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cape (version 2.0.2)

Combined Analysis of Pleiotropy and Epistasis

Description

Combines complementary information across multiple related phenotypes to infer directed epistatic interactions between genetic markers. This analysis can be applied to a variety of engineered and natural populations.

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Version

Install

install.packages('cape')

Monthly Downloads

318

Version

2.0.2

License

GPL-3

Maintainer

Anna L Tyler

Last Published

June 9th, 2016

Functions in cape (2.0.2)

Filter markers by minor allele frequency.

Filter markers by Hardy-Weinberg equilibrium

calc.delta.errors

Error propagation

direct.influence

Calculate the significance of direct influences of variant pairs on phenotypes

Calculate P Values for Interactions Based on Permutations

Remove phenotypes from the phenotype matrix

Estimate Errors of Regression Coefficients

Generate a matrix of consecutive pairs

get.chr.markers

Calculate a genome-wide significance threshold for the single-variant scan

genome.wide.threshold.1D.parallel

Calculate a genome-wide significance threshold for the single-variant scan using parallel computing.

get.eigentraits

Calculate eigentraits from phenotype matrix

Get the best layout matrix for a given number of panes per page.

get.geno.with.covar

Retrieve the genotype matrix with the covariates appended.

Bin a continuous vector into discrete values.

Combinatorial Analysis of Epistasis and Pleiotropy

Retrieve the genotype matrix.

get.marker.name

Get marker names from marker numbers

Get marker numbers from marker names

Get information about covariates

Use column titles to retrieve column numbers

Convert the final results to a form plotted by plotNetwork and plotCollapsedVarInf

Get marker values

Retrieve colors for use in plotting.

Retrieve the genotype matrix.

genome.wide.threshold.1D

Calculate a genome-wide significance threshold for the single-variant scan

Get chromosome assignments for a vector of markers.

get.linearly.independent

Find all markers in the genotype matrix that are linearly independent

Normalize and mean center phenotypes

get.marker.location

Get the chromosomal coordinate of markers

linkage.blocks.network

Calculates linkage blocks using community detection.

get.pairs.for.pairscan

Select marker pairs for pairscan based on filters

kinship.on.the.fly

Kinship correction for genotype and phenotype.

impute.missing.geno

Impute missing genotypes in measured markers.

Get the column index of markers in the genotype matrix

Mouse cross data from Reifsnyder et al. (2000)

Plot histograms of phenotypes.

Generate data.obj from pheno.obj and geno.obj

Calculate all leave-one-out or leave-two-out kinship matrices.

Used in plotting results of pair scan.

Create a covariate from a genetic marker.

Runs one singlescan

Perform regressions for all pairs of markers and all phenotypes.

plotCollapsedVarInf

Plot variant-to-variant influences

Plot phenotype values by individual.

Plot the final epistatic network

Read in and format data for analysis by cape

Given a vector of elements, create a two-column matrix listing all pairs of elements

Plot the results of the singular value decomposition of the phenotype matrix

Create a covariate from a phenotype.

Performs a pairscan with kinship correction.

one.pairscan.parallel

Perform regression analysis for one phenotype and all pairs of markers using a kinship correction.

plotVariantInfluences

Plot variant-to-variant influences

Read in and format data for analysis by cape

report.progress

Print the progress of a function to the screen

plot the results from pairscan

Subset a cross object to include only specified chromosomes.

Divide a region into equal parts.

Plot the results of singlescan

Remove markers from the data.obj

Normalize a vector using rank normalization

read.population

Read in and format data for analysis by cape

Generate a null distribution for the pairscan.

Performs a pairscan without a kinship correction.

Run the single-variant regression for all phenotypes

Sort the genetic markers in the data.obj.

writePopulation

Write out a cape data object to .csv format.

select.markers.for.pairscan

A required step that filters variable and non-redundant markers for the pairscan

Write out a cape data object to .csv format.

writeVariantInfluences

Write the final results to a file

Plot correlations between phenotype pairs.

Plot qq plots of phenotype pairs.

plotSinglescan.heat

Plot the results of singlescan as a heatmap

Subset a cross object to include specific individuals

select.eigentraits

Select a subset of the eigentraits for further analysis

Rotate a matrix 90 degrees clockwise

Remove individuals from the data.obj

Select phenotypes for analysis