deva_normalization {blacksheepr} | R Documentation

## Normalization of data to prepare for deva. Uses a Median of Ratio method followed by a log2 transformation.

### Description

Normalization of data to prepare for deva. Uses a Median of Ratio method followed by a log2 transformation.

### Usage

    deva_normalization(intable, method = "MoR-log")

### Arguments

`intable` | table with samples along the columns and features along the rows.
`method` | DEFAULT: "MoR-log" Method by which to normalize data in preparation for deva. Options are <"MoR-log", "MoR", "log">. Where "MoR" refers to the Median of ratio's. The "log" transformation is necessary to compress heavily skewed data and allow for proper detection. "MoR-log" as the default will perform MoR followed by a log2 transform.

### Value

A normalized table for input into deva

### Examples

    library(pasilla)
    pasCts <- system.file("extdata",
        "pasilla_gene_counts.tsv", package="pasilla")
    cts <- as.matrix(read.csv(pasCts,sep="\t",row.names="gene_id"))
    norm_cts <- deva_normalization(cts, method = "MoR-log")

[Package blacksheepr version 1.1.0 Index]