implemented density plots other than for PC1 & PC2

CoDaSeq/R/codaSeq.PCAplot.r

@@ -23,10 +23,10 @@
 #'   `load.sym` (default: `TRUE`).
 #' @param plot.ellipses Character vector indicating whether or not to draw
 #'   confidence ellipses around sample *or* loading groups. Must be one of either
-#'   `"groups"` or `"loadings"`, or `NULL`.
+#'   `"groups"` or `"loadings"`, or `NULL` (default: `NULL`).
 #' @param plot.density Logical value indicating whether or not to draw density
 #'   plots for the specified principal components above and beside the main
-#'   biplot.
+#'   biplot (default: `NULL`).
 #' @param grp A list of groups where each element is a vector containing the
 #'   indices of group members (default: `NULL`).
 #' @param grp.col A vector of the same length as `grp` containing colours for
@@ -40,7 +40,7 @@
 #'     each element of `grp.sym` paired with the corresponding element of 
 #'     `grp`).
 #'   * A character vector equal to `"text"` (plots samples as text, with the 
-#'     label set to `rownames(pcx$x)`).
+#'     labels set to `rownames(pcx$x)`).
 #' @param grp.cex A numeric value indicating the relative size of the group
 #'   symbols or text to be plotted (default: `1`).
 #' @param load.grp A list of loading groups where each element is a vector
@@ -57,26 +57,29 @@
 #'     each element of `load.sym` paired with the corresponding element of 
 #'     `load.grp`).
 #'   * A character vector equal to `"text"` (plots variable loadings as text,
-#'     with the label set to `rownames(pcx$rotation)`).
+#'     with the labels set to `rownames(pcx$rotation)`).
 #' @param load.cex A numeric value indicating the relative size of the
 #'   loading symbols or text to be plotted (default: `0.5`).
 #' @param PC A numeric vector of length = 2 indicating which prinicpal
 #'   components should be plotted (default: `c(1,2)`)
 #' @param plot.legend A character string equal to either `"groups"` or
 #'   `"loadings"`, or NULL, indicating whether to draw a legend for groups,
-#'   loadings or neither (default: `NULL`).
-#' @param leg.position A character string equal to one of the following:
-#'   `"topleft"`, `"top"`, `"topright"`, `"right"`, `"bottomright"`, `"bottom"`,
-#'   `"bottomleft"`, `"left"`, or `"center"`. Cannot be called in conjunction
-#'   with `leg.xy` (default: `NULL`).
+#'   loadings or neither (default: `NULL`). If you wish to draw legends for
+#'   both groups and loadings, you can call `legend()` immediately after
+#'   `codaSeq.PCAplot()`, adjusting the `x` and `y` arguments manually
+#'    (start at zero and play around with the numbers).
+#' @param leg.position A character vector indicating legend position presets,
+#'   equal to one of the following: `"topleft"`, `"top"`, `"topright"`, 
+#'   `"right"`, `"bottomright"`, `"bottom"`, `"bottomleft"`, `"left"`, or 
+#'   `"center"`. Cannot be called alongside with `leg.xy` (default: `NULL`).
 #' @param leg.xy A numeric vector of length = 2, specifying the x and y
 #'   coordinates at which to draw the top-right corner of the legend box. Cannot
-#'   be called in conjunctionn with `leg.position` (default: `NULL`)
+#'   be called in conjunction with `leg.position` (default: `NULL`).
 #' @param leg.cex A numeric value indicating the relative size of the legend
 #'   text (default: `0.55`).
 #' @param leg.columns A numeric calue indicating the number of columns to split
 #'   legend items into (default: `1`)
-#' @param title A character string containing the desired title of the biplot
+#' @param title A character vector containing the desired title of the biplot
 #'   (default: `""`).
 #'
 #' @return Returns a plot showing samples and/or loadings as specified by the
@@ -146,7 +149,7 @@
 #' 
 #' # Bayesian-multiplicative replacement of count-zeros 
 #' clr.input<-cmultRepl(t(ak_op),label = "0",
-#'                      method = "CZM",output = "p-counts")
+#'                      method = "CZM",, z.warning = 0.99)
 #' 
 #' # CLR-transformation using codaSeq.clr
 #' clr.data<-codaSeq.clr(t(clr.input), IQLR = FALSE,
@@ -388,8 +391,8 @@ codaSeq.PCAplot <- function(pcx, plot.groups=FALSE, plot.loadings=TRUE, plot.ell
     if(plot.density=="groups"){
       list.group<-list()
       for(k in 1:length(grp)){
-        points.pc1<-pcx$x[,1][grp[[k]]]
-        points.pc2<-pcx$x[,2][grp[[k]]]
+        points.pc1<-pcx$x[,PC[1]][grp[[k]]]
+        points.pc2<-pcx$x[,PC[2]][grp[[k]]]
         list.group[[names(grp)[k]]]<-as.data.frame(cbind(points.pc1,points.pc2))
       }
 
@@ -433,8 +436,8 @@ codaSeq.PCAplot <- function(pcx, plot.groups=FALSE, plot.loadings=TRUE, plot.ell
     } else if(plot.density=="loadings"){
       list.loadings<-list()
       for (k in 1:length(load.grp)) {
-        points.pc1<-pcx$rotation[,1][load.grp[[k]]]*scale.factor.1
-        points.pc2<-pcx$rotation[,2][load.grp[[k]]]*scale.factor.2
+        points.pc1<-pcx$rotation[,PC[1]][load.grp[[k]]]*scale.factor.1
+        points.pc2<-pcx$rotation[,PC[2]][load.grp[[k]]]*scale.factor.2
         list.loadings[[names(load.grp)[k]]]<-as.data.frame(cbind(points.pc1,points.pc2))
       }
 

CoDaSeq/R/codaSeq.PCAvalues.R

@@ -25,7 +25,7 @@
 #' data("ak_op")      # feature table: 4347 OTU x 30 samples (15x ak, 15x op)
 #' 
 #' # Bayesian-multiplicative replacement of count-zeros 
-#' clr.input<-cmultRepl(t(ak_op),label = "0",
+#' clr.input<-cmultRepl(t(ak_op),label = "0", z.warning = 0.99,
 #'                      method = "CZM",output = "p-counts")
 #' 
 #' # CLR-transformation using codaSeq.clr

CoDaSeq/man/codaSeq.PCAplot.rd

@@ -26,11 +26,11 @@ depending on \code{grp.sym} (default: \code{FALSE}).}
 
 \item{plot.ellipses}{Character vector indicating whether or not to draw
 confidence ellipses around sample \emph{or} loading groups. Must be one of either
-\code{"groups"} or \code{"loadings"}, or \code{NULL}.}
+\code{"groups"} or \code{"loadings"}, or \code{NULL} (default: \code{NULL}).}
 
 \item{plot.density}{Logical value indicating whether or not to draw density
 plots for the specified principal components above and beside the main
-biplot.}
+biplot (default: \code{NULL}).}
 
 \item{grp}{A list of groups where each element is a vector containing the
 indices of group members (default: \code{NULL}).}
@@ -48,7 +48,7 @@ specified values to set the  \code{pch} argument on a per-group basis, with
 each element of \code{grp.sym} paired with the corresponding element of
 \code{grp}).
 \item A character vector equal to \code{"text"} (plots samples as text, with the
-label set to \code{rownames(pcx$x)}).
+labels set to \code{rownames(pcx$x)}).
 }}
 
 \item{grp.cex}{A numeric value indicating the relative size of the group
@@ -71,7 +71,7 @@ specified values to set the  \code{pch} argument on a per-group basis, with
 each element of \code{load.sym} paired with the corresponding element of
 \code{load.grp}).
 \item A character vector equal to \code{"text"} (plots variable loadings as text,
-with the label set to \code{rownames(pcx$rotation)}).
+with the labels set to \code{rownames(pcx$rotation)}).
 }}
 
 \item{load.cex}{A numeric value indicating the relative size of the
@@ -82,24 +82,27 @@ components should be plotted (default: \code{c(1,2)})}
 
 \item{plot.legend}{A character string equal to either \code{"groups"} or
 \code{"loadings"}, or NULL, indicating whether to draw a legend for groups,
-loadings or neither (default: \code{NULL}).}
+loadings or neither (default: \code{NULL}). If you wish to draw legends for
+both groups and loadings, you can call \code{legend()} immediately after
+\code{codaSeq.PCAplot()}, adjusting the \code{x} and \code{y} arguments manually
+(start at zero and play around with the numbers).}
 
-\item{leg.position}{A character string equal to one of the following:
-\code{"topleft"}, \code{"top"}, \code{"topright"}, \code{"right"}, \code{"bottomright"}, \code{"bottom"},
-\code{"bottomleft"}, \code{"left"}, or \code{"center"}. Cannot be called in conjunction
-with \code{leg.xy} (default: \code{NULL}).}
+\item{leg.position}{A character vector indicating legend position presets,
+equal to one of the following: \code{"topleft"}, \code{"top"}, \code{"topright"},
+\code{"right"}, \code{"bottomright"}, \code{"bottom"}, \code{"bottomleft"}, \code{"left"}, or
+\code{"center"}. Cannot be called alongside with \code{leg.xy} (default: \code{NULL}).}
 
 \item{leg.xy}{A numeric vector of length = 2, specifying the x and y
 coordinates at which to draw the top-right corner of the legend box. Cannot
-be called in conjunctionn with \code{leg.position} (default: \code{NULL})}
+be called in conjunction with \code{leg.position} (default: \code{NULL}).}
 
 \item{leg.cex}{A numeric value indicating the relative size of the legend
 text (default: \code{0.55}).}
 
 \item{leg.columns}{A numeric calue indicating the number of columns to split
 legend items into (default: \code{1})}
 
-\item{title}{A character string containing the desired title of the biplot
+\item{title}{A character vector containing the desired title of the biplot
 (default: \code{""}).}
 }
 \value{
@@ -152,7 +155,7 @@ symbols<-c(rep(17,13),rep(16,13),11)
 
 # Bayesian-multiplicative replacement of count-zeros 
 clr.input<-cmultRepl(t(ak_op),label = "0",
-                     method = "CZM",output = "p-counts")
+                     method = "CZM",, z.warning = 0.99)
 
 # CLR-transformation using codaSeq.clr
 clr.data<-codaSeq.clr(t(clr.input), IQLR = FALSE,

CoDaSeq/vignettes/CoDaSeq_vignette.Rnw

@@ -74,7 +74,7 @@ We now replace 0 counts in the dataset with imputed values using the Count Zero
 # from the zCompositions package
 # the table is transposed t() to make the samples by row
 # all further analyses have this orientation
-f.n0 <- cmultRepl(t(f), label=0, method="CZM")
+f.n0 <- cmultRepl(t(f), label=0, method="CZM", z.warning = 0.99)
 
 # perform the centered log-ratio transformation
 f.clr <- codaSeq.clr(f.n0, samples.by.row=TRUE)
@@ -101,7 +101,7 @@ par(mfrow=c(3,4))
 
 label="ALL"
 f <- codaSeq.filter(ak_op, min.reads=1000, samples.by.row=FALSE, min.count=1)
-f.n0 <- cmultRepl(t(f), label=0, method="CZM")
+f.n0 <- cmultRepl(t(f), label=0, method="CZM", z.warning = 0.99)
 # perform the centered log-ratio transformation
 f.clr <- codaSeq.clr(f.n0, samples.by.row=TRUE)
 f.pcx <- prcomp(f.clr)
@@ -110,7 +110,7 @@ codaSeq.PCAplot(f.pcx, title=label, plot.groups=TRUE, grp.col=rbcol,
 
 label="min.count=100"
 f <- codaSeq.filter(ak_op, min.reads=1000, min.count=10, samples.by.row=FALSE)
-f.n0 <- cmultRepl(t(f), label=0, method="CZM")
+f.n0 <- cmultRepl(t(f), label=0, method="CZM", z.warning = 0.99)
 # perform the centered log-ratio transformation
 f.clr <- codaSeq.clr(f.n0, samples.by.row=TRUE)
 f.pcx <- prcomp(f.clr)
@@ -119,7 +119,7 @@ codaSeq.PCAplot(f.pcx, title=label, plot.groups=TRUE, grp.col=rbcol,
 
 label="min.prop=0.01"
 f <- codaSeq.filter(ak_op, min.reads=1000, min.prop=0.01, samples.by.row=FALSE)
-f.n0 <- cmultRepl(t(f), label=0, method="CZM")
+f.n0 <- cmultRepl(t(f), label=0, method="CZM", z.warning = 0.99)
 # perform the centered log-ratio transformation
 f.clr <- codaSeq.clr(f.n0, samples.by.row=TRUE)
 f.pcx <- prcomp(f.clr)
@@ -128,7 +128,7 @@ codaSeq.PCAplot(f.pcx, title=label, plot.groups=TRUE, grp.col=rbcol,
 
 label="max.prop=0.01"
 f <- codaSeq.filter(ak_op, min.reads=1000, min.prop=0.001, max.prop=0.01, samples.by.row=FALSE)
-f.n0 <- cmultRepl(t(f), label=0, method="CZM")
+f.n0 <- cmultRepl(t(f), label=0, method="CZM", z.warning = 0.99)
 # perform the centered log-ratio transformation
 f.clr <- codaSeq.clr(f.n0, samples.by.row=TRUE)
 f.pcx <- prcomp(f.clr)
@@ -137,7 +137,7 @@ codaSeq.PCAplot(f.pcx, title=label, plot.groups=TRUE, grp.col=rbcol,
 
 label="var.filt=TRUE"
 f <- codaSeq.filter(ak_op, min.reads=1000, var.filt=TRUE, samples.by.row=FALSE)
-f.n0 <- cmultRepl(t(f), label=0, method="CZM")
+f.n0 <- cmultRepl(t(f), label=0, method="CZM", z.warning = 0.99)
 # perform the centered log-ratio transformation
 f.clr <- codaSeq.clr(f.n0, samples.by.row=TRUE)
 f.pcx <- prcomp(f.clr)
@@ -146,7 +146,7 @@ codaSeq.PCAplot(f.pcx, title=label, plot.groups=TRUE, grp.col=rbcol,
 
 label="min.occurrence=0.5"
 f <- codaSeq.filter(ak_op, min.reads=1000, min.occurrence=0.5, samples.by.row=FALSE)
-f.n0 <- cmultRepl(t(f), label=0, method="CZM")
+f.n0 <- cmultRepl(t(f), label=0, method="CZM", z.warning = 0.99)
 # perform the centered log-ratio transformation
 f.clr <- codaSeq.clr(f.n0, samples.by.row=TRUE)
 f.pcx <- prcomp(f.clr)