small fixes

DESCRIPTION

@@ -30,7 +30,7 @@ biocViews:
 Imports: stats, methods, utils, plyr, tidyr, MASS, stringr, ape, vegan,
         SNPRelate, StAMPP, sp, PopGenReport, robustbase,
         gridExtra, foreach, dplyr, crayon, devtools,reshape2,
-        patchwork, data.table, hierfstat
+        patchwork, hierfstat, data.table
 Suggests: 
     tibble,
     HardyWeinberg,
@@ -62,7 +62,6 @@ Suggests:
     plotly,
     ggthemes,
     ggrepel,
-    raster,
     strataG,
     ggtern,
     markdown,
@@ -71,6 +70,7 @@ Suggests:
     SIBER,
     fields,
     snpStats,
+    raster,
     boot
 License: GPL-2
 LazyData: true

NAMESPACE

@@ -1,8 +1,8 @@
 # Generated by roxygen2: do not edit by hand
 
 export(AIC)
-export(AIC.comp)
-export(CLR)
+export(AIC_comp)
+export(fsc.bootstraps)
 export(fsc.estimate)
 export(fsc.multiple.estimate)
 export(gi2gl)

R/fastsimcoal.R

@@ -1,4 +1,3 @@
-
 #' Run fastsimcoal to estimate parameters' values
 #'
 #' Run fastsimcoal assuming that in \code{dir.in} there are the tpl, est and obs
@@ -9,7 +8,6 @@
 #' default value). If \code{ncpu}>0 and \code{nBatches=NULL}, \code{nBatches} is
 #' set to twice ]code{nspu}.
 #'
-#'
 #' @param dir.in The path where to run fsc
 #' @param n The number of coalescent simulations to approximate the expected SFS
 #'   (-n option). This should be larger than 100,000.
@@ -24,13 +22,20 @@
 #' @param fsc.path The path where fsc is installed or \code{"path"} if it is in
 #'   the PATH (that means that it can be called regardless of the working
 #'   directory)
-#'@author  Carlo Pacioni (Post to \url{https://groups.google.com/d/forum/dartr})
+#' @author  Carlo Pacioni (Post to \url{https://groups.google.com/d/forum/dartr})
 #' @export
 #' @references Excoffier L., Dupanloup I., Huerta-Sánchez E., Sousa V. C. and
 #'   Foll M. (2013) Robust demographic inference from genomic and SNP data. PLoS
 #'   genetics 9(10)
-fsc.estimate <- function(dir.in, n=500000, L=100, maf=TRUE, ncpu=0, nBatches=NULL, 
-                         fsc.cmd="fsc2702", fsc.path="path") {
+fsc.estimate <- function(dir.in,
+                         n=500000,
+                         L=100,
+                         maf=TRUE,
+                         ncpu=0, 
+                         nBatches=NULL, 
+                         fsc.cmd="fsc2702", 
+                         fsc.path="path") {
+
   if(!is.integer(as.integer(ncpu))) stop("The number of CPUs has to be an integer")
   if(ncpu == 0 & is.null(nBatches)) nBatches <- 12
   if(ncpu > 0 & is.null(nBatches)) nBatches <- 2 * ncpu
@@ -62,27 +67,26 @@ fsc.multiple.estimate <- function(dir.in, n=500000, L=100, maf=TRUE, ncpu=0,
 
 }
 
-
-#' AIC
-#'
-#' compute the AIC given the likelihood in log10 scale (default fsc output) and
-#' number of parameters, which is automatically read by the function if
-#' \code{k=NULL).
-#'
+#' @name AIC
+#' @title Compute the AIC given the likelihood in log10 scale
+#' @description Compute the AIC given the likelihood in log10 scale (default fsc
+#'  output) and number of parameters, which is automatically read by the 
+#'  function if \code{k=NULL}.
+#' @param dir.in The directory where the analysis was conducted
+#' @param k The number of parameters in the model. If \code{NULL} is read
+#'   automatically by the function
+#' @details
 #' It is important to note that this function will probably fail if there are
 #' more than one .est within each directory as it will read these to evaluate
 #' the number of parameters in the model. If there is more than one file, there
 #' is no way to know which one is correct.
-#'
-#' @param dir.in The directory where the analysis was conducted
-#' @param k The number of parameters in the model. If \code{NULL} is read
-#'   automatically by the function
-#'@author  Carlo Pacioni (Post to \url{https://groups.google.com/d/forum/dartr})
+#' @author  Carlo Pacioni (Post to \url{https://groups.google.com/d/forum/dartr})
 #' @export
 #' @references Excoffier L., Dupanloup I., Huerta-Sánchez E., Sousa V. C. and
 #'   Foll M. (2013) Robust demographic inference from genomic and SNP data. PLoS
 #'   genetics 9(10)
-AIC <- function(dir.in, k=NULL) {
+AIC <- function(dir.in,
+                k=NULL) {
   log10toln<-function(l10) {
     rlns=l10/log10(exp(1))
   }
@@ -106,13 +110,14 @@ AIC <- function(dir.in, k=NULL) {
   return(2*k-2*ln)
 }
 
-#' Compute and compare AIC for different fasimcoal models
-#'
+#' @name AIC_comp 
+#' @title Compute and compare AIC for different fastsimcoal models
+#' @description
 #' This functions expects that different fastsimcoal models were run in
 #' different directories within the same parent directory (as for
 #' \code{fsc.multiple.estimate}). Assuming that \code{dir.in} is the parent
 #' directory, it will extract and compute AIC from all of them.
-#'
+#' @details
 #' It is important to note that this function will probably fail if there are
 #' more than one .est within each directory as it will read these to evaluate
 #' the number of parameters in the model. If there is more than one file, there
@@ -121,15 +126,15 @@ AIC <- function(dir.in, k=NULL) {
 #' cause problems in reporting the results even if the function completes.
 #'
 #' @param dir.in The parent directory within which the models have been run
-#'@author  Carlo Pacioni (Post to \url{https://groups.google.com/d/forum/dartr})
+#' @author  Carlo Pacioni (Post to \url{https://groups.google.com/d/forum/dartr})
 #' @export
 #' @references Excoffier L., Dupanloup I., Huerta-Sánchez E., Sousa V. C. and
 #'   Foll M. (2013) Robust demographic inference from genomic and SNP data. PLoS
 #'   genetics 9(10)
-AIC.comp <- function(dir.in) {
+AIC_comp <- function(dir.in) {
   mod.nms <- list.dirs(dir.in, full.names=FALSE, recursive=FALSE)
   ld <- list.dirs(dir.in,full.names=TRUE, recursive=FALSE)
-  lAICs <- sapply(ld, amplicR::AIC, USE.NAMES=FALSE)
+  lAICs <- sapply(ld, AIC, USE.NAMES=FALSE)
   mod.rank <- rank(lAICs)
   return(data.frame(Model=mod.nms, AIC=lAICs, Delta=lAICs - min(lAICs), Rank=mod.rank))
 }
@@ -179,27 +184,41 @@ AIC.comp <- function(dir.in) {
 #'@param boot.type The method to be used to compute the confidence intervals.
 #'  See \code{?boot.ci} for details. By default, percentile intervals are
 #'  computed.
-#'@inheritParams fsc.estimate
-#'@author  Carlo Pacioni (Post to \url{https://groups.google.com/d/forum/dartr})
-#'@return A list with the following elements \itemize{ \item Bootstr.stats:
-#'  Descriptive statistics from bootstraps (Median, lower and upper limit), an
-#'  the initial estimated parameters  \item P.Rand.less.Obs: The probability that
-#'  a random value from the null Composite Likelihood Ratio distribution is less
-#'  than the observed CLR \item P.Rand.gt.Obs: The probability that a random
-#'  value from the null Composite Likelihood Ratio distribution is greater than
-#'  the observed CLR \item Sim: The estimates from the simulated data }
+#' @inheritParams fsc.estimate
+#' @author  Carlo Pacioni (Post to \url{https://groups.google.com/d/forum/dartr})
+#' @return A list with the following elements: 
+#' \itemize{ 
+#' \item Bootstr.stats: Descriptive statistics from bootstraps (Median, lower and
+#' upper limit), an the initial estimated parameters.  
+#' \item P.Rand.less.Obs: The probability that a random value from the null 
+#' Composite Likelihood Ratio distribution is less than the observed CLR.
+#' \item P.Rand.gt.Obs: The probability that a random value from the null 
+#' Composite Likelihood Ratio distribution is greater than the observed CLR.
+#' \item Sim: The estimates from the simulated data.
+#' }
+#' @export
 #'@references Excoffier L., Dupanloup I., Huerta-Sánchez E., Sousa V. C. and
 #'  Foll M. (2013) Robust demographic inference from genomic and SNP data. PLoS
 #'  genetics 9(10)
-#'@export
 
-CLR <- MaxEstLhood <- MaxObsLhood <- Param <- NULL
-
-fsc.bootstraps <- function(dir.in, nLoci=10000, nSim=100, maf=TRUE, ncpu=0, 
-                           nBatches=NULL, fsc.cmd="fsc2702", fsc.path="path",
-                           par.indLoci="200000 0", par.nBlocks=1, 
+fsc.bootstraps <- function(dir.in, 
+                           nLoci=10000, 
+                           nSim=100,
+                           maf=TRUE, 
+                           ncpu=0, 
+                           nBatches=NULL, 
+                           fsc.cmd="fsc2702", 
+                           fsc.path="path",
+                           par.indLoci="200000 0",
+                           par.nBlocks=1, 
                            par.data="DNA 100 0 2.5e-8 0.33",
-                           n=100000, L=50, nBoot=1000, conf=0.95, boot.type="perc") {
+                           n=100000, 
+                           L=50, 
+                           nBoot=1000, 
+                           conf=0.95, 
+                           boot.type="perc") {
+
+  CLR <- MaxEstLhood <- MaxObsLhood <- Param <- NULL
   #---------- Helper ---------------#
   med.i <- function(x, i) median(x[i])
 

R/gl.impute.r

@@ -127,7 +127,7 @@ gl.impute <-  function(x,
     x3 <- NULL
     # merge back populations
     for (pop in pop_list) {
-      x3 <- rbind (x3, pop)
+      x3 <- rbind(x3, pop)
     }
   }
   # if 1 population

R/gl.report.hwe.r

@@ -109,12 +109,16 @@
 #'
 #' Ternary plots can be used to visualise patterns of H-W proportions (plot.out
 #' = TRUE). P-values and the statistical (non)significance of a large number of
-#' bi- allelic markers can be inferred from their position in a ternary plot.
+#' bi-allelic markers can be inferred from their position in a ternary plot.
 #' See Graffelman & Morales-Camarena (2008) for further details. Ternary plots
 #' are based on the function  \code{\link[HardyWeinberg]{HWTernaryPlot}} from
-#' the package HardyWeinberg. Loci that depart significantly from H-W
-#' proportions are shown in red, and those not showing significant departure are
-#' shown in green.
+#' the package HardyWeinberg. Each vertex of the Ternary plot represents one of 
+#' the three possible genotypes for SNP data: homozygous for the reference 
+#' allele (AA), heterozygous (AB) and homozygous for the alternative allele
+#'  (BB). Loci deviating significantly from Hardy-Weinberg proportions after 
+#'  correction for multiple tests are shown in pink. The blue parabola 
+#'  represents Hardy-Weinberg equilibrium, and the area between green lines 
+#'  represents the acceptance region.
 #'
 #' For these plots to work it is necessary to install the package ggtern.
 #' @return A dataframe containing loci, counts of reference SNP homozygotes,

R/gl.report.ld.map.r

@@ -7,7 +7,7 @@
 #' 
 #' This function requires that SNPs to be mapped to a reference genome and the 
 #' information for SNP's position must be stored in the genlight accessor 
-#' @@position" and the SNP's chromosome name in the accessor @@chromosome. 
+#' position" and the SNP's chromosome name in the accessor chromosome. 
 #'
 #' @param x Name of the genlight object containing the SNP data [required].
 #' @param ld_max_pairwise Maximum distance in number of base pairs at which LD 

R/gl2sfs.R

@@ -23,10 +23,13 @@
 #'
 #'It expects a dartR formatted genlight object, but it should also  work with
 #'other genlight objects.
-#'
-#'@param outfile_root The root of the name of the output file
-#'@inheritParams gl.report.heterozygosity
-#'@inheritParams gl2vcf
+#' @param x Name of the genlight object containing the SNP data [required].
+#' @param n.invariant.tags Number of invariant sites[default 0].
+#' @param outfile_root The root of the name of the output file [default "gl2sfs"].
+#' @param outpath Path where to save the output file [default tempdir()].
+#' @param verbose Verbosity: 0, silent or fatal errors; 1, begin and end; 2,
+#' progress log; 3, progress and results summary; 5, full report
+#' [default 2, unless specified using gl.set.verbosity].
 #'@return A list with two elements: the DAF and MAF.
 #'@author Custodian: Carlo Pacioni (Post to
 #'  \url{https://groups.google.com/d/forum/dartr})