visualise: Visualise

In Oshlack/Baller: Classification of RNA-seq data from ALL samples

Description

Produces a multidimensional scaling (MDS) plot for all of the samples in your fpkm table and colours them based on the classification in table classed.

Usage

visualise(FPKM,classed)

Arguments

classed	A data frame where each row represents the probability for given a sample to fit each of the four classes as well as its overall classification based on the chosen thresholds.
FPKM	A matrix of fragments/reads per kilobase per million. Rows are genes and columns are samples.

Value

Produces a multidimensional scaling (MDS) plot for all of the samples in your fpkm table and colours them based on the classification in table classed.

Examples

cf <- system.file("data","test_data.txt",package="AllSorts") #Get path to raw text file (a tsv)
counts <- read.table(file=cf,sep=' ',stringsAsFactors = FALSE,header=TRUE)
FPKM <- streamline(counts[,c(1:6)],counts$Gene_Length)
thresh <- c(0.2,0.2,0.8,0.9)
classed <- classify(FPKM,thresh)
visualise(FPKM,classed)

Oshlack/Baller documentation built on Jan. 23, 2021, 6:50 p.m.