442 lines
14 KiB
R
442 lines
14 KiB
R
# tocID <- "scripts/ABC-dbUtilities.R"
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#
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# database utilities for ABC learning units
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#
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# ==============================================================================
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#TOC> ==========================================================================
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#TOC>
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#TOC> Section Title Line
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#TOC> -------------------------------------------------
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#TOC> 1 PACKAGES 32
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#TOC> 2 FUNCTIONS 50
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#TOC> 2.01 dbSanitizeSequence() 53
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#TOC> 2.02 dbConfirmUnique() 88
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#TOC> 2.03 dbInit() 106
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#TOC> 2.04 dbAutoincrement() 147
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#TOC> 2.05 dbAddProtein() 160
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#TOC> 2.06 dbAddFeature() 180
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#TOC> 2.07 dbAddTaxonomy() 199
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#TOC> 2.08 dbAddAnnotation() 215
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#TOC> 2.09 dbFetchUniProtSeq() 243
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#TOC> 2.10 dbFetchPrositeFeatures() 289
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#TOC> 2.11 node2text() 339
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#TOC> 2.12 dbFetchNCBItaxData() 351
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#TOC> 2.13 UniProtIDmap() 390
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#TOC> 3 TESTS 429
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#TOC>
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#TOC> ==========================================================================
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# = 1 PACKAGES ============================================================
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if (! requireNamespace("jsonlite", quietly = TRUE)) {
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install.packages("jsonlite")
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}
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if (! requireNamespace("httr", quietly = TRUE)) {
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install.packages("httr")
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}
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if (! requireNamespace("xml2", quietly = TRUE)) {
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install.packages("xml2")
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}
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# = 2 FUNCTIONS ===========================================================
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# == 2.01 dbSanitizeSequence() =============================================
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dbSanitizeSequence <- function(s, unambiguous = TRUE) {
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# Remove FASTA header lines, if any,
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# flatten any structure that s has,
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# remove all non-letters except "-" (gap) and "*" (stop),
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# convert to uppercase.
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#
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# Parameters:
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# s chr A DNA or protein sequence plus other characters
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# unambiguous bool if TRUE, stop() if any letter remaining after
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# processing matches an ambiguity code. This is likely
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# due to inadvertently including meta-data, such as
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# a FASTA header, with the sequence.
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# Note: since U is an ambiguity code for amino acid sequences, you need
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# to set unambiguous = FALSE to process RNA sequences with Uracil.
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# Value: chr a valid, uppercase, amino acid sequence
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#
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s <- as.character(unlist(s)) # convert complex object to plain chr vector
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s <- unlist(strsplit(s, "\n")) # split up at linebreaks, if any
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s <- s[! grepl("^>", s)] # drop all lines beginning">" (FASTA header)
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s <- paste(s, collapse="") # combine into single string
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s <- toupper(gsub("[^a-zA-Z*-]", "", s))
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if (unambiguous) {
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amb <- "([bjouxzBJOUXZ])" # parentheses capture the match
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ambChar <- unlist(regmatches(s, regexec(amb, s)))[1]
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if (! is.na(ambChar)) {
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stop(paste("Input contains ambiguous codes(s): \"",
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ambChar, "\".", sep=""))
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}
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}
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return(s)
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}
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# == 2.02 dbConfirmUnique() ================================================
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dbConfirmUnique <- function(x) {
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# x is a vector of logicals.
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# returns x if x has exactly one TRUE element.
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# stop() otherwise.
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if (any(!is.logical(x))) {
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stop("PANIC: Input is not a boolean vector.")
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} else if (sum(x) == 0) {
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stop("PANIC: No match found.")
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} else if (sum(x) > 1) {
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stop("PANIC: More than one match found.")
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} else {
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return(x)
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}
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}
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# == 2.03 dbInit() =========================================================
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dbInit <- function() {
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# Return an empty instance of the protein database
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# Open the link and study the schema:
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# https://docs.google.com/presentation/d/13vWaVcFpWEOGeSNhwmqugj2qTQuH1eZROgxWdHGEMr0
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db <- list()
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db$version <- "1.0"
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db$protein <- data.frame(
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ID = numeric(),
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name = character(),
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RefSeqID = character(),
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UniProtID = character(),
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taxonomyID = numeric(),
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sequence = character())
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db$taxonomy <- data.frame(
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ID = numeric(),
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species = character())
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db$annotation <- data.frame(
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ID = numeric(),
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proteinID = numeric(),
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featureID = numeric(),
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start = numeric(),
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end = numeric())
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db$feature <- data.frame(
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ID = numeric(),
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name = character(),
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description = character(),
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sourceDB = character(),
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accession = character())
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return(db)
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}
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# == 2.04 dbAutoincrement() ================================================
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dbAutoincrement <- function(tb) {
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# Return a unique integer that can be used as a primary key
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# Value:
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# num a number one-larger than the largest current value in table$ID
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if (length(tb$ID) == 0) {
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return(1)
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} else {
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return(max(tb$ID) + 1)
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}
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}
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# == 2.05 dbAddProtein() ===================================================
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dbAddProtein <- function(db, jsonDF) {
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# Add one or more protein entries to the database db.
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# Parameters:
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# db list a database created with dbInit()
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# jsonDF data frame protein data imported into a data frame with
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# fromJSON()
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for (i in seq_len(nrow(jsonDF))) {
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x <- data.frame(ID = dbAutoincrement(db$protein),
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name = jsonDF$name[i],
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RefSeqID = jsonDF$RefSeqID[i],
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UniProtID = jsonDF$UniProtID[i],
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taxonomyID = jsonDF$taxonomyID[i],
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sequence = dbSanitizeSequence(jsonDF$sequence[i]))
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db$protein <- rbind(db$protein, x)
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}
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return(db)
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}
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# == 2.06 dbAddFeature() ===================================================
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dbAddFeature <- function(db, jsonDF) {
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# Add one or more feature entries to the database db.
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# Parameters:
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# db list a database created with dbInit()
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# jsonDF data frame feature data imported into a data frame with
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# fromJSON()
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for (i in seq_len(nrow(jsonDF))) {
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x <- data.frame(ID = dbAutoincrement(db$feature),
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name = jsonDF$name[i],
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description = jsonDF$description[i],
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sourceDB = jsonDF$sourceDB[i],
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accession = jsonDF$accession[i])
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db$feature <- rbind(db$feature, x)
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}
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return(db)
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}
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# == 2.07 dbAddTaxonomy() ==================================================
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dbAddTaxonomy <- function(db, jsonDF) {
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# Add one or more taxonomy entries to the database db.
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# Parameters:
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# db list A database created with dbInit()
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# jsonDF data frame Taxonomy data imported into a data frame with
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# fromJSON()
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for (i in seq_len(nrow(jsonDF))) {
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x <- data.frame(
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ID = jsonDF$ID[i],
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species = jsonDF$species[i])
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db$taxonomy <- rbind(db$taxonomy, x)
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}
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return(db)
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}
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# == 2.08 dbAddAnnotation() ================================================
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dbAddAnnotation <- function(db, jsonDF) {
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# Add one or more annotation entries to the database db.
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# Parameters:
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# db list a database created with dbInit()
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# jsonDF data frame annotation data imported into a data frame with
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# fromJSON()
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for (i in seq_len(nrow(jsonDF))) {
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sel <- jsonDF$pName[i] == db$protein$name
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sel <- dbConfirmUnique(sel)
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pID <- db$protein$ID[sel]
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sel <- jsonDF$fName[i] == db$feature$name
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sel <- dbConfirmUnique(sel)
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fID <- db$feature$ID[sel]
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x <- data.frame(ID = dbAutoincrement(db$annotation),
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proteinID = pID,
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featureID = fID,
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start = as.integer(jsonDF$start[i]),
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end = as.integer(jsonDF$end[i]))
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db$annotation <- rbind(db$annotation, x)
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}
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return(db)
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}
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# == 2.09 dbFetchUniProtSeq() ==============================================
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dbFetchUniProtSeq <- function(IDs) {
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# Fetch a protein sequence from UniProt.
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# Parameters:
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# IDs char a vector of UniProt IDs (accession number)
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# Value:
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# char a vector of the same length as ID. It contains
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# sequences where the retrieval was successful, NA where
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# it was not successful. The elements are named with
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# the ID, the header lines are set as attribute "header"
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BASE <- "http://www.uniprot.org/uniprot/"
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sq <- character()
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hd <- character()
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for (i in seq_along(IDs)) {
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URL <- sprintf("%s%s.fasta", BASE, IDs[i])
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response <- httr::GET(URL)
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if (httr::status_code(response) == 200) {
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s <- as.character(response)
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s <- unlist(strsplit(s, "\n"))
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x <- dbSanitizeSequence(s)
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} else {
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s <- ""
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x <- NA
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}
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hd[i] <- s[1]
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sq[i] <- x
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}
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names(sq) <- IDs
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attr(sq, "headers") <- hd
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return(sq)
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}
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if (FALSE) {
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inp <- c("P79073", "P0000000", "A0A1W2TKZ7")
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s <- dbFetchUniProtSeq(inp)
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s[1:3]
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str(s)
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attr(s, "headers")[1]
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}
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# == 2.10 dbFetchPrositeFeatures() =========================================
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dbFetchPrositeFeatures <- function(ID) {
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# Fetch feature annotations from ScanProsite.
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# Parameters:
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# ID char a UniProt ID (accession number)
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# Value:
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# data frame uID char UniProt ID
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# start num start of motif
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# end num end of motif
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# psID char PROSITE motif ID
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# psName char PROSITE motif name
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# psSeq char sequence annotated to the feature
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# If the operation is not successful, a 0-length data frame is returned.
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URL <- "https://prosite.expasy.org/cgi-bin/prosite/PSScan.cgi"
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response <- httr::POST(URL,
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body = list(meta = "opt1",
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meta1_protein = "opt1",
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seq = ID,
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skip = "on",
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output = "tabular"))
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myFeatures <- data.frame()
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if (httr::status_code(response) == 200) {
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lines <- unlist(strsplit(httr::content(response, "text"), "\\n"))
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patt <- sprintf("\\|%s\\|", ID)
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lines <- lines[grep(patt, lines)]
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for (line in lines) {
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tokens <- unlist(strsplit(line, "\\t|\\|"))
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myFeatures <- rbind(myFeatures,
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data.frame(uID = tokens[2],
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start = as.numeric(tokens[4]),
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end = as.numeric(tokens[5]),
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psID = tokens[6],
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psName = tokens[7],
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psSeq = tokens[11]))
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}
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}
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return(myFeatures)
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}
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if (FALSE) {
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dbFetchPrositeFeatures("P33520") # RES1_SCHPO
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}
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# == 2.11 node2text() ======================================================
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node2text <- function(doc, tag) {
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# an extractor function for the contents of elements
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# between given tags in an XML response.
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# Contents of all matching elements is returned in
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# a vector of strings.
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path <- paste0("//", tag)
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nodes <- xml2::xml_find_all(doc, path)
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return(xml2::xml_text(nodes))
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}
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# == 2.12 dbFetchNCBItaxData() =============================================
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dbFetchNCBItaxData <- function(ID) {
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# Fetch feature taxID and Organism from the NCBI.
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# Parameters:
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# ID char a RefSeq ID (accession number)
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# Value:
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# data frame taxID num NCBI taxID
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# organism char organism for this taxID
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# If the operation is not successful, a 0-length data frame is returned.
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eUtilsBase <- "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/"
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URL <- paste(eUtilsBase,
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"esearch.fcgi?",
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"db=protein",
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"&term=", ID,
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sep="")
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myXML <- xml2::read_xml(URL)
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GID <- node2text(myXML, "Id")
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URL <- paste0(eUtilsBase,
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"esummary.fcgi?",
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"db=protein",
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"&id=",
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GID,
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"&version=2.0")
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myXML <- xml2::read_xml(URL)
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x <- as.integer(node2text(myXML, "TaxId"))
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y <- node2text(myXML, "Organism")
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tID <- data.frame()
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if (length(x) > 0 && length(y) > 0) {
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tID <- data.frame(taxID = x, organism = y)
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}
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return(tID)
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}
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# == 2.13 UniProtIDmap() ===================================================
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UniProtIDmap <- function (s, mapFrom = "P_REFSEQ_AC", mapTo = "ACC") {
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# Use UniProt ID mapping service to map one or more IDs
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# Parameters:
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# s char A string of white-space separated IDs
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# mapFrom char the database in which the IDs in s are valid.
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# Default is RefSeq protein
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# mapTo char the database in which the target IDs are valid.
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# Default is UniProtKB
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# Value
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# A data frame of mapped IDs, with column names From and To, or an
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# empty data frame if the mapping was unsuccessful. No rows are returned
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# for IDs that are not mapped.
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# Initialize curl
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httr::set_config(httr::config(http_version = 0))
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URL <- "https://www.uniprot.org/uploadlists/"
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response <- httr::POST(URL,
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body = list(from = mapFrom,
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to = mapTo,
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format = "tab",
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query = s))
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if (httr::status_code(response) == 200) { # 200: oK
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myMap <- read.delim(file = textConnection(httr::content(response)),
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sep = "\t")
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colnames(myMap) <- c("From", "To")
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} else {
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myMap <- data.frame()
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warning(paste("No uniProt ID mapping returned:",
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"server sent status",
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httr::status_code(response)))
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}
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return(myMap)
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}
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# = 3 TESTS ===============================================================
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if (FALSE) {
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if (! requireNamespace("testthat", quietly = TRUE)) {
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install.packages("testthat")
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}
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# ToDo: test everything here
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}
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# [END]
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