README.md

In Jon-Simpson/miRmapper: A package for the S4 miRmapper class

miRMapper - Impact Analysis of Micro RNAs

After a sequencing experiment, it may be useful to understand how the regulation of certain genes is affected by the presence of miRNAs. miRMapper is an R package with the goal of providing this understanding by performing an analysis of the predicted impact micro RNAs have on gene expression. The user must supply a csv file containing the predicted target genes from the experiment for each miRNA of interest. miRNA target predictions for humans, mice, and rats can be obtained through the R package multiMiR. For information about multiMiR and miRNA-target interactions, please go to the multiMiR site.

There is also an optional input where the user can supply a csv containing the entire list of genes from the sequencing experiment. Output files for the analysis include metrics outlining the predicted impacts of each miRNA, a network of the interactions, and a dendrogram and identity heatmap for depicting miRNA similarities.

Getting Started

Install the R package with the following commands.

install.packages("devtools")
devtools::install_github("MUSC-CGM/miRMapper")
library(miRMapper)

All inputs for the program should be located in the same directory. It is in this directory that a new folder call "/miRMapper-Output" will be created for all of the output files.

The main input file, "interaction.csv", is required to be in a .csv file format. The file must contain 2 columns, with no header, where each row contains a predicted interaction. Example:

dre-miR-499,saa
dre-miR-499,upp2
dre-miR-499,ppdpfb

The optional second input, "DEgenes.csv", will also need to be a csv file. This file should have 1 column, with no header, that contains the complete set of genes from the sequencing experiment, or any particular set of genes of interest. This file is only used to compute the percentage of miRNA impact across an entire transcriptome. An example of this file is:

lmo2
gng12a
gstt1b
gstt1b
gng2
rpl36a
ebpl
asah1b

Both files should be loaded with the following (making sure that header=FALSE):

de_genes <- read.csv("/path/to/miRmapperFolder/de_genes.csv", header=FALSE)

Example

To produce all outputs, use the the runAnalysis() method:

miRmap <- miRmapper::miRmapper(interactions=interact, DEgenes=de_genes)
miRmapper::runAnalysis(miRmap)

Jon-Simpson/miRmapper documentation built on June 9, 2019, 12:42 a.m.