BreastCancer: Gene expression and clinical data used to predict the...

In lsplsGlm: Classification using LS-PLS for Logistic Regression

Description

Genetic and clinical data about 78 primary breast cancers. BreastCancer is a list of two matrice (X and D) and one vector (Y).

Usage

data(BreastCancer)

Details

The object is composed of a list of two matrices: genetic data X of size 78x4348 and clinical data D of size 78x7. There is also a response variable Y of size 78x1. The clinical data contain information on 78 primary breast cancers (34 from patients who developed metastases within 5 years and 44 from patients who continue to be disease-free after a period of at least 5 years) which have been selected from patients who were lymph node negative and under 55 years of age at diagnosis.

Value

X	a data gene matrix (78x4348) giving the expression levels of 4348 genes for the 78 patients. Each row corresponds to a patient, each column to a gene.
D	a data matrix (78x7) of clinical data. Each row corresponds to a patient and each column to a clinical variable.
Y	a numeric vector of length 78 giving the presence of subclinical metastases (1 for presence, 0 otherwise).

Examples

# load dataset
data(BreastCancer)

# how many patients and how many genes ?
dim(BreastCancer$X)

# how many patients of class 0 and 1 respectively ?
sum(BreastCancer$Y==0)
sum(BreastCancer$Y==1)

Example output

[1]   78 4348
[1] 44
[1] 34

lsplsGlm documentation built on May 2, 2019, 12:36 p.m.