LONGOcmd: LONGO function

In BioHPC/LONGO: Long gene expression as a metric for neuronal identity

LONGO function

Description

This function allows the user to preset the variables and allows a faster analysis of data. Please use the shiny interface first to get an understanding of how this package analyzes data.

Usage

LONGOcmd(fileLocation, separator = ",", header = TRUE, commentChar = "!",
  species = "hsapiens_gene_ensembl", libraryType = "affy_primeview",
  multiProbes = "mean", windowSize = 200, stepSize = 40,
  windowStyle = "mean", filterData = TRUE, normalizeData = TRUE,
  controlColumn = 2)

Arguments

fileLocation	Address to the file to be analyzed
separator	Option to specify the separated value, default=","
header	Option to specify if there is a header in the file, default=TRUE
commentChar	Option to specify the commented character in the loaded file, default="!"
species	species name of the data based off the biomaRt database
libraryType	the gene identifier of the data based off the biomaRt database
multiProbes	Option to change the method for handling multiple probes going to the same gene, default=mean
windowSize	Option to alter the size of the windows to be created from the dataframe, default=200
stepSize	Option to alter the size of the steps used to create the windows, default=40
windowStyle	Option to alter the method used to create windows, default=mean
filterData	Option to filter data, default=TRUE
normalizeData	Option to normalize data, default=TRUE
controlColumn	column of the data used as a control for the statistical analysis

Value

Returns nothing

Examples

LONGOcmd(exampleRatData, species = "mmusculus_gene_ensembl",
libraryType = "affy_mouse430a_2")

LONGOcmd("~/data.csv")
LONGOcmd("~/data.csv", windowSize=100, stepSize=20)
LONGOcmd("~/data.csv", multiProbes="highest")

BioHPC/LONGO documentation built on Oct. 31, 2024, 4:43 a.m.