@@ -1,8 +1,8 @@

 Package: MotifDb

 Type: Package

 Title: An Annotated Collection of Protein-DNA Binding Sequence Motifs

-Version: 1.19.6

-Date: 2017-09-07

+Version: 1.19.7

+Date: 2017-09-12

 Author: Paul Shannon, Matt Richards

 Maintainer: Paul Shannon <pshannon@systemsbiology.org>

 Depends: R (>= 2.15.0), methods, BiocGenerics, S4Vectors, IRanges, Biostrings

@@ -3,8 +3,7 @@ setGeneric('query', signature='object', function(object, queryString, ignore.cas

 setGeneric('motifToGene', signature='object', function(object, motifs, source) standardGeneric('motifToGene'))

 setGeneric('geneToMotif', signature='object', function(object, geneSymbols, source) standardGeneric('geneToMotif'))

 setGeneric('associateTranscriptionFactors', signature='object',

-           function(object, tbl.withMotifs, motif.column.name, source, expand.rows)

-              standardGeneric('associateTranscriptionFactors'))

+           function(object, tbl.withMotifs,  source, expand.rows) standardGeneric('associateTranscriptionFactors'))

 #------------------------------------------------------------------------------------------------------------------------

 setClass ('MotifList',

           contains='SimpleList',

@@ -400,23 +399,25 @@ setMethod ('geneToMotif', 'MotifList',

 #-------------------------------------------------------------------------------

 setMethod('associateTranscriptionFactors', 'MotifList',

-   function(object, tbl.withMotifs, motif.column.name, source, expand.rows){

+   function(object, tbl.withMotifs, source, expand.rows){

      stopifnot(source %in% c("MotifDb", "TFClass"))

      tbl.out <- data.frame()

      if(source %in% c("MotifDb")){

-        # "direct" means:  lookup up in the object metadata, expect one TF geneSymbol per matrix name

-        pfm.ids <- tbl.withMotifs[, motif.column.name]

+           # lookup up in the object metadata, expect one TF geneSymbol per matrix name

+        pfm.ids <- tbl.withMotifs[, "motifName"]

         matched.rows <- match(pfm.ids, names(as.list(object)))

         #if(length(matched.rows) == nrow(tbl.withMotifs)) {

         tbl.new <- mcols(object)[matched.rows, c("geneSymbol", "pubmedID")]

         tbl.new$geneSymbol[nchar(tbl.new$geneSymbol)==0] <- NA

         tbl.new$pubmedID[nchar(tbl.new$pubmedID)==0] <- NA

         tbl.out <- as.data.frame(cbind(tbl.withMotifs, tbl.new))

-         #}

         } # direct

      if(source %in% c("TFClass")){

+        if(! "shortMotif" %in% colnames(tbl.withMotifs)){

+           stop("MotifDb::assoicateTranscriptionFactors needs a 'shortMotif' column with the TFClass source")

+           }

         tbl.tfClass <- read.table(system.file(package="MotifDb", "extdata", "tfClass.tsv"), sep="\t", as.is=TRUE, header=TRUE)

-        motif.ids <- tbl.withMotifs[, motif.column.name]

+        motif.ids <- tbl.withMotifs[, "shortMotif"]

         geneSymbols <- lapply(motif.ids, function(id) paste(tbl.tfClass$tf.gene[grep(id, tbl.tfClass$motif)], collapse=";"))

         geneSymbols <- unlist(geneSymbols)

         pubmedIds   <- lapply(motif.ids, function(id) unique(tbl.tfClass$pubmedID[grep(id, tbl.tfClass$motif)]))

@@ -809,16 +809,17 @@ test.associateTranscriptionFactors <- function()

       #      "Hsapiens-jaspar2016-RUNX1-MA0002.1"  "Hsapiens-jaspar2016-TFAP2A-MA0003.1"

    motif.names <- names(pfms[1:5])

-   tbl <- data.frame(motifLongName=motif.names, score=runif(5), stringsAsFactors=FALSE)

-   tbl.anno <- associateTranscriptionFactors(mdb, tbl, "motifLongName", source="MotifDb", expand.rows=FALSE)

+   tbl <- data.frame(motifName=motif.names, score=runif(5), stringsAsFactors=FALSE)

+   tbl.anno <- associateTranscriptionFactors(mdb, tbl, source="MotifDb", expand.rows=FALSE)

    checkEquals(dim(tbl.anno), c(nrow(tbl), ncol(tbl) + 2))

    checkTrue(all(c("geneSymbol", "pubmedID") %in% colnames(tbl.anno)))

+   checkEquals(tbl.anno$geneSymbol, c("RUNX1", "TFAP2A", "TFAP2A", "TFAP2A", "AR"))

       # now add in a bogus motif name, one for which there cannot possibly be a TF

    motif.names[3] <- "bogus"

-   tbl <- data.frame(motifLongName=motif.names, score=runif(5), stringsAsFactors=FALSE)

-   tbl.anno <- associateTranscriptionFactors(mdb, tbl, "motifLongName", source="MotifDb", expand.rows=FALSE)

+   tbl <- data.frame(motifName=motif.names, score=runif(5), stringsAsFactors=FALSE)

+   tbl.anno <- associateTranscriptionFactors(mdb, tbl, source="MotifDb", expand.rows=FALSE)

    checkTrue(is.na(tbl.anno$geneSymbol[3]))

    checkTrue(is.na(tbl.anno$pubmedID[3]))

@@ -826,65 +827,42 @@ test.associateTranscriptionFactors <- function()

       # the tfFamily

       #      "MA0002.1" "MA0003.1" "MA0003.2" "MA0003.3" "MA0007.2"

+   motif.names <- names(pfms[1:5])

    short.motif.names <- unlist(lapply(strsplit(motif.names, "-"), function(tokens) return(tokens[length(tokens)])))

-   tbl <- data.frame(motif=short.motif.names, score=runif(5), stringsAsFactors=FALSE)

+   tbl <- data.frame(motifName=motif.names, shortMotif=short.motif.names, score=runif(5), stringsAsFactors=FALSE)

-   tbl.anno <- associateTranscriptionFactors(mdb, tbl, "motif", source="TFClass", expand.rows=FALSE)

+   tbl.anno <- associateTranscriptionFactors(mdb, tbl, source="TFClass", expand.rows=FALSE)

    checkEquals(dim(tbl.anno), c(nrow(tbl), ncol(tbl) + 2))

+      # TFClass only annotates MA0003.3, none of the others

+   checkTrue(all(is.na(tbl.anno$geneSymbol[-4])))

+   checkTrue(all(is.na(tbl.anno$pubmedID[-4])))

+   checkEquals(tbl.anno$geneSymbol[4], "TFAP2A;TFAP2B;TFAP2C;TFAP2D;TFAP2E")

+   checkEquals(tbl.anno$pubmedID[4],   "23180794")

+

+      # now ask for expandsion of the semicolon separated list

+   tbl.anno <- associateTranscriptionFactors(mdb, tbl, source="TFClass", expand.rows=TRUE)

+   checkEquals(dim(tbl.anno), c(nrow(tbl) + 4, ncol(tbl) + 2))

+   checkTrue(all(c("TFAP2A", "TFAP2B", "TFAP2C", "TFAP2D", "TFAP2E") %in% tbl.anno$geneSymbol))

+

       # now add in a bogus motif name, one for which there cannot possibly be a TF

    motif.names <- names(pfms[1:5])

    short.motif.names <- unlist(lapply(strsplit(motif.names, "-"), function(tokens) return(tokens[length(tokens)])))

-   short.motif.names[3] <- "bogus"

-   tbl <- data.frame(motif=short.motif.names, score=runif(5), stringsAsFactors=FALSE)

+   short.motif.names[4] <- "bogus"

+   tbl <- data.frame(shortMotif=short.motif.names, score=runif(5), stringsAsFactors=FALSE)

-   tbl.anno <- associateTranscriptionFactors(mdb, tbl, "motif", source="TFClass", expand.rows=FALSE)

+   tbl.anno <- associateTranscriptionFactors(mdb, tbl, source="TFClass", expand.rows=FALSE)

    checkEquals(dim(tbl.anno), c(nrow(tbl), ncol(tbl) + 2))

+      # after adding bogus to the only mapped motif name, all geneSymbol and pubmedID values should be NA

+   checkTrue(all(is.na(tbl.anno$geneSymbol)))

+   checkTrue(all(is.na(tbl.anno$pubmedID)))

-} # test.associateTranscriptionFactors

-#------------------------------------------------------------------------------------------------------------------------

-#  MA0003.3 is mapped by TFClass to TFAP2A;TFAP2B;TFAP2C;TFAP2D;TFAP2E   (pumbedID 23180794)

-#  use it as a first test of the "exapand.rows" argument to associateTranscriptionFactors method

-#  MA0017.1  is unmapped by TFClass

-#  MA0017.2  is mapped to NR2F1

-test.associateTranscriptionFactors_expandRows <- function()

-{

-   printf("--- test.assoicateTranscriptionFactors")

+      # now make sure that the absence of the  TFClass-specific "shortMotif" field is detected

+   motif.names <- names(pfms[1:5])

+   tbl <- data.frame(motifName=motif.names, score=runif(5), stringsAsFactors=FALSE)

+   checkException(tbl.anno <- associateTranscriptionFactors(mdb, tbl, source="TFClass", expand.rows=FALSE), silent=TRUE)

-   mdb <- MotifDb

-   motifs <- c("MA0003.3", "MA0017.1", "MA0017.2")

-   tbl <- data.frame(motif=motifs, stringsAsFactors=FALSE)

-   tbl.anno <- associateTranscriptionFactors(mdb, tbl, motif.column.name="motif", source="TFClass", expand.rows=FALSE)

-   checkEquals(dim(tbl.anno), c(3,3))

-   checkEquals(tbl.anno$geneSymbol[c(1,3)], c("TFAP2A;TFAP2B;TFAP2C;TFAP2D;TFAP2E", "NR2F1"))

-   checkTrue(is.na(tbl.anno$geneSymbol[2]))

-

-   tbl.annoX <- associateTranscriptionFactors(mdb, tbl, motif.column.name="motif", source="TFClass", expand.rows=TRUE)

-   checkEquals(dim(tbl.annoX), c(7,3))

-   checkEquals(tbl.annoX$motif, c(rep("MA0003.3", 5), "MA0017.2", "MA0017.1"))

-   checkEquals(tbl.annoX$geneSymbol[1:6], c("TFAP2A", "TFAP2B", "TFAP2C", "TFAP2D", "TFAP2E", "NR2F1"))

-   checkTrue(is.na(tbl.annoX$geneSymbol[7]))

-

-      # now a large scale test

-   set.seed(37)

-   mdb.human <- query(mdb, "sapiens")   # > 4000 human matrices

-   indices <- sample(1:length(mdb.human), size=250)

-   motif.long.names <- names(mdb.human)[indices]

-   motif.short.names <- mcols(mdb.human)[indices, "providerId"]

-   tbl <- data.frame(motif.short=motif.short.names, motif.long=motif.long.names, stringsAsFactors=FALSE)

-

-   tbl.anno.mdb <- associateTranscriptionFactors(mdb, tbl, motif.column.name="motif.long", source="MotifDb", expand.rows=FALSE)

-   tbl.anno.mdbX <- associateTranscriptionFactors(mdb, tbl, motif.column.name="motif.long", source="MotifDb", expand.rows=TRUE)

-

-   tbl.anno.tfc  <- associateTranscriptionFactors(mdb, tbl, motif.column.name="motif.short", source="TFClass", expand.rows=FALSE)

-   checkEquals(nrow(tbl.anno.tfc), length(motif.short.names))

-   checkTrue(length(grep(";", tbl.anno.tfc$geneSymbol)) > 20)

-

-   tbl.anno.tfcX <- associateTranscriptionFactors(mdb, tbl, motif.column.name="motif.short", source="TFClass", expand.rows=TRUE)

-   checkTrue(nrow(tbl.anno.tfcX) > nrow(tbl.anno.tfc))   # 250 vs 779

-   checkEquals(length(grep(";", tbl.anno.tfcX$geneSymbol)), 0)

-

-

-} # test.associateTranscriptionFactors_expandRows

+

+} # test.associateTranscriptionFactors

 #------------------------------------------------------------------------------------------------------------------------