ImputeNormData: Filter, impute, and normalise data.

In miRLAB: Dry lab for exploring miRNA-mRNA relationships

Description

Remove the genes (rows) that have more than r% of missing data; use the impute package to fill in missing data, and finally normalise the data.

Usage

ImputeNormData(dataset, r)

Arguments

dataset	The input dataset in csv format. e.g. "EMT.csv"
r	The rate threshold to filter the records (genes). Genes with more than r% missing data will be removed.

Value

The processed dataset.

References

1. Hastie T, Tibshirani R, Narasimhan B and Chu G. impute: Imputation for microarray data. R package version 1.42.0.

2. Smyth, G.K. (2005). Limma: linear models for microarray data. In Bioinformatics and computational biology solutions using R and Bioconductor (pp. 397-420). Springer New York.

Examples

dataset=system.file("extdata", "ToyEMT.csv", package="miRLAB")
impdata=ImputeNormData(dataset, 0.1)

miRLAB documentation built on Nov. 8, 2020, 5:45 p.m.