version 2.0.0

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: propr
 Title: Calculating Proportionality Between Vectors of Compositional
         Data
-Version: 1.1.0
+Version: 2.0.0
 URL: http://github.com/tpq/propr
 BugReports: http://github.com/tpq/propr/issues
 Authors@R: c(
@@ -16,20 +16,21 @@ Description: The bioinformatic evaluation of gene co-expression often begins wit
     analysis, a branch of math dealing specifically with relative data. In a
     subsequent publication, Erb and Nicodemus expounded these efforts by elaborating
     on another proportionality metric, rho. This package introduces a programmatic
-    framework for the calculation of feature dependence using proportionality and
-    other compositional data methods discussed in the cited publications.
+    framework for the calculation of feature dependence through proportionality, as
+    discussed in the cited publications.
 License: GPL-2
 LazyData: true
 VignetteBuilder: knitr
 RoxygenNote: 5.0.1
 Depends: R (>= 3.2.2)
-Imports: methods
+Imports: methods, Rcpp
 Suggests: compositions, dendextend, ggplot2, ggthemes, knitr,
         rmarkdown, testthat
-NeedsCompilation: no
-Packaged: 2016-07-06 00:08:59 UTC; thom
+LinkingTo: Rcpp
+NeedsCompilation: yes
+Packaged: 2016-08-27 10:09:40 UTC; thom
 Author: Thomas Quinn [aut, cre],
   David Lovell [aut]
 Maintainer: Thomas Quinn <contacttomquinn@gmail.com>
 Repository: CRAN
-Date/Publication: 2016-07-06 09:44:00
+Date/Publication: 2016-08-27 14:22:08

MD5

@@ -1,31 +1,35 @@
-455c771cf8481b26401d90907353a3aa *DESCRIPTION
-156ec54e98b9e35ed47a671d223edf1b *NAMESPACE
-d42464af95b40021761560662d6f709d *NEWS.md
-202017784e399813d15f595fff4440e4 *R/propr-backend.R
-a50b04d7046c0b703e4e7098de5f3ddf *R/propr-classes.R
-9c4cd2f34759be4bea23c8eed7d7bb7f *R/propr-methods.R
-e71cf145895d640e635811964126b17c *R/propr-perb.R
-628ec584b94b4b595b5f3b7c9aae07ba *R/propr-phit.R
-eb65f255609f369fa209912ea0065afb *README.md
+d059c5cfd0ae6d49d3ad206f30e81551 *DESCRIPTION
+abca9c6df0bbaa00132e035a2f45cd07 *NAMESPACE
+86f9ea9dbd4141deb84cb8b6ea7488bb *NEWS.md
+63b6059302761d78cac73c0a061e42af *R/RcppExports.R
+9edd9c2a76f3d62afb4c952bc696893d *R/backend.R
+879cf2cba4859c162b1ddb23cffdcdd6 *R/classes.R
+d8aaf1df117330520b66ce586bd97f1d *R/methods.R
+0d32a2a2d574ddf523364de75909dfc6 *R/perb.R
+d956e0a6be76b159d703c14b16220e29 *R/phit.R
+c2b8cbefab7357aadca5dbe49ca9fda9 *README.md
 79086a6786543eda37d50ee59b2d9da5 *build/vignette.rds
-7e8b32c5ecd2d10e82aed71f928be93a *inst/doc/propr-vignette.R
-d4bfa5c80c697c188330a0c205b86d13 *inst/doc/propr-vignette.Rmd
-2cdfc1f722d89face3c159481581484a *inst/doc/propr-vignette.html
-3a1924d0443f34ddfc7e8a051dea4b37 *man/perb.Rd
-e82dfb7b8d74048aa755b946858288ff *man/phit.Rd
-c1f20b8969faf5bbd5a0399e54ab615d *man/propr-class.Rd
-d5ccc56298a3b1d5e04968cfc4d8d74e *man/propr.Rd
-0fe59d89c9611cf4301cbc8f43cb2fa3 *man/proprALR.Rd
-b3c307949b6b75260172ed7ef0997fdd *man/proprCLR.Rd
-f3ca7b8b03b6b44ee558ae5c00010048 *man/proprPairs.Rd
-2287bdb852156bbe3d98830c561dc115 *man/proprPerb.Rd
-18fb6daf85bb1e408a53dde4b679a392 *man/proprPhit.Rd
-6082a9b422e214509bfac10bd6f93a2c *man/proprSym.Rd
-d2e912419a153a83fb9753300bfd7d9d *man/proprTri.Rd
-d3b180f9c085eb5ee6cb51db23dbe723 *man/proprVLR.Rd
+76af6a0eefb17a39e9abb65f4f1863fa *inst/doc/propr-vignette.R
+ea81a5e66116c32b2af3ffcf8f5a27a2 *inst/doc/propr-vignette.Rmd
+d8c966a5849ce485e471c8a1fe8f6969 *inst/doc/propr-vignette.html
+79e934eb5df289c87d2c969ef49e9a44 *man/perb.Rd
+aa9d8b8c2a05fe4f6e87c03ad2adac25 *man/phit.Rd
+6254e24d72b8f3c50cc74ebe23fce600 *man/propr-class.Rd
+34f13a665f4c8eaad4053520258bac54 *man/propr.Rd
+85ab40d6e380c797d17562532076f126 *man/proprALR.Rd
+67b85829d0471a87b07a9c86ec2ac38d *man/proprCLR.Rd
+c8e131841455fe7e2a761d5b5581cbe0 *man/proprPairs.Rd
+d022f2c881c3bf28115196ba7b0e7e40 *man/proprPerb.Rd
+5e20133ee7cf3cbdf2d428ab0b028ced *man/proprPhit.Rd
+50d59ee28ccfb5eccda2fe08e26cc1de *man/proprSym.Rd
+ae05d59999662a5cda9edd24c95dc2c7 *man/proprTri.Rd
+30cf7ef2f3541d1115cdf201024af289 *man/proprVLR.Rd
+e034c70dc15e875cd83c36c9844d484d *src/RcppExports.cpp
+5dd779e7a1530c9f45ff65109ff87f63 *src/backend.cpp
 38a416384180a93d31020bdffb37ccee *tests/testthat.R
+247f6465b01f02caa7c8c8ea380b05b3 *tests/testthat/test-Rcpp.R
 fc05d9b4d260a59e5ee9868520801bd6 *tests/testthat/test-logratio.R
 18bea904004f38c52e8236832c08f21a *tests/testthat/test-perb.R
 fb995286047319340ea951b7fb50b49a *tests/testthat/test-phit.R
 23378d943d79a9bf3fb14ed100337e57 *tests/testthat/test-vlr.R
-d4bfa5c80c697c188330a0c205b86d13 *vignettes/propr-vignette.Rmd
+ea81a5e66116c32b2af3ffcf8f5a27a2 *vignettes/propr-vignette.Rmd

NAMESPACE

@@ -4,18 +4,17 @@ export(dendrogram)
 export(perb)
 export(phit)
 exportClasses(propr)
-exportMethods("$")
 exportMethods("[")
 exportMethods(image)
 exportMethods(plot)
 exportMethods(show)
 exportMethods(subset)
+importFrom(Rcpp,sourceCpp)
 importFrom(grDevices,rainbow)
 importFrom(methods,new)
 importFrom(methods,show)
 importFrom(stats,as.dendrogram)
 importFrom(stats,as.dist)
-importFrom(stats,ecdf)
 importFrom(stats,hclust)
 importFrom(stats,order.dendrogram)
-importFrom(stats,p.adjust)
+useDynLib(propr)

NEWS.md

@@ -1,7 +1,40 @@
+## propr 2.0.0
+---------------------
+* Modified `phit`, `perb` functions
+  * Permutation testing removed
+  * Added `lazyPairs` construct
+    * Slot @pairs not populated until after `[`
+* Modified `propr` Class
+  * `@pairs` slot now integer vector
+    * Populated with `indexPairs` function
+      * Translate with `indexToCoord` function
+  * `show` method updated for `lazyPairs` construct
+  * `[` method completely redesigned
+    * First argument specifies operation
+    * Second argument specifies reference
+    * Indexes @matrix based on these
+  * `subset` method revised but still copy-on-modify
+    * Resets @pairs when called
+  * `$` method removed
+* Visualization tools revised
+  * `plot`, `image`, `dendrogram` methods
+    * Improved performance
+    * Compatible with new @pairs indexing
+    * No longer requires column names
+* Modified backend code
+  * Rephrased code for `proprPhit`
+  * Rephrased code for `proprPerb`
+  * Rephrased code for `proprVLR`
+  * All functions translated into C++
+    * Estimated 80% reduction in RAM overhead
+    * Estimated 100-fold performance increase
+    * ALR methods no longer drop dimension
+    * All have modify-in-place behavior
+
 ## propr 1.1.0
 ---------------------
 * New orientation expected for input data
-  * Updated back-end and vignette accordingly
+  * Updated backend and vignette accordingly
   * Removed redundant transpositions
 * Fixed rare subsetting errors
 * Tweaked plot methods

R/RcppExports.R

@@ -0,0 +1,39 @@
+# This file was generated by Rcpp::compileAttributes
+# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
+
+covRcpp <- function(X, norm_type = 0L) {
+    .Call('propr_covRcpp', PACKAGE = 'propr', X, norm_type)
+}
+
+vlrRcpp <- function(X) {
+    .Call('propr_vlrRcpp', PACKAGE = 'propr', X)
+}
+
+clrRcpp <- function(X) {
+    .Call('propr_clrRcpp', PACKAGE = 'propr', X)
+}
+
+alrRcpp <- function(X, ivar = 0L) {
+    .Call('propr_alrRcpp', PACKAGE = 'propr', X, ivar)
+}
+
+symRcpp <- function(X) {
+    .Call('propr_symRcpp', PACKAGE = 'propr', X)
+}
+
+phiRcpp <- function(X, sym = 1L) {
+    .Call('propr_phiRcpp', PACKAGE = 'propr', X, sym)
+}
+
+rhoRcpp <- function(X, ivar = 0L) {
+    .Call('propr_rhoRcpp', PACKAGE = 'propr', X, ivar)
+}
+
+indexPairs <- function(X, op = "==", ref = 0) {
+    .Call('propr_indexPairs', PACKAGE = 'propr', X, op, ref)
+}
+
+indexToCoord <- function(V, N) {
+    .Call('propr_indexToCoord', PACKAGE = 'propr', V, N)
+}
+

R/propr-backend.R → R/backend.R

@@ -9,22 +9,24 @@ proprPhit <- function(counts, symmetrize = TRUE){
   # Replace zeroes with next smallest number
   counts[counts == 0] <- unique(sort(as.matrix(counts)))[2]
 
-  # Calculate the variance of the log-ratio ("variation array")
-  counts.vlr <- proprVLR(counts)
-  colnames(counts.vlr) <- colnames(counts)
-  rownames(counts.vlr) <- colnames(counts)
+  # Calculate the variance of the log-ratio (i.e., "variation array")
+  mat <- proprVLR(counts)
+  colnames(mat) <- colnames(counts)
+  rownames(mat) <- colnames(counts)
 
-  # Calculate feature variance across clr transformed treatments
+  # Perform clr-transformation of "count matrix"
   counts.clr <- proprCLR(counts)
-  counts.clr.var <- apply(counts.clr, 2, stats::var)
 
   # Sweep out feature clr variance from the variation array
-  phi <- sweep(counts.vlr, 2, counts.clr.var, FUN = "/")
+  for(i in 1:ncol(mat)){
+
+    mat[, i] <- mat[, i] / stats::var(counts.clr[, i])
+  }
 
   # Symmetrize matrix if symmetrize = TRUE
-  if(symmetrize) phi <- proprSym(phi)
+  if(symmetrize) mat <- proprSym(mat)
 
-  return(phi)
+  return(mat)
 }
 
 #' Calculate proportionality metric rho (Erb 2016).
@@ -39,36 +41,34 @@ proprPerb <- function(counts, ivar = 0){
   # Replace zeroes with next smallest number
   counts[counts == 0] <- unique(sort(as.matrix(counts)))[2]
 
-  # Calculate the variance of the log-ratio ("variation array")
-  counts.vlr <- proprVLR(counts)
-  colnames(counts.vlr) <- colnames(counts)
-  rownames(counts.vlr) <- colnames(counts)
+  # Calculate the variance of the log-ratio (i.e., "variation array")
+  mat <- proprVLR(counts)
+  colnames(mat) <- colnames(counts)
+  rownames(mat) <- colnames(counts)
 
+  # Perform *lr-transformation of "count matrix"
   if(ivar != 0){
 
-    # Calculate feature variance across alr transformed treatments
-    counts.vlr <- counts.vlr[-ivar, -ivar] # returns one less dimension
-    counts.alr <- proprALR(counts, ivar = ivar) # returns one less dimension
-    counts.var <- apply(counts.alr, 2, stats::var)
+    mat <- mat[-ivar, -ivar] # returns one less dimension
+    counts.lr <- proprALR(counts, ivar = ivar) # returns one less dimension
 
   }else{
 
-    # Calculate feature variance across clr transformed treatments
-    counts.clr <- proprCLR(counts)
-    counts.var <- apply(counts.clr, 2, stats::var)
+    counts.lr <- proprCLR(counts)
   }
 
-  # Divide variation array by sum of feature variances
-  for(i in 1:ncol(counts.vlr)){
-    for(j in 1:nrow(counts.vlr)){
-      counts.vlr[i, j] <- counts.vlr[i, j] / (counts.var[i] + counts.var[j])
+  # Sweep out feature *lr variance from the variation array
+  var.lr <- apply(counts.lr, 2, stats::var)
+  for(i in 1:ncol(mat)){
+
+    for(j in 1:nrow(mat)){
+
+      # Calculate: rho = 1 - (var(x - y))/(var(x) + var(y))
+      mat[i, j] <- 1 - (mat[i, j] / (var.lr[i] + var.lr[j]))
     }
   }
 
-  # Calculate: p = 1 - (var(x - y))/(var(x) + var(y))
-  rho <- 1 - counts.vlr
-
-  return(rho)
+  return(mat)
 }
 
 #' Calculates the variance of the log of the ratios.
@@ -86,11 +86,16 @@ proprVLR <- function(X, check = FALSE){
     if(any(is.na(X))) stop("NA values found")
   }
 
-  logX <- log(X)
-  Cov    <- stats::var(logX)  ## Note the avoidance of compositions::var
-  D      <- ncol(logX)
-  VarCol <- matrix(rep(diag(Cov), D), ncol = D)
-  return(-2 * Cov + VarCol + t(VarCol))
+  X <- log(X)
+  X <- stats::var(X)
+  X.diag <- diag(X)
+
+  for(col in 1:ncol(X)){
+
+    X[, col] <- -2 * X[, col] + X.diag + X.diag[col]
+  }
+
+  return(X)
 }
 
 #' Calculates the centered log-ratio transformation.

R/propr-classes.R → R/classes.R

@@ -1,17 +1,21 @@
+#' @useDynLib propr
+#' @importFrom Rcpp sourceCpp
+NULL
+
 #' The propr Package
 #'
 #' @description
 #' Welcome to the \code{propr} package!
 #'
 #' To learn more about how to calculate metrics of proportionality,
-#'  see the help file for the method definitions \code{\link{phit}}
+#'  see the help file for the functions \code{\link{phit}}
 #'  and \code{\link{perb}}.
 #'
 #' To learn more about the resultant \code{propr} class object, see
 #'  the help file for the class definition \code{\link{propr-class}}.
 #'
 #' To learn more about compositional data analysis, and its relevance
-#'  to biological count data, see the attached vignette.
+#'  to biological count data, see the bundled vignette.
 #'
 #' To learn more about \code{propr} class methods, see below.
 #'
@@ -20,27 +24,28 @@ NULL
 
 #' An S4 class to hold results from proportionality analysis.
 #'
-#' @slot counts A data.frame. Stores the original "count matrix" input.
-#' @slot logratio A data.frame. Stores the log-ratio transformed "count matrix".
-#' @slot matrix A matrix. Stores the proportionality matrix calculated by \code{phit} or \code{perb}.
-#' @slot pairs A data.frame. Projects the proportionality matrix pairwise.
+#' @slot counts A matrix. Stores the original "count matrix" input.
+#' @slot logratio A matrix. Stores the log-ratio transformed "count matrix".
+#' @slot matrix A matrix. Stores the proportionality matrix calculated by
+#'  \code{phiRcpp} or \code{rhoRcpp}.
+#' @slot pairs A vector. Indexes the proportionality metrics of interest.
 #'
 #' @seealso \code{\link{propr}}, \code{\link{phit}}, \code{\link{perb}}
 #'
 #' @examples
-#' randomNum <- sample(1:1000, size = 25 * 10, replace = TRUE)
-#' counts <- matrix(randomNum, nrow = 25, ncol = 10)
-#' prop <- perb(counts, ivar = 0, iter = 0)
-#' prop[1:5, ]
-#' prop$prop
-#' prop[1:5, "prop"]
-#' subset(prop, 1:5)
+#' set.seed(12345)
+#' N <- 100
+#' X <- data.frame(a=(1:N), b=(1:N) * rnorm(N, 10, 0.1),
+#'                 c=(N:1), d=(N:1) * rnorm(N, 10, 1.0))
+#' rho <- perb(X, ivar = 0)
+#' rho[">", .99]
+#' subset(rho, 1:2)
 #' @export
 setClass("propr",
          slots = c(
-           counts = "data.frame",
-           logratio = "data.frame",
+           counts = "matrix",
+           logratio = "matrix",
            matrix = "matrix",
-           pairs = "data.frame"
+           pairs = "numeric"
          )
 )