adjusted p-values from a lfmm run

Description

Return the lfmm output vector of adjusted p-values and the genomic inflation factor using the genomic control method or the lambda inflation factor parameter for the chosen runs with K fatent factors, the d-th variable and the all option. For an example, see lfmm.

Usage

adjusted.pvalues (object, genomic.control, lambda, K, d, all, run)

Arguments

Value

Author(s)

Eric Frichot

See Also

lfmm.data lfmm p.values mlog10p.values

Examples

### Example of analyses using lfmm ###

data("tutorial")
# creation of the genotype file, genotypes.lfmm.
# It contains 400 SNPs for 50 individuals.
write.lfmm(tutorial.R, "genotypes.lfmm")
# creation of the environment file, gradient.env.
# It contains 1 environmental variable for 40 individuals.
write.env(tutorial.C, "gradients.env")

################
# runs of lfmm #
################

# main options, K: (the number of latent factors), 
#           CPU: the number of CPUs.

# Toy runs with K = 3 and 2 repetitions.
# around 15 seconds per run.
project = NULL
project = lfmm("genotypes.lfmm", "gradients.env", K = 3, repetitions = 2,
    iterations = 6000, burnin = 3000, project = "new")

# get the adjusted p-values using the genomic control method
res = adjusted.pvalues(project, K = 3)

hist(res$p.values, col = "yellow3")

# get the adjusted p-values with the genomic inflatino factor
res = adjusted.pvalues(project, genomic.control = FALSE, 
    lambda = res$genomic.inflation.factor, K = 3)

hist(res$p.values, col = "yellow3")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(LEA)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/LEA/adjusted_pvalues.Rd_%03d_medium.png", width=480, height=480)
> ### Name: adjusted.pvalues
> ### Title: adjusted p-values from a lfmm run
> ### Aliases: adjusted.pvalues
> ### Keywords: lfmm
> 
> ### ** Examples
> 
> ### Example of analyses using lfmm ###
> 
> data("tutorial")
> # creation of the genotype file, genotypes.lfmm.
> # It contains 400 SNPs for 50 individuals.
> write.lfmm(tutorial.R, "genotypes.lfmm")
[1] "genotypes.lfmm"
> # creation of the environment file, gradient.env.
> # It contains 1 environmental variable for 40 individuals.
> write.env(tutorial.C, "gradients.env")
[1] "gradients.env"
> 
> ################
> # runs of lfmm #
> ################
> 
> # main options, K: (the number of latent factors), 
> #           CPU: the number of CPUs.
> 
> # Toy runs with K = 3 and 2 repetitions.
> # around 15 seconds per run.
> project = NULL
> project = lfmm("genotypes.lfmm", "gradients.env", K = 3, repetitions = 2,
+     iterations = 6000, burnin = 3000, project = "new")
The project is saved into :
 genotypes_gradients.lfmmProject 

To load the project, use:
 project = load.lfmmProject("genotypes_gradients.lfmmProject")

To remove the project, use:
 remove.lfmmProject("genotypes_gradients.lfmmProject")

[1] "********************************"
[1] "* K = 3  repetition 1  d = 1   *"
[1] "********************************"
Summary of the options:

        -n (number of individuals)      50
        -L (number of loci)             400
        -K (number of latent factors)   3
        -o (output file)                genotypes_gradients.lfmm/K3/run1/genotypes_r1
        -i (number of iterations)       6000
        -b (burnin)                     3000
        -s (seed random init)           772036597
        -p (number of processes (CPU))  1
        -x (genotype file)              genotypes.lfmm
        -v (variable file)              gradients.env
        -D (number of covariables)      1
        -d (the dth covariable)         1

Read variable file:
 	gradients.env		OK.

Read genotype file:
 	genotypes.lfmm		OK.

<<<<
	 Analyse for variable 1

		Start of the Gibbs Sampler algorithm.

	[                                                                           ]
	[===========================================================================]

		End of the Gibbs Sampler algorithm.

	ED:20000.19902	 DIC: 19968.12444 


ERROR: unable to open file genotypes_gradients.lfmm/K3/run1/genotypes_r1_s1.3.dic. Please, check that the name of the file you provided is correct.

Error: 
Execution halted