Package 'iPath'

density fall plot

Description

This function allows you to express your love of cats.

Usage

density_fall(iES_mat, gs_str, indVec, title = TRUE)

Arguments

iES_mat, gs_str	is the iES_mat with tumor and normal and gs name.
indVec	the binary indicator for normal(0) and tumor (1) patients.
title	boolean true or false for including the title in the ggplot.

Value

ggplot object containing the KM plot.

Examples

data(PRAD_data)
data(GSDB_example)
iES_mat = iES_cal2(prad_exprs, GSDB = GSDB_example)
density_fall(iES_mat, gs_str = "SimPathway1", indVec = prad_inds)

---

example gene set database (GSDB)

Description

includes geneset.names, genesets.

Usage

data("GSDB_example")

Format

A list of gene set database

Source

https://www.gsea-msigdb.org/gsea/msigdb/

References

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3106198/

Examples

data("GSDB_example")
GSDB_example$geneset.names

---

GSEA calculation

Description

This function calculates the GSEA enrichment score.

Usage

GSEA(gene_list, gene_set, stats_vector)

Arguments

gene_list	is a list of genes.
gene_set	is a set of genes.
stats_vector	a vector quantify the level of genes in the gene list.

Value

the orignial GSEA score.

---

iES calculation Function

Description

This function calculates the iES matrix which is the core of iPath.

Usage

iES_cal2(Y, GSDB, BPPARAM = NULL, nPro = 0)

Arguments

Y	is the expression matrix.
GSDB	is the gene set database.
BPPARAM	parameters from the BiocParallel.
nPro	number of processors (default = 0).

Value

a matrix with rows corresponding to the pathways and columns corresponding to the patients.

Examples

data(PRAD_data)
data(GSDB_example)
iES_mat = iES_cal2(prad_exprs, GSDB = GSDB_example)

---

iES calculation Function

Description

This function allows to investigate on one specific pathway.

Usage

iES_surv(iES_mat, cli, indVec = NULL, npatsThre = 5)

Arguments

iES_mat	is iES matrix with rows corresponding to the pathway and columns corresponding to the patients.
cli	clinical data associated to the gene expression data.
indVec	binary vector indicating normal (0) and tumor (1).
npatsThre	the threshold of number of patients for survival analysis.

Value

a matrix of survival analysis from coxph.

Examples

data(PRAD_data)
data(GSDB_example)
iES_mat = iES_cal2(prad_exprs, GSDB = GSDB_example)
iES_surv(iES_mat, cli = prad_cli, indVec = prad_inds)

---

iES survival for a certain pathway

Description

This function allows you to express your love of cats.

Usage

iES_survPlot(iES_mat, cli, gs_str, indVec = NULL, npatsThre = 5, title = TRUE)

Arguments

iES_mat, gs_str	is the GSDB iES_mat with tumor and normal and gs name.
cli	clinical data corresponding to the expression data.
indVec	the binary indicator for normal(0) and tumor (1) patients.
npatsThre	the threshold of number of patients for survival analysis.
title	boolean true or false for including the title (gs_str) in the ggplot.

Value

ggplot object containing the KM plot.

Examples

data(PRAD_data)
data(GSDB_example)
iES_mat = iES_cal2(prad_exprs, GSDB = GSDB_example)
iES_survPlot(iES_mat, cli = prad_cli, gs_str = "SimPathway1", indVec = prad_inds)

---

simulated clinical data for PRAD cancer patients

Description

prad_cli is the clinical data containing three variables times, bcr_patient_barcode, and patient.vital_status.

Usage

data("PRAD_data")

Format

An object of "matrix" class contains the clinical outcomes

Source

https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga

References

Kosinski M, Biecek P (2021). RTCGA: The Cancer Genome Atlas Data Integration. R package version 1.22.0, https://rtcga.github.io/RTCGA.

Examples

data("PRAD_data")
prad_cli[1:10,]

---

expression matrix for PRAD cancer patients in TCGA

Description

prad_exprs is the RPKM expression matrix which belongs to "matrix" class. The data includes 102 samples about human preimplantation embryos and embryonic stem cells. It contains 19304 genes after removing genes with extreme high dropout rate.

Usage

data("PRAD_data")

Format

An object of "matrix" class contains the mRNA expressions

Source

https://www.bioconductor.org/packages/release/bioc/html/RTCGA.html

References

Kosinski M, Biecek P (2021). RTCGA: The Cancer Genome Atlas Data Integration. R package version 1.22.0, https://rtcga.github.io/RTCGA.

Examples

data("PRAD_data")
prad_exprs[1:10, 1:4]

---

normal (0) and tumor (1) classes associated with PRAD expression data

Description

normal (0) and tumor (1) classes associated with PRAD expression data.

Usage

data("PRAD_data")

Format

A character vector contains the class label

Source

https://www.bioconductor.org/packages/release/bioc/html/RTCGA.html

References

Kosinski M, Biecek P (2021). RTCGA: The Cancer Genome Atlas Data Integration. R package version 1.22.0, https://rtcga.github.io/RTCGA.

Examples

data("PRAD_data")
table(prad_inds)

---

remove genes with 0 sd

Description

This function helps remove non-informative genes.

Usage

rem_data(Y)

Arguments

Y	is the expression matrix.

Value

a processed matrix

---

set up for the parallel computing for biocParallel.

Description

This function sets up the environment for parallel computing.

Usage

setUp_BPPARAM(nproc = 0, BPPARAM = NULL)

Arguments

nproc	number of processors
BPPARAM	bpparameter from bpparam

Value

BAPPARAM settings

---

water fall plot

Description

This function allows you to express your love of cats.

Usage

water_fall(iES_mat, gs_str, indVec, title = TRUE)

Arguments

iES_mat, gs_str	is the iES_mat with tumor and normal and gs name.
indVec	the binary indicator for normal(0) and tumor (1) patients.
title	boolean true or false for including the title (gs_str) in the ggplot.

Value

ggplot object containing the KM plot.

Examples

data(PRAD_data)
data(GSDB_example)
iES_mat = iES_cal2(prad_exprs, GSDB = GSDB_example)
water_fall(iES_mat, gs_str = "SimPathway1", indVec =prad_inds)

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