Package 'PAST'

Assign SNPs in a chunk to genes

Description

Assign SNPs in a chunk to genes

Usage

assign_chunk(gff, chunk, window)

Arguments

gff	The GFF data for the chromosome being parsed
chunk	The dataframe containing SNP data
window	The search window around the SNPs

Value

tagSNPs labeled with gene names

---

Assign SNPs to genes

Description

Assign SNPs to genes

Usage

assign_SNPs_to_genes(
  gwas_data,
  LD,
  gff_file,
  filter_type,
  window,
  r_squared_cutoff,
  num_cores
)

Arguments

gwas_data	Merged association and effects data from merge_data()
LD	Linkage disequilibrium data from parse_LD()
gff_file	The path to a GFF file
window	The search window for genes around the SNP
r_squared_cutoff	The R^2 value used to determine SNP significance
num_cores	The number of cores to use in parallelizing PAST

Value

A dataframe of genes from the SNP data

Examples

example("load_GWAS_data")
example("load_LD")
demo_genes_file = system.file("extdata", "genes.gff",
  package = "PAST", mustWork = TRUE)
filter_type = c("gene")
genes <-assign_SNPs_to_genes(gwas_data, LD, demo_genes_file, filter_type, 1000, 0.8, 2)

---

Determine Linkage

Description

Determine Linkage

Usage

determine_linkage(chunk, r_squared_cutoff)

Arguments

chunk	A chunk of data to be processed
r_squared_cutoff	The R^2 value to check against

Value

Either the first unlinked SNP or a set of linked SNPs

---

Find Pathway Significance

Description

Find Pathway Significance

Usage

find_pathway_significance(
  genes,
  pathways_file,
  gene_number_cutoff = 5,
  mode,
  sample_size = 1000,
  num_cores
)

Arguments

genes	Genes from assign_SNPs_to_genes()
pathways_file	A file containing the pathway IDs, their names, and the genes in the pathway
gene_number_cutoff	A cut-off for the minimum number of genes in a pathway
mode	increasing/decreasing
sample_size	How many times to sample the effects data during random sampling
num_cores	The number of cores to use in parallelizing PAST

Value

Rugplots data

Examples

example("assign_SNPs_to_genes")
demo_pathways_file = system.file("extdata", "pathways.txt.xz",
  package = "PAST", mustWork = TRUE)
rugplots_data <- find_pathway_significance(genes, demo_pathways_file, 5,
  "increasing", 1000, 2)

---

Find representative SNP for a chunk of SNPs

Description

Find representative SNP for a chunk of SNPs

Usage

find_representative_SNP(chunk, r_squared_cutoff)

Arguments

chunk	A chunk of data to parse
r_squared_cutoff	The R^2 value to check against when counting SNPs

Value

A single SNP representing the whole chunk

---

Find the SNP-gene assignment that represents SNPs assigned to a gene

Description

Find the SNP-gene assignment that represents SNPs assigned to a gene

Usage

find_representative_SNP_gene_pairing(chunk)

Arguments

chunk

A chunk of gene assignments

Value

A single SNP-gene assignment representing all SNPS assigned to the same gene to a gene

---

Load GWAS data

Description

Load GWAS data

Usage

load_GWAS_data(
  association_file,
  effects_file,
  association_columns = c("Trait", "Marker", "Locus", "Site", "p", "marker_R2"),
  effects_columns = c("Trait", "Marker", "Locus", "Site", "Effect")
)

Arguments

association_file	The association file
effects_file	The effects file
association_columns	The names of the columns in your association data for Trait, Marker, Chromosome, Site, F, p, and marker_Rsquared
effects_columns	The names of the columns in your effects data for Trait, Marker, Chromosome, Site, and effect

Value

The association data and the effects data merged into a dataframe with one row for each SNP

Examples

demo_association_file = system.file("extdata", "association.txt.xz",
  package = "PAST", mustWork = TRUE)
demo_effects_file = system.file("extdata", "effects.txt.xz",
  package = "PAST", mustWork = TRUE)
gwas_data <- load_GWAS_data(demo_association_file, demo_effects_file)

---

Load Linkage Disequilibrium

Description

Load Linkage Disequilibrium

Usage

load_LD(
  LD_file,
  LD_columns = c("Locus1", "Position1", "Site1", "Position2", "Site2", "Dist_bp",
    "R.2")
)

Arguments

LD_file	The file containing linkage disequilibrium data
LD_columns	The names of the columns in your linkage disequilibrium data for the chromosome of the first SNP, the position of the first SNP, the site of the first SNP, the chromosome of the second SNP, the position of the second SNP, the site of the second SNP, the distance between the two SNPs, and the R.2

Value

The linkage disequilibrium data in a list containing dataframes for each chromosome.

Examples

demo_LD_file = system.file("extdata","LD.txt.xz",
  package = "PAST", mustWork = TRUE)
LD <- load_LD(demo_LD_file)

---

Plot Rugplots for Selected Pathways

Description

Plot Rugplots for Selected Pathways

Usage

plot_pathways(
  rugplots_data,
  filter_type,
  filter_parameter,
  mode,
  output_directory
)

Arguments

rugplots_data	The data to be plotted (returned from find_pathway_significance())
filter_type	The parameter to be used for filtering
filter_parameter	The cut-off value of the filtering parameter
mode	The mode used to create the data (increasing/decreasing)
output_directory	An existing directory to save results in

Value

Does not return a value

Examples

example("find_pathway_significance")
plot_pathways(rugplots_data, "pvalue", "0.03", "decreasing", tempdir())

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