updated

DESCRIPTION

@@ -0,0 +1,34 @@
+Package: RNAAgeCalc
+Type: Package
+Title: A multi-tissue transcriptional age calculator
+Version: 0.99.1
+Authors@R: c(
+    person("Xu", "Ren", 
+        email = "xuren2120@gmail.com", role = c("aut", "cre")),
+    person("Pei Fen", "Kuan", 
+        email = "peifen.kuan@stonybrook.edu", role = "aut"))
+Description: It has been shown that both DNA methylation and RNA transcription 
+    are linked to chronological age and age related diseases. Several 
+    estimators have been developed to predict human aging from DNA level and 
+    RNA level. Most of the human transcriptional age predictor are based on 
+    microarray data and limited to only a few tissues. To date, transcriptional 
+    studies on aging using RNASeq data from different human tissues is limited.
+    The aim of this package is to provide a tool for across-tissue and 
+    tissue-specific transcriptional age calculation based on GTEx RNASeq data.
+License: GPL-2
+Encoding: UTF-8
+Imports:
+    ggplot2,
+    impute,
+    AnnotationDbi,
+    org.Hs.eg.db,
+    stats
+Depends:
+    R (>= 3.5)
+Suggests:
+    knitr,
+    rmarkdown,
+    testthat
+RoxygenNote: 6.1.0
+VignetteBuilder: knitr
+biocViews: RNASeq,GeneExpression

NAMESPACE

@@ -0,0 +1,21 @@
+# Generated by roxygen2: do not edit by hand
+
+export(count2FPKM)
+export(makeplot)
+export(predict_age)
+import(org.Hs.eg.db)
+importFrom(AnnotationDbi,select)
+importFrom(ggplot2,aes)
+importFrom(ggplot2,element_text)
+importFrom(ggplot2,geom_point)
+importFrom(ggplot2,geom_smooth)
+importFrom(ggplot2,ggplot)
+importFrom(ggplot2,ggtitle)
+importFrom(ggplot2,theme)
+importFrom(ggplot2,theme_bw)
+importFrom(ggplot2,xlab)
+importFrom(ggplot2,ylab)
+importFrom(impute,impute.knn)
+importFrom(stats,lm)
+importFrom(stats,na.omit)
+importFrom(stats,residuals)

R/count2FPKM.R

@@ -0,0 +1,71 @@
+
+#' @title Converting gene expression data from raw count to FPKM
+#' @description This function converts gene expression data from raw count to
+#' FPKM.
+#'
+#' @param rawcount a matrix or data frame which contains gene expression count
+#' data.
+#' @param genelength gene length in bp. The size of `genelength` should be
+#' equal to the number of rows in `rawcount`. This argument is optional. If
+#' not provided, gene length is obtained from the internal database.
+#' @param idtype a string which indicates the gene id type in rawcount matrix.
+#' It should be one of "SYMBOL", "ENSEMBL", "ENTREZID" or "REFSEQ".
+#' Default is "SYMBOL".
+#' @export
+#' @import org.Hs.eg.db
+#' @importFrom AnnotationDbi select
+#' @return a data frame contains FPKM.
+#' @references Carlson M (2019). org.Hs.eg.db: Genome wide annotation for
+#' Human. R package version 3.8.2.
+#' @examples
+#' data(countExample)
+#' head(rawcount)
+#' fpkm = count2FPKM(rawcount)
+#' head(fpkm)
+
+count2FPKM = function(rawcount, genelength = NULL, idtype = "SYMBOL"){
+    if(is.null(genelength)){
+        if(idtype!="ENSEMBL"){
+            ## convert the gene id to ENSEMBL to match the gene id in gene
+            ## length database
+            temp = suppressMessages(select(org.Hs.eg.db, rownames(rawcount),
+                columns = "ENSEMBL", keytype = idtype))
+            outcome = temp[temp$ENSEMBL%in%rownames(lengthDB),]
+            outcome = outcome[!duplicated(outcome[,idtype]),]
+            ## ind is all the one to one map
+            ind = which(!outcome$ENSEMBL %in%
+                outcome$ENSEMBL[duplicated(outcome$ENSEMBL)])
+            outcome1 = outcome[ind,]   ## outcome1 is all the 1-1 map
+
+            matchid = match(rownames(rawcount),outcome1[,idtype])
+            genelength = lengthDB[outcome1$ENSEMBL[matchid],"bp_length"]
+        }else{
+            genelength = lengthDB[rownames(rawcount), "bp_length"]
+        }
+
+    }else{
+        stopifnot(is.vector(genelength))
+        stopifnot(is.numeric(genelength))
+        if(any(genelength<0, na.rm = TRUE)){
+            stop("genelength cannot contain negative value(s).")
+        }
+        if(length(genelength)!=nrow(rawcount)){
+            stop("The size of genelength vector should be equal to the number 
+of rows in rawcount.")
+        }
+    }
+
+    if(any(is.na(genelength))){
+        warning("Can't find gene length for ",
+                round(sum(is.na(genelength))/nrow(rawcount)*100,4),
+                "% genes when converting raw count to FPKM.")
+    }
+
+    countSum = colSums(rawcount)
+    bg = matrix(countSum, ncol = ncol(rawcount),
+        nrow = nrow(rawcount), byrow = TRUE)
+    wid = matrix(genelength, nrow = nrow(rawcount),
+        ncol = ncol(rawcount), byrow = FALSE)
+    data.frame(rawcount / (wid/1000) / (bg/1e6))
+
+}

R/exampledata.R

@@ -0,0 +1,21 @@
+#' @title An example of FPKM data
+#'
+#' @description An example of FPKM data
+#' @docType data
+#' @name fpkm
+#' @usage fpkm
+#' @format A data frame which contains the fpkm data. Each row is a gene and 
+#' each column is a sample
+#' @keywords datasets
+NULL
+
+#' @title An example of RNASeq count data
+#'
+#' @description An example of RNASeq count data
+#' @docType data
+#' @name rawcount
+#' @usage rawcount
+#' @format A data frame which contains the RNASeq count data. Each row is a 
+#' gene and each column is a sample
+#' @keywords datasets
+NULL

R/makeplot.R

@@ -0,0 +1,41 @@
+
+
+#' @title Make plot to visualize RNA age
+#'
+#' @description This function makes plots to visualize the relationship
+#' between chronological age and RNA age.
+#' @param res a data frame returned by `predict_age` function. If the
+#' chronological age is not provided when using `predict_age` function,
+#' visulization cannot be made.
+#' @param main title of the plot
+#' @param xlab label of x-axis
+#' @param ylab label of y-axis
+#' @importFrom ggplot2 ggplot aes geom_point geom_smooth ggtitle xlab ylab
+#' theme_bw theme element_text
+#' @export
+#' @return the plot which shows RNA age vs chronological age
+#' @examples
+#' data(fpkmExample)
+#' fpkm_large = cbind(fpkm, fpkm, fpkm, fpkm)
+#' fpkm_large = cbind(fpkm_large, fpkm_large, fpkm_large, fpkm_large)
+#' colnames(fpkm_large) = paste0("sample",1:32)
+#' chronage = data.frame(sampleid = colnames(fpkm_large), age = 1:32)
+#' res = predict_age(exprdata = fpkm_large, exprtype = "FPKM",
+#' chronage = chronage)
+#' makeplot(res)
+
+makeplot = function(res, main = "RNA age vs chronological age",
+                    xlab = "chronological age", ylab = "RNA Age"){
+    if(!"ChronAge"%in%colnames(res)){
+        stop("Chronological age is not found in res data frame.")
+    }
+    if(nrow(na.omit(res))<30){
+        warning("Less than 30 samples. The linear regression on RNA age vs
+chronological age may not be reliable.")
+    }
+    ggplot(res, aes(x=ChronAge, y=RNAAge)) + geom_point(shape=19,size=1) +
+        geom_smooth(method=lm) + ggtitle(main) + xlab(xlab) + ylab(ylab) +
+        theme_bw() + theme(plot.title = element_text(hjust = 0.5))
+}
+
+