README.md

In Priyadarshini-Rai/SelfE: Feature Selection Model

SelfE: Gene Selection via Self-Expression for Single-Cell Data

Priyadarshini Rai, Debarka Sengupta, Angshul Majumdar

Description

The first input parameter to SelfE.R is a pre-processed single-cell data matrix, with rows representing cells/samples and columns representing genes/features. The second input parameter 'k' denotes the number of feature(s) user wants to select from the available features. SelfE returns an array of index values corresponding to the selected genes and the length of the array is equal to input parameter 'k'.

Dependencies

Packages: pracma, pinv.

Excecution

To run the SelfE model use the following the commands:

source(SelfE.R)

# Loading data
Processed_Data = read.table('Single Cell Dataset/PBMC_Data_1019Samples.csv', sep = ',', header = FALSE)

# Number of features user wants to select
Number_of_Features = 50

# Calling SelfE
GeneIDs = SelfE(Processed_Data, Number_of_Features)

# Selecting genes from the data
SelfE_Data = Processed_Data[, GeneIDs]

Priyadarshini-Rai/SelfE documentation built on Dec. 12, 2019, 1:20 a.m.