Package 'receptLoss'

Table of Nuclear Hormone Receptors (NHRs)

Description

This object contains a table of all known NHRs and was adapted from the 'guidetopharmacology' website (see references). It was joined with a bioMart table to include ensemble gene ids, which are commonly used gene symbols.

Usage

nhrs

Format

A tibble with 54 rows and 6 variables:

hgnc_symbol

the HUGO gene nomenclature committee (HGNC) symbol (letters and numbers, ex. THRB)

hgnc_id

the HUGO gene nomenclature committee (HGNC) symbol (a number, ex. 11799)

hgnc_name

the HUGO gene nomenclature committee (HGNC) gene name (ex. "Thyroid hormone receptor beta")

entrez_gene_id

the entrez gene id (a number, ex. 7068)

ensembl_gene_id

the ensembl gene id (ex. ENSG00000151090, always starts with ENSG)

synonyms

words or gene symbols in the literature that refer to the same gene

Source

http://www.guidetopharmacology.org/DATA/targets_and_families.csv

http://www.biomart.org/

---

Plot histogram of genes with expression loss

Description

This function allows you to plot histograms of tumor and adj normal data

Usage

plotReceptLoss(exprMatrNml, exprMatrTum, rldf, geneName, addToTitle = "", clrs)

Arguments

exprMatrNml	A matrix of expression values from normal tissue. Each row is a gene, and each column is a patient or sample. Genes should be in same order as exprMatrTum.
exprMatrTum	A matrix of expression values from tumor tissue. Each row is a gene, and each column is a patient or sample. Genes should be in same order as exprMatrNml.
rldf	The dataframe output from running the receptLoss function
geneName	The name of the gene to plot. The name of the gene should correspond to a row name in both exprMatrNml and exprMatrTum matrices.
addToTitle	A string that can be added to the title, which includes the gene name.
clrs	Vector of length 2 containing colors to use for plot

Value

returns an object of class 'ggplot'

Examples

exprMatrNml <- matrix(abs(rnorm(100, mean=2)), nrow=10)
exprMatrTum <- matrix(abs(rnorm(100)), nrow=10)
geneNames <- paste0(letters[seq_len(nrow(exprMatrNml))],
seq_len(nrow(exprMatrNml)))
rownames(exprMatrNml) <- rownames(exprMatrTum) <- geneNames
nSdBelow <- 2
minPropPerGroup <- .2
rl <- receptLoss(exprMatrNml, exprMatrTum, nSdBelow, minPropPerGroup)
clrs <- c("#E78AC3", "#8DA0CB")
plotReceptLoss(exprMatrNml, exprMatrTum, rl, geneName="g7", clrs=clrs)

---

Identify genes with expression loss

Description

This function allows you to identify genes with loss of expression

Usage

receptLoss(exprMatrNml, exprMatrTum, nSdBelow, minPropPerGroup)

Arguments

exprMatrNml	A matrix of expression values from normal tissue. Each row is a gene, and each column is a patient or sample. Genes should be in same order as exprMatrTum.
exprMatrTum	A matrix of expression values from tumor tissue. Each row is a gene, and each column is a patient or sample. Genes should be in same order as exprMatrNml.
nSdBelow	The number of SD below the mean of the adjacent normal tissue to set the boundary between tumor subgroups.
minPropPerGroup	A value between 0-1 that represents the minimum proportion of samples that should be present in each of the two subgroups (defined by the boundary set by nSdBelow) for a particular gene.

Value

a nx7 matrix, with n equaling the number of genes. The columns are as follows:

• geneNm - the gene name

• lowerBound - the lower bound, or the value 'nSdBelow' the mean of the normal tissue expression data.

• propTumLessThBound - the proportion of tumor samples with expression levels less than 'lowerBound'

• muAb - "mu above", the mean expression value of tumors greater than (ie above) the 'lowerBound'.

• 'muBl' - "mu below", the mean expression value of tumors less than (ie below) the 'lowerBound'.

• 'deltaMu' - the difference between 'muAb' and 'muBl'.

• meetsMinPropPerGrp - a logical indicating whether the proportion of samples in each group is greater than that set by 'minPropPerGroup'.

Examples

exprMatrNml <- matrix(abs(rnorm(100, mean=2)), nrow=10)
exprMatrTum <- matrix(abs(rnorm(100)), nrow=10)
geneNames <- paste0(letters[seq_len(nrow(exprMatrNml))],
seq_len(nrow(exprMatrNml)))
rownames(exprMatrNml) <- rownames(exprMatrTum) <- geneNames
nSdBelow <- 2
minPropPerGroup <- .2
rl <- receptLoss(exprMatrNml, exprMatrTum, nSdBelow, minPropPerGroup)
head(rl)

---