| Title: | Data used in the vignette of the cnvGSA package |
|---|---|
| Description: | This package contains the data used in the vignette of the cnvGSA package. |
| Authors: | Joseph Lugo <[email protected]> |
| Maintainer: | Joseph Lugo <[email protected]> |
| License: | LGPL |
| Version: | 1.49.0 |
| Built: | 2026-10-10 10:30:32 UTC |
| Source: | https://github.com/bioc/cnvGSAdata |
This package contains data used in the examples and vignette of the cnvGSA package.
Raw input files:
cnv_AGP_demo.txt - CNV data
enrGeneric_AGP_demo.txt - enrichment generic data
enrGMT_AGP_demo.gmt - enrichment GMT data
kl_gene_AGP_demo.txt - genes of interest data
kl_loci_AGP_demo.txt - known loci data
ph_AGP_demo.txt - phenotype/covariate data
gene_ID_demo.txt - gene ID file
Pre-built input:
cnvGSA_input_example.RData
Saved output:
cnvGSA_output_example.RData
Pre-built Gene-set data:
gs_data_example.RData
Joseph Lugo [email protected]
The file contains rare CNV data similar to that used in the Pinto et al. 2014 ASD study.
The data is stored in a similar format as the Genome Variation Format http://www.sequenceontology.org/resources/gvf.html. See the user manual for more information.
Pinto, D et al. Convergence of Genes and Cellular Pathways Dysregulated in Autism Spectrum Disorders. Am J Hum Genet. 2014 May 1; 94(5): 677–694.
cnvFile <- system.file( "extdata", "cnv_AGP_demo.txt", package="cnvGSAdata" ) cnv.df <- read.table (cnvFile, header = TRUE, sep = "\t", quote = "\"", stringsAsFactors = FALSE)cnvFile <- system.file( "extdata", "cnv_AGP_demo.txt", package="cnvGSAdata" ) cnv.df <- read.table (cnvFile, header = TRUE, sep = "\t", quote = "\"", stringsAsFactors = FALSE)
Pre-built input used in the full workflow example in the cnvGSA vignette.
data("cnvGSA_input_example")data("cnvGSA_input_example")
The dataset contains cnvGSA.in, a single object of class CnvGSAInput as defined in the cnvGSA package. When processed by cnvGSAlogRegTest() – the main function in that package – it produces as its output an object of class CnvGSAOutput (such as the one stored in cnvGSA_output_example.RData).
Saved output from the full workflow example in the cnvGSA vignette.
data("cnvGSA_output_example")data("cnvGSA_output_example")
The dataset contains cnvGSA.out, a single object of class CnvGSAOutput as defined in the cnvGSA package. CnvGSAOutput is a simple S4 class containing a slot for each data structure output by cnvGSAlogRegTest (the main function in the package):
res.lsgsTables.lsgsData.lsphData.lsconfig.dfres.ls contains the output from the regression tests, gsTables.ls contains the the gene-set tables, gsData.ls contains the gene-set data needed for other scripts, phData.ls contains the phenotype/covariate data and config.df contains the config data frame that allows the other scripts to read in the params.
See the cnvGSA vignette for complete details and discussion.
The file contains gene-sets with their FDR and p-values similar to that used in the Pinto et al. 2014 ASD study.
The data is stored in a generic file format which can be seen here http://www.baderlab.org/Software/EnrichmentMap/UserManual#Generic_results_files
Pinto, D et al. Functional impact of global rare copy number variation in autism spectrum disorders. Nature. 2010 Jul 15; 466(7304): 368–72.
enrFile <- system.file( "extdata", "enrGeneric_AGP_demo.txt", package="cnvGSAdata" ) enrGeneric.df <- read.table (enrFile, header = TRUE, sep = "\t", quote = "\"", stringsAsFactors = FALSE)enrFile <- system.file( "extdata", "enrGeneric_AGP_demo.txt", package="cnvGSAdata" ) enrGeneric.df <- read.table (enrFile, header = TRUE, sep = "\t", quote = "\"", stringsAsFactors = FALSE)
The file contains gene-set data similar to that used in the Pinto et al. 2014 ASD study.
The data is stored in the Gene Matrix Transposed format http://www.baderlab.org/Software/EnrichmentMap/UserManual#Gene_sets_file_.28GMT_file.29.
Pinto, D et al. Convergence of Genes and Cellular Pathways Dysregulated in Autism Spectrum Disorders. Am J Hum Genet. 2014 May 1; 94(5): 677–694.
gmtFile <- system.file( "extdata", "enrGMT_AGP_demo.gmt", package="cnvGSAdata" ) no_col <- max(count.fields(gmtFile, sep = "\t")) gmt.df <- read.table(gmtFile,sep="\t",fill=TRUE,col.names=1:no_col)gmtFile <- system.file( "extdata", "enrGMT_AGP_demo.gmt", package="cnvGSAdata" ) no_col <- max(count.fields(gmtFile, sep = "\t")) gmt.df <- read.table(gmtFile,sep="\t",fill=TRUE,col.names=1:no_col)
The file contains Entrez gene ID's
The data is stored in a format that look like (geneID) -tab- (Symbol) -tab- (Name).
geneIDFile <- system.file( "extdata", "gene_ID_demo.txt", package="cnvGSAdata" ) geneID.df <- read.table (geneIDFile, header = TRUE, sep = "\t", quote = "\"", stringsAsFactors = FALSE)geneIDFile <- system.file( "extdata", "gene_ID_demo.txt", package="cnvGSAdata" ) geneID.df <- read.table (geneIDFile, header = TRUE, sep = "\t", quote = "\"", stringsAsFactors = FALSE)
Saved gsData described in the cnvGSA vignette.
data("gs_data_example")data("gs_data_example")
The dataset contains gsData. It contains the gene-sets analyzed in the cnvGSA vignette as well as the gene set names.
gs_all.lsgsid2name.chvgs_all.ls contains the gene-sets used in the analysis and gsid2name.chv contains the gene-set names.
See the cnvGSA vignette for complete details and discussion.
Contains the genes of interest that were also used in the Pinto et al. 2014 ASD study.
This file is used to provide the genes of interest that will be looked at in the testing.
Pinto, D et al. Convergence of Genes and Cellular Pathways Dysregulated in Autism Spectrum Disorders. Am J Hum Genet. 2014 May 1; 94(5): 677–694.
klGeneFile <- system.file( "extdata", "kl_gene_AGP_demo.txt", package="cnvGSAdata" ) kl_gene.df <- read.table (klGeneFile, header = TRUE, sep = "\t", quote = "\"", stringsAsFactors = FALSE)klGeneFile <- system.file( "extdata", "kl_gene_AGP_demo.txt", package="cnvGSAdata" ) kl_gene.df <- read.table (klGeneFile, header = TRUE, sep = "\t", quote = "\"", stringsAsFactors = FALSE)
Contains the known loci of genes as in the Pinto et al. 2014 ASD study.
This file is used to provide the loci of certain genes and this will affect the results from the test.
Pinto, D et al. Convergence of Genes and Cellular Pathways Dysregulated in Autism Spectrum Disorders. Am J Hum Genet. 2014 May 1; 94(5): 677–694.
klLociFile <- system.file( "extdata", "kl_loci_AGP_demo.txt", package="cnvGSAdata" ) kl_loci.df <- read.table (klLociFile, header = TRUE, sep = "\t", quote = "\"", stringsAsFactors = FALSE)klLociFile <- system.file( "extdata", "kl_loci_AGP_demo.txt", package="cnvGSAdata" ) kl_loci.df <- read.table (klLociFile, header = TRUE, sep = "\t", quote = "\"", stringsAsFactors = FALSE)
The file contains covariate/phenotype data similar to that used in the Pinto et al. 2014 ASD study.
The data is stored in a format that is a subset of the the CNV data. It includes all the covariates and phenotypes that the user wants.
Pinto, D et al. Convergence of Genes and Cellular Pathways Dysregulated in Autism Spectrum Disorders. Am J Hum Genet. 2014 May 1; 94(5): 677–694.
phFile <- system.file( "extdata", "ph_AGP_demo.txt", package="cnvGSAdata" ) ph.df <- read.table (phFile, header = TRUE, sep = "\t", quote = "\"", stringsAsFactors = FALSE)phFile <- system.file( "extdata", "ph_AGP_demo.txt", package="cnvGSAdata" ) ph.df <- read.table (phFile, header = TRUE, sep = "\t", quote = "\"", stringsAsFactors = FALSE)