for input format.

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.

Value

data expression data in matrix format, with sample name in columns and gene symbol or miRNA name in rows.

See Also

lm for fitting linear models.

Examples

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## 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"
)

anamiR documentation built on Oct. 31, 2019, 8:55 a.m.