@@ -46,21 +46,21 @@

 #' fit = fitFeatureModel(obj = lungTrim,mod=mod)

 #' head(MRtable(fit))

 #'

-MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,

+MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj@taxa,

     uniqueNames=FALSE,adjustMethod="fdr",group=0,eff=0,numberEff=FALSE,ncounts=0,file=NULL){

-    if(length(grep("fitFeatureModel",obj$call))){

-        groups = factor(obj$design[,by])

+    if(length(grep("fitFeatureModel",obj@call))){

+        groups = factor(obj@design[,by])

         by = "logFC"; coef = 1:2;

-        tb = data.frame(logFC=obj$fitZeroLogNormal$logFC,se=obj$fitZeroLogNormal$se)

-        p  = obj$pvalues

+        tb = data.frame(logFC=obj@fitZeroLogNormal$logFC,se=obj@fitZeroLogNormal$se)

+        p  = obj@pvalues

     } else {

-        tb = obj$fit$coefficients

+        tb = obj@fit$coefficients

         if(is.null(coef)){

             coef = 1:ncol(tb)

         }

-        p=obj$eb$p.value[,by]

-        groups = factor(obj$fit$design[,by])

+        p=obj@eb$p.value[,by]

+        groups = factor(obj@fit$design[,by])

         if(eff>0){

             effectiveSamples = calculateEffectiveSamples(obj)

             if(numberEff == FALSE){

@@ -79,7 +79,7 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,

         }

     }

     padj = p.adjust(p,method=adjustMethod)

-    cnts = obj$counts

+    cnts = obj@counts

     posIndices = cnts>0

     np0 = rowSums(posIndices[,groups==0])

@@ -126,5 +126,5 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,

         mat2 = rbind(nm,mat2)

         write(t(mat2),ncolumns=ncol(mat2),file=file,sep="\t")

     }

-    invisible(as.data.frame(mat))

+    return(as.data.frame(mat))

 }

@@ -105,7 +105,7 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,

         np=rowSums(cbind(np0,np1))

         valid = intersect(valid,which(np>=ncounts))

     }

-    srt = srt[which(srt%in%valid)][1:number]

+    srt = srt[which(srt%in%valid)][1:min(number,nrow(tb))]

     mat = cbind(np0,np1)

     mat = cbind(mat,nc0)

@@ -30,24 +30,22 @@

 #' @param file Name of file, including location, to save the table.

 #' @return Table of the top-ranked features determined by the linear fit's

 #' coefficient.

-#' @seealso \code{\link{fitZig}} \code{\link{fitFeatureModel}} \code{\link{MRcoefs}}

+#' @seealso \code{\link{fitZig}} \code{\link{fitFeatureModel}} \code{\link{MRcoefs}} \code{\link{MRfulltable}}

 #' @examples

 #' 

 #' data(lungData)

 #' k = grep("Extraction.Control",pData(lungData)$SampleType)

 #' lungTrim = lungData[,-k]

-#' k = which(rowSums(MRcounts(lungTrim)>0)<10)

-#' lungTrim = lungTrim[-k,]

-#' cumNorm(lungTrim)

+#' lungTrim=filterData(lungTrim,present=30)

+#' lungTrim=cumNorm(lungTrim,p=0.5)

 #' smokingStatus = pData(lungTrim)$SmokingStatus

 #' mod = model.matrix(~smokingStatus)

-#' settings = zigControl(maxit=1,verbose=FALSE)

-#' fit = fitZig(obj = lungTrim,mod=mod,control=settings)

+#' fit = fitZig(obj = lungTrim,mod=mod)

 #' head(MRtable(fit))

 #' ####

 #' fit = fitFeatureModel(obj = lungTrim,mod=mod)

 #' head(MRtable(fit))

-#' 

+#'

 MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,

     uniqueNames=FALSE,adjustMethod="fdr",group=0,eff=0,numberEff=FALSE,ncounts=0,file=NULL){

@@ -8,8 +8,7 @@

 #' ensure significant features called are moderately present.

 #' 

 #' 

-#' @param obj A list containing the linear model fit produced by lmFit through

-#' fitZig.

+#' @param obj Output of fitFeatureModel or fitZig.

 #' @param by Column number or column name specifying which coefficient or

 #' contrast of the linear model is of interest.

 #' @param coef Column number(s) or column name(s) specifying which coefficient

@@ -17,7 +16,7 @@

 #' @param number The number of bacterial features to pick out.

 #' @param taxa Taxa list.

 #' @param uniqueNames Number the various taxa.

-#' @param adjust.method Method to adjust p-values by. Default is "FDR". Options

+#' @param adjustMethod Method to adjust p-values by. Default is "FDR". Options

 #' include "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr",

 #' "none". See \code{\link{p.adjust}} for more details.

 #' @param group One of five choices, 0,1,2,3,4. 0: the sort is ordered by a

@@ -27,11 +26,11 @@

 #' of the coefficient fit in increasing order. 4: no sorting.

 #' @param eff Filter features to have at least a "eff" quantile or number of effective samples.

 #' @param numberEff Boolean, whether eff should represent quantile (default/FALSE) or number.

-#' @param counts Filter features to have at least 'counts' of counts.

+#' @param ncounts Filter features to have at least 'counts' of counts.

 #' @param file Name of file, including location, to save the table.

 #' @return Table of the top-ranked features determined by the linear fit's

 #' coefficient.

-#' @seealso \code{\link{fitZig}} \code{\link{MRcoefs}}

+#' @seealso \code{\link{fitZig}} \code{\link{fitFeatureModel}} \code{\link{MRcoefs}}

 #' @examples

 #' 

 #' data(lungData)

@@ -45,32 +44,51 @@

 #' settings = zigControl(maxit=1,verbose=FALSE)

 #' fit = fitZig(obj = lungTrim,mod=mod,control=settings)

 #' head(MRtable(fit))

+#' ####

+#' fit = fitFeatureModel(obj = lungTrim,mod=mod)

+#' head(MRtable(fit))

 #' 

-MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,adjust.method="fdr",group=0,eff=0,numberEff=FALSE,counts=0,file=NULL){

-    tb = obj$fit$coefficients

-    tx = as.character(taxa);

+MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,

+    uniqueNames=FALSE,adjustMethod="fdr",group=0,eff=0,numberEff=FALSE,ncounts=0,file=NULL){

+

+    if(length(grep("fitFeatureModel",obj$call))){

+        groups = factor(obj$design[,by])

+        by = "logFC"; coef = 1:2;

+        tb = data.frame(logFC=obj$fitZeroLogNormal$logFC,se=obj$fitZeroLogNormal$se)

+        p  = obj$pvalues

+    } else {

+        tb = obj$fit$coefficients

+        if(is.null(coef)){

+            coef = 1:ncol(tb)

+        }

+        p=obj$eb$p.value[,by]

+        groups = factor(obj$fit$design[,by])

+        if(eff>0){

+            effectiveSamples = calculateEffectiveSamples(obj)

+            if(numberEff == FALSE){

+                valid = which(effectiveSamples>=quantile(effectiveSamples,p=eff,na.rm=TRUE))

+            } else {

+                valid = which(effectiveSamples>=eff)

+            }

+        }        

+    }

+    tx = as.character(taxa)

     if(uniqueNames==TRUE){

         for (nm in unique(tx)) {

             ii=which(tx==nm)

-        tx[ii]=paste(tx[ii],seq_along(ii),sep=":")

+            tx[ii]=paste(tx[ii],seq_along(ii),sep=":")

         }

     }

-

-    if(is.null(coef)){coef = 1:ncol(tb);}

-

-    p=obj$eb$p.value[,by];

-    padj = p.adjust(p,method=adjust.method);

-    

-    groups = factor(obj$fit$design[,by])

-    cnts = obj$counts;

-    yy = cnts>0;

+    padj = p.adjust(p,method=adjustMethod)

+    cnts = obj$counts

+    posIndices = cnts>0

-    np0 = rowSums(yy[,groups==0]);

-    np1 = rowSums(yy[,groups==1]);

+    np0 = rowSums(posIndices[,groups==0])

+    np1 = rowSums(posIndices[,groups==1])

-    nc0 = rowSums(cnts[,groups==0]);

-    nc1 = rowSums(cnts[,groups==1]);

+    nc0 = rowSums(cnts[,groups==0])

+    nc1 = rowSums(cnts[,groups==1])

     if(group==0){

         srt = order(abs(tb[,by]),decreasing=TRUE)

@@ -81,37 +99,28 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,a

     } else if(group==3){

         srt = order(p,decreasing=FALSE)

     } else {

-        srt = 1:length(padj);

+        srt = 1:length(padj)

     }

-    valid = 1:length(padj);

-    if(eff>0){

-        effectiveSamples = calculateEffectiveSamples(obj);

-        if(numberEff == FALSE){

-            valid = which(effectiveSamples>=quantile(effectiveSamples,p=eff,na.rm=TRUE));

-        } else {

-            valid = which(effectiveSamples>=eff);

-        }

+    valid = 1:length(padj)

+    if(ncounts>0){

+        np=rowSums(cbind(np0,np1))

+        valid = intersect(valid,which(np>=ncounts))

     }

-    if(counts>0){

-        np=rowSums(cbind(np0,np1));

-        valid = intersect(valid,which(np>=counts));

-    }

-

-    srt = srt[which(srt%in%valid)][1:number];

+    srt = srt[which(srt%in%valid)][1:number]

-    mat = cbind(np0,np1);

-    mat = cbind(mat,nc0);

-    mat = cbind(mat,nc1);

-    mat = cbind(mat,tb[,coef]);

-    mat = cbind(mat,p);

-    mat = cbind(mat,padj);

-    rownames(mat) = tx;

-    mat = mat[srt,];

+    mat = cbind(np0,np1)

+    mat = cbind(mat,nc0)

+    mat = cbind(mat,nc1)

+    mat = cbind(mat,tb[,coef])

+    mat = cbind(mat,p)

+    mat = cbind(mat,padj)

+    rownames(mat) = tx

+    mat = mat[srt,]

     nm = c("+samples in group 0","+samples in group 1","counts in group 0",

-        "counts in group 1",colnames(tb)[coef],"pvalues","adjPvalues");

-    colnames(mat) = nm;

+        "counts in group 1",colnames(tb)[coef],"pvalues","adjPvalues")

+    colnames(mat) = nm

     if(!is.null(file)){

         nm = c("Taxa",nm)

@@ -118,7 +118,6 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,a

         mat2 = cbind(rownames(mat),mat)

         mat2 = rbind(nm,mat2)

         write(t(mat2),ncolumns=ncol(mat2),file=file,sep="\t")

-    } else{

-        return(as.data.frame(mat))

     }

+    invisible(as.data.frame(mat))

 }

@@ -66,11 +66,11 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,a

     cnts = obj$counts;

     yy = cnts>0;

-    np0 = rowSums(yy[,groups==unique(groups)[1]]);

-    np1 = rowSums(yy[,groups==unique(groups)[2]]);

+    np0 = rowSums(yy[,groups==0]);

+    np1 = rowSums(yy[,groups==1]);

-    nc0 = rowSums(cnts[,groups==unique(groups)[1]]);

-    nc1 = rowSums(cnts[,groups==unique(groups)[2]]);

+    nc0 = rowSums(cnts[,groups==0]);

+    nc1 = rowSums(cnts[,groups==1]);

     if(group==0){

         srt = order(abs(tb[,by]),decreasing=TRUE)

@@ -109,9 +109,8 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,a

     rownames(mat) = tx;

     mat = mat[srt,];

-    nm = c(paste("+samples in group",unique(groups)[1]),paste("+samples in group",unique(groups)[2]),

-    paste("counts in group",unique(groups)[1]),paste("counts in group",unique(groups)[2]),

-    colnames(tb)[coef],"pvalues","adjPvalues");

+    nm = c("+samples in group 0","+samples in group 1","counts in group 0",

+        "counts in group 1",colnames(tb)[coef],"pvalues","adjPvalues");

     colnames(mat) = nm;

     if(!is.null(file)){

@@ -81,10 +81,10 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,a

     } else if(group==3){

         srt = order(p,decreasing=FALSE)

     } else {

-        srt = 1:length(np0);

+        srt = 1:length(padj);

     }

-    valid = 1:length(np0);

+    valid = 1:length(padj);

     if(eff>0){

         effectiveSamples = calculateEffectiveSamples(obj);

         if(numberEff == FALSE){

@@ -111,7 +111,7 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,a

     nm = c(paste("+samples in group",unique(groups)[1]),paste("+samples in group",unique(groups)[2]),

     paste("counts in group",unique(groups)[1]),paste("counts in group",unique(groups)[2]),

-    colnames(tb)[coef],"pValue","adjPvalue");

+    colnames(tb)[coef],"pvalues","adjPvalues");

     colnames(mat) = nm;

     if(!is.null(file)){

@@ -20,13 +20,14 @@

 #' @param adjust.method Method to adjust p-values by. Default is "FDR". Options

 #' include "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr",

 #' "none". See \code{\link{p.adjust}} for more details.

-#' @param group One of three choices, 0,1,2,3,4. 0: the sort is ordered by a

+#' @param group One of five choices, 0,1,2,3,4. 0: the sort is ordered by a

 #' decreasing absolute value coefficient fit. 1: the sort is ordered by the raw

 #' coefficient fit in decreasing order. 2: the sort is ordered by the raw

 #' coefficient fit in increasing order. 3: the sort is ordered by the p-value

 #' of the coefficient fit in increasing order. 4: no sorting.

-#' @param eff Restrict samples to have at least a "eff" quantile or number of effective samples.

+#' @param eff Filter features to have at least a "eff" quantile or number of effective samples.

 #' @param numberEff Boolean, whether eff should represent quantile (default/FALSE) or number.

+#' @param counts Filter features to have at least 'counts' of counts.

 #' @param file Name of file, including location, to save the table.

 #' @return Table of the top-ranked features determined by the linear fit's

 #' coefficient.

@@ -45,7 +46,7 @@

 #' fit = fitZig(obj = lungTrim,mod=mod,control=settings)

 #' head(MRtable(fit))

 #' 

-MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,adjust.method="fdr",group=0,eff=0,numberEff=FALSE,file=NULL){

+MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,adjust.method="fdr",group=0,eff=0,numberEff=FALSE,counts=0,file=NULL){

     tb = obj$fit$coefficients

     tx = as.character(taxa);

@@ -83,12 +84,20 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,a

         srt = 1:length(np0);

     }

-    effectiveSamples = calculateEffectiveSamples(obj);

-    if(numberEff == FALSE){

-        valid = which(effectiveSamples>=quantile(effectiveSamples,p=eff,na.rm=TRUE));

-    } else {

-        valid = which(effectiveSamples>=eff);

+    valid = 1:length(np0);

+    if(eff>0){

+        effectiveSamples = calculateEffectiveSamples(obj);

+        if(numberEff == FALSE){

+            valid = which(effectiveSamples>=quantile(effectiveSamples,p=eff,na.rm=TRUE));

+        } else {

+            valid = which(effectiveSamples>=eff);

+        }

     }

+    if(counts>0){

+        np=rowSums(cbind(np0,np1));

+        valid = intersect(valid,which(np>=counts));

+    }

+

     srt = srt[which(srt%in%valid)][1:number];

     mat = cbind(np0,np1);

@@ -58,7 +58,7 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,a

     if(is.null(coef)){coef = 1:ncol(tb);}

-    p=obj$eb$p[,by];

+    p=obj$eb$p.value[,by];

     padj = p.adjust(p,method=adjust.method);

     groups = factor(obj$fit$design[,by])

@@ -20,13 +20,14 @@

 #' @param adjust.method Method to adjust p-values by. Default is "FDR". Options

 #' include "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr",

 #' "none". See \code{\link{p.adjust}} for more details.

-#' @param group One of three choices, 0,1,2. 0: the sort is ordered by a

+#' @param group One of three choices, 0,1,2,3,4. 0: the sort is ordered by a

 #' decreasing absolute value coefficient fit. 1: the sort is ordered by the raw

 #' coefficient fit in decreasing order. 2: the sort is ordered by the raw

 #' coefficient fit in increasing order. 3: the sort is ordered by the p-value

-#' of the coefficient fit in increasing order.

-#' @param eff Restrict samples to have at least a "eff" quantile effective samples.

-#' @param output Name of output file, including location, to save the table.

+#' of the coefficient fit in increasing order. 4: no sorting.

+#' @param eff Restrict samples to have at least a "eff" quantile or number of effective samples.

+#' @param numberEff Boolean, whether eff should represent quantile (default/FALSE) or number.

+#' @param file Name of file, including location, to save the table.

 #' @return Table of the top-ranked features determined by the linear fit's

 #' coefficient.

 #' @seealso \code{\link{fitZig}} \code{\link{MRcoefs}}

@@ -44,7 +45,7 @@

 #' fit = fitZig(obj = lungTrim,mod=mod,control=settings)

 #' head(MRtable(fit))

 #' 

-MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,adjust.method="fdr",group=0,eff=0,output=NULL){

+MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,adjust.method="fdr",group=0,eff=0,numberEff=FALSE,file=NULL){

     tb = obj$fit$coefficients

     tx = as.character(taxa);

@@ -78,10 +79,16 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,a

         srt = order((tb[,by]),decreasing=FALSE)

     } else if(group==3){

         srt = order(p,decreasing=FALSE)

+    } else {

+        srt = 1:length(np0);

     }

     effectiveSamples = calculateEffectiveSamples(obj);

-    valid = which(effectiveSamples>=quantile(effectiveSamples,p=eff,na.rm=TRUE));

+    if(numberEff == FALSE){

+        valid = which(effectiveSamples>=quantile(effectiveSamples,p=eff,na.rm=TRUE));

+    } else {

+        valid = which(effectiveSamples>=eff);

+    }

     srt = srt[which(srt%in%valid)][1:number];

     mat = cbind(np0,np1);

@@ -98,11 +105,11 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,a

     colnames(tb)[coef],"pValue","adjPvalue");

     colnames(mat) = nm;

-    if(!is.null(output)){

+    if(!is.null(file)){

         nm = c("Taxa",nm)

         mat2 = cbind(rownames(mat),mat)

         mat2 = rbind(nm,mat2)

-        write(t(mat2),ncolumns=ncol(mat2),file=output,sep="\t")

+        write(t(mat2),ncolumns=ncol(mat2),file=file,sep="\t")

     } else{

         return(as.data.frame(mat))

     }

@@ -25,6 +25,7 @@

 #' coefficient fit in decreasing order. 2: the sort is ordered by the raw

 #' coefficient fit in increasing order. 3: the sort is ordered by the p-value

 #' of the coefficient fit in increasing order.

+#' @param eff Restrict samples to have at least a "eff" quantile effective samples.

 #' @param output Name of output file, including location, to save the table.

 #' @return Table of the top-ranked features determined by the linear fit's

 #' coefficient.

@@ -43,14 +44,14 @@

 #' fit = fitZig(obj = lungTrim,mod=mod,control=settings)

 #' head(MRtable(fit))

 #' 

-MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,adjust.method="fdr",group=0,output=NULL){

+MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,adjust.method="fdr",group=0,eff=0,output=NULL){

     tb = obj$fit$coefficients

     tx = as.character(taxa);

     if(uniqueNames==TRUE){

         for (nm in unique(tx)) {

             ii=which(tx==nm)

-            tx[ii]=paste(tx[ii],seq_along(ii),sep=":")

+        tx[ii]=paste(tx[ii],seq_along(ii),sep=":")

         }

     }

@@ -70,28 +71,32 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,a

     nc1 = rowSums(cnts[,groups==unique(groups)[2]]);

     if(group==0){

-        srt = order(abs(tb[,by]),decreasing=TRUE)[1:number]

+        srt = order(abs(tb[,by]),decreasing=TRUE)

     } else if(group==1){

-        srt = order((tb[,by]),decreasing=TRUE)[1:number]

+        srt = order((tb[,by]),decreasing=TRUE)

     } else if(group==2){

-        srt = order((tb[,by]),decreasing=FALSE)[1:number]

+        srt = order((tb[,by]),decreasing=FALSE)

     } else if(group==3){

-        srt = order(p,decreasing=FALSE)[1:number]

+        srt = order(p,decreasing=FALSE)

     }

-    mat = cbind(np0,np1)

-    mat = cbind(mat,nc0)

-    mat = cbind(mat,nc1)

-    mat = cbind(mat,tb[,coef])

-    mat = cbind(mat,p)

-    mat = cbind(mat,padj)

+    effectiveSamples = calculateEffectiveSamples(obj);

+    valid = which(effectiveSamples>=quantile(effectiveSamples,p=eff,na.rm=TRUE));

+    srt = srt[which(srt%in%valid)][1:number];

+

+    mat = cbind(np0,np1);

+    mat = cbind(mat,nc0);

+    mat = cbind(mat,nc1);

+    mat = cbind(mat,tb[,coef]);

+    mat = cbind(mat,p);

+    mat = cbind(mat,padj);

     rownames(mat) = tx;

-    mat = mat[srt,]

+    mat = mat[srt,];

     nm = c(paste("+samples in group",unique(groups)[1]),paste("+samples in group",unique(groups)[2]),

     paste("counts in group",unique(groups)[1]),paste("counts in group",unique(groups)[2]),

-    colnames(tb)[coef],"pValue","adjPvalue")

-    colnames(mat) = nm

+    colnames(tb)[coef],"pValue","adjPvalue");

+    colnames(mat) = nm;

     if(!is.null(output)){

         nm = c("Taxa",nm)

@@ -1,3 +1,48 @@

+#' Table of top microbial marker gene from linear model fit including sequence

+#' information

+#' 

+#' Extract a table of the top-ranked features from a linear model fit. This

+#' function will be updated soon to provide better flexibility similar to

+#' limma's topTable. This function differs from \code{link{MRcoefs}} in that it

+#' provides other information about the presence or absence of features to help

+#' ensure significant features called are moderately present.

+#' 

+#' 

+#' @param obj A list containing the linear model fit produced by lmFit through

+#' fitZig.

+#' @param by Column number or column name specifying which coefficient or

+#' contrast of the linear model is of interest.

+#' @param coef Column number(s) or column name(s) specifying which coefficient

+#' or contrast of the linear model to display.

+#' @param number The number of bacterial features to pick out.

+#' @param taxa Taxa list.

+#' @param uniqueNames Number the various taxa.

+#' @param adjust.method Method to adjust p-values by. Default is "FDR". Options

+#' include "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr",

+#' "none". See \code{\link{p.adjust}} for more details.

+#' @param group One of three choices, 0,1,2. 0: the sort is ordered by a

+#' decreasing absolute value coefficient fit. 1: the sort is ordered by the raw

+#' coefficient fit in decreasing order. 2: the sort is ordered by the raw

+#' coefficient fit in increasing order. 3: the sort is ordered by the p-value

+#' of the coefficient fit in increasing order.

+#' @param output Name of output file, including location, to save the table.

+#' @return Table of the top-ranked features determined by the linear fit's

+#' coefficient.

+#' @seealso \code{\link{fitZig}} \code{\link{MRcoefs}}

+#' @examples

+#' 

+#' data(lungData)

+#' k = grep("Extraction.Control",pData(lungData)$SampleType)

+#' lungTrim = lungData[,-k]

+#' k = which(rowSums(MRcounts(lungTrim)>0)<10)

+#' lungTrim = lungTrim[-k,]

+#' cumNorm(lungTrim)

+#' smokingStatus = pData(lungTrim)$SmokingStatus

+#' mod = model.matrix(~smokingStatus)

+#' settings = zigControl(maxit=1,verbose=FALSE)

+#' fit = fitZig(obj = lungTrim,mod=mod,control=settings)

+#' head(MRtable(fit))

+#' 

 MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,adjust.method="fdr",group=0,output=NULL){

     tb = obj$fit$coefficients

     tx = as.character(taxa);

@@ -56,4 +101,4 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,a

     } else{

         return(as.data.frame(mat))

     }

-}

\ No newline at end of file

+}

@@ -2,7 +2,7 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,a

     tb = obj$fit$coefficients

     tx = as.character(taxa);

-    if(uniqueNames=TRUE){

+    if(uniqueNames==TRUE){

         for (nm in unique(tx)) {

             ii=which(tx==nm)

             tx[ii]=paste(tx[ii],seq_along(ii),sep=":")

@@ -1,10 +1,12 @@

-MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,adjust.method="fdr",group=0,output=NULL){

+MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,uniqueNames=FALSE,adjust.method="fdr",group=0,output=NULL){

     tb = obj$fit$coefficients

     tx = as.character(taxa);

-    for (nm in unique(tx)) {

-        ii=which(tx==nm)

-        tx[ii]=paste(tx[ii],seq_along(ii),sep=":")

+    if(uniqueNames=TRUE){

+        for (nm in unique(tx)) {

+            ii=which(tx==nm)

+            tx[ii]=paste(tx[ii],seq_along(ii),sep=":")

+        }

     }

     if(is.null(coef)){coef = 1:ncol(tb);}

@@ -28,6 +30,8 @@ MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,adjust.method="fdr"

         srt = order((tb[,by]),decreasing=TRUE)[1:number]

     } else if(group==2){

         srt = order((tb[,by]),decreasing=FALSE)[1:number]

+    } else if(group==3){

+        srt = order(p,decreasing=FALSE)[1:number]

     }

     mat = cbind(np0,np1)

new file mode 100644

@@ -0,0 +1,55 @@

+MRtable<-function(obj,by=2,coef=NULL,number=10,taxa=obj$taxa,adjust.method="fdr",group=0,output=NULL){

+    tb = obj$fit$coefficients

+    tx = as.character(taxa);

+    

+    for (nm in unique(tx)) {

+        ii=which(tx==nm)

+        tx[ii]=paste(tx[ii],seq_along(ii),sep=":")

+    }

+

+    if(is.null(coef)){coef = 1:ncol(tb);}

+

+    p=obj$eb$p[,by];

+    padj = p.adjust(p,method=adjust.method);

+    

+    groups = factor(obj$fit$design[,by])

+    cnts = obj$counts;

+    yy = cnts>0;

+    

+    np0 = rowSums(yy[,groups==unique(groups)[1]]);

+    np1 = rowSums(yy[,groups==unique(groups)[2]]);

+

+    nc0 = rowSums(cnts[,groups==unique(groups)[1]]);

+    nc1 = rowSums(cnts[,groups==unique(groups)[2]]);

+

+    if(group==0){

+        srt = order(abs(tb[,by]),decreasing=TRUE)[1:number]

+    } else if(group==1){

+        srt = order((tb[,by]),decreasing=TRUE)[1:number]

+    } else if(group==2){

+        srt = order((tb[,by]),decreasing=FALSE)[1:number]

+    }

+

+    mat = cbind(np0,np1)

+    mat = cbind(mat,nc0)

+    mat = cbind(mat,nc1)

+    mat = cbind(mat,tb[,coef])

+    mat = cbind(mat,p)

+    mat = cbind(mat,padj)

+    rownames(mat) = tx;

+    mat = mat[srt,]

+

+    nm = c(paste("+samples in group",unique(groups)[1]),paste("+samples in group",unique(groups)[2]),

+    paste("counts in group",unique(groups)[1]),paste("counts in group",unique(groups)[2]),

+    colnames(tb)[coef],"pValue","adjPvalue")

+    colnames(mat) = nm

+

+    if(!is.null(output)){

+        nm = c("Taxa",nm)

+        mat2 = cbind(rownames(mat),mat)

+        mat2 = rbind(nm,mat2)

+        write(t(mat2),ncolumns=ncol(mat2),file=output,sep="\t")

+    } else{

+        return(as.data.frame(mat))

+    }

+}

\ No newline at end of file