Nothing
inst/unitTests/test_PSICQUIC.R
In PSICQUIC: Proteomics Standard Initiative Common QUery InterfaCe
# test_PSICQUIC.R
#-------------------------------------------------------------------------------
# options(stringsAsFactors=FALSE)
#-------------------------------------------------------------------------------
library(PSICQUIC)
library(RUnit)
library(RCurl)
#-------------------------------------------------------------------------------
kras <- "3845"
tp53 <- "7157"
myc <- "4609"
hepC <- "11103"
human <- "9606"
rat <- "10116"
stickleback <- "69293"
#-------------------------------------------------------------------------------
printf <- function(...) print(noquote(sprintf(...)))
#-------------------------------------------------------------------------------
paulsTests <- function()
{
test_initialConditions()
test_.loadRegistry()
test_ctor()
test_.retrieveData()
test_rawQuery()
test_.enumerateSearchPairs()
test_.restrictBySpecies()
test_interactions()
test_interactionsTwoGenes()
test_interactionsFourGenes()
test_handleEmbeddedSingleQuotes()
test_retrieveByPubmedID()
test_retrieveByPubmedIdOnly()
test_retrieveByOmimId()
test_retrieveByInteractionType()
test_retrieveByDetectionMethod()
test_retrieveBySpeciesId()
test_smallMoleculeWithoutSpeciesDesignation()
} # paulsTests
#-------------------------------------------------------------------------------
test_initialConditions <- function()
{
print("--- test_initialConditions")
# the PSICQUIC class avoids factors, using character strings always
# make sure that nothing in the environment will hide any failure
# to accomplish that
x <- data.frame(a=letters, b=LETTERS)
checkTrue(all(sapply(x, is.factor)))
} # test_initialConditions
#-------------------------------------------------------------------------------
test_.loadRegistry <- function()
{
print("--- test_.loadRegistry")
tbl <- PSICQUIC:::.loadRegistry()
# do some simple reasonableness tests
checkEquals(colnames(tbl), c("url"))
checkEquals(grep("^http", tbl$url), 1:nrow(tbl))
checkTrue(nrow(tbl) > 1) # ridiculously conservative number of rows
} # test_.loadRegistry
#-------------------------------------------------------------------------------
test_ctor <- function()
{
print("--- test_ctor")
psicquic <- PSICQUIC(test=TRUE)
checkTrue(is(providers(psicquic), "character"))
checkTrue(length(providers(psicquic)) > 0)
} # test_ctor
#-------------------------------------------------------------------------------
# this utility method is the ultimate endpoint of all queries for the
# interactions, and rawQuery methods.
# make sure it works when called directly
test_.retrieveData <- function()
{
print("--- test_.retrieveData")
#psicquic <- PSICQUIC(test=TRUE)
psicquic <- PSICQUIC()
available.providers <- providers(psicquic)
source <- "BioGrid"
if(!source %in% available.providers)
source <- "BIND"
if(!source %in% available.providers) # mentha ill-behaved on (14 oct 2015)
source <- "mentha"
if(!source %in% available.providers){
print("expected psicquic sources not available, skipping test_.retrieveData");
return(TRUE)
}
base.url <- PSICQUIC:::providerUrl(psicquic, source)
fixed.site.url <- sub("psicquic$", "current/search/query/", base.url)
args <- "identifier:TP53%20AND%20species:9606"
full.url <- sprintf("%s%s", fixed.site.url, args)
tbl <- PSICQUIC:::.retrieveData(full.url)
# no factors!
checkTrue(all(sapply(tbl, is.character)))
checkEquals(ncol(tbl), 15)
checkTrue(nrow(tbl) > 0) # 62 x 15 on (11 sep 2013)
suppressMessages({tbl <- PSICQUIC:::.retrieveData("http://intentionally.bogus")})
checkEquals(dim(tbl), c(0,0))
} # test_.retrieveData
#-------------------------------------------------------------------------------
test_rawQuery <- function()
{
print("--- test_rawQuery")
psicquic <- PSICQUIC(test=TRUE)
# the minimal query: id and species
available.providers <- providers(psicquic)
source <- "BioGrid"
if(!source %in% available.providers)
source <- "BIND"
if(!source %in% available.providers)
source <- "mentha"
if(!source %in% available.providers){
print("expected psicquic sources not available, skipping test_.retrieveData");
return(TRUE)
}
rawArgs.0 <- "identifier:TP53 AND species:9606"
tbl <- rawQuery(psicquic, source, rawArgs.0)
checkEquals(ncol(tbl), 15)
checkTrue(nrow(tbl) > 20)
# no column names added
checkEquals(colnames(tbl), paste("V", 1:15, sep=""))
# specify a AND b. IntAct and iRefIndex both
# report interactions between these two
if("iRefIndex" %in% available.providers){
rawArgs.1 <- "identifier:(ALK AND MAP3K3) AND species:9606"
tbl.2 <- rawQuery(psicquic, "iRefIndex", rawArgs.1)
checkEquals(nrow(tbl.2), 4)
# two references support interactions between these two at iRefIndex:
# 15657099: 1 row
# 14743216: 3 rows
rawArgs <- sprintf("%s AND pubid:(15657099 OR 14743216)", rawArgs.1)
tbl.3 <- rawQuery(psicquic, "iRefIndex", rawArgs)
checkEquals(nrow(tbl.3), 4)
rawArgs <- sprintf("%s AND pubid:15657099", rawArgs.1)
tbl.4 <- rawQuery(psicquic, "iRefIndex", rawArgs)
checkEquals(nrow(tbl.4), 1)
rawArgs <- sprintf("%s AND pubid:14743216", rawArgs.1)
tbl.5 <- rawQuery(psicquic, "iRefIndex", rawArgs)
checkEquals(nrow(tbl.5), 3)
} # if iRefIndexl
# BioGrid ALK yields these interaction types
# psi-mi:MI:0407(direct interaction) 7
# psi-mi:MI:0915(physical association) 55
if("BioGrid" %in% available.providers){
rawArgs <- sprintf("%s AND type:physical association", rawArgs.0)
tbl.6 <- rawQuery(psicquic, "BioGrid", rawArgs)
checkTrue(nrow(tbl.6) > 50) # 1331 (aug 2014) but just 55 (dec 2013)
checkEquals(ncol(tbl.6), 15)
rawArgs <- sprintf("%s AND type:direct interaction", rawArgs.0)
tbl.7 <- rawQuery(psicquic, "BioGrid", rawArgs)
checkTrue(nrow(tbl.7) >= 15) # 15 (dec 2013) 801 (aug 2014)
checkEquals(ncol(tbl.7), 15)
rawArgs <- sprintf("%s AND type:(direct interaction OR physical association)",
rawArgs.0)
tbl.8 <- rawQuery(psicquic, "BioGrid", rawArgs)
checkTrue(nrow(tbl.8) >= 62) # 62 (dec 2013) 2184 (aug 2014)
} # if BioGrid
} # test_rawQuery
#-------------------------------------------------------------------------------
test_.enumerateSearchPairs <- function()
{
print("--- test_.enumerateSearchPairs")
checkEquals(PSICQUIC:::.enumerateSearchPairs(c()), list(a=NA, b=NA))
checkEquals(PSICQUIC:::.enumerateSearchPairs(c("a")), list(a="a", b=NA))
checkEquals(PSICQUIC:::.enumerateSearchPairs(c("a", "b")), list(a="a", b="b"))
pairs <- PSICQUIC:::.enumerateSearchPairs(c("a", "b", "c"))
checkEquals(pairs, list(a=c("a", "a", "b"),
b=c("b", "c", "c")))
} # test_.enumerateSearchPairs
#-------------------------------------------------------------------------------
test_interactions <- function()
{
print("--- test_interactions")
psicquic <- PSICQUIC(test=FALSE)
providers <- c("mentha", "BioGrid")
if(!all(providers %in% providers(psicquic))){
print("expected psicquic sources not available, test_interactionTwoGenes");
return(TRUE)
}
# make sure that a failed request returns an empty data.frame
# with all of the expected column names
tbl.empty <- interactions(psicquic, provider=providers,
id="fubarCompletelyUnrecognizableGeneName",
species=stickleback)
checkEquals(dim(tbl.empty), c(0,16))
# ALK: anaplastic lymphoma kinase, entrez geneID 238
tbl <- interactions(psicquic, id="ALK",
species="9606", speciesExclusive=TRUE,
provider=providers, quiet=TRUE)
# no factors. confidence scores are (as of oct 2013) unparsed strings
checkTrue(all(sapply(tbl, is.character)))
#browser()
checkTrue(nrow(tbl) > 1) # 411 on (10 sep 2013), 165 on (6 jan 2015)
# except for "confidenceScore", which is numeric,
# all columns are character
# cross-tabulation gives a useful summary of the
# interactions: how determined, of what nature:
xtab <- as.data.frame(with(tbl, table(detectionMethod,type)),
stringsAsFactors=FALSE)
xtab <- xtab[xtab$Freq > 0,]
xtab <- xtab[order(xtab$Freq, decreasing=TRUE),]
# do a very simple single test:
# "physical association" is a common interaction type
checkTrue(length(grep("physical association", xtab$type)) >= 1)
# test now for a nonsensical call
checkException(interactions(psicquic, provider="bogus provider"),
silent=TRUE)
} # test_interactions
#-------------------------------------------------------------------------------
test_interactionsTwoGenes <- function()
{
print("--- test_interactionsTwoGenes")
psicquic <- PSICQUIC()
providers <- c("mentha", "BioGrid")
if(!all(providers %in% providers(psicquic))){
print("expected psicquic sources not available, test_interactionTwoGenes");
return(TRUE)
}
# ALK: anaplastic lymphoma kinase, entrez geneID 238
# SHC3: entrez geneID 53358
# JAK3: entrez geneID 3718
# HSPD1: entrez geneID 3329
tbl <- interactions(psicquic, species="9606", id=c("ALK", "JAK3"),
provider=providers, quiet=TRUE)
checkTrue(nrow(tbl) > 1) # (found nrow=5 on 6 jan 2015)
} # test_interactionsTwoGenes
#-------------------------------------------------------------------------------
test_interactionsFourGenes <- function()
{
print("--- test_interactionsFourGenes")
psicquic <- PSICQUIC(test=FALSE)
providers <- c("mentha", "BioGrid", "BIND")
if(!all(providers %in% providers(psicquic))){
print("expected psicquic sources not available, test_interactionFourGenes");
return(TRUE)
}
# ALK: anaplastic lymphoma kinase, entrez geneID 238
# SHC3: entrez geneID 53358
# JAK3: entrez geneID 3718
# HSPD1: entrez geneID 3329
tbl <- interactions(psicquic, species="9606", id=c("ALK", "JAK3", "SHC3", "HSPD1"),
provider=providers, quiet=TRUE)
checkTrue(nrow(tbl) > 1)
mapper <- IDMapper("9606")
tbl.2 <- addGeneInfo(mapper, tbl)
checkEquals(sort(unique(c(tbl.2$A.name, tbl.2$B.name))),
c("ALK", "HSPD1", "JAK3", "SHC3"))
} # test_interactionsFourGenes
#-------------------------------------------------------------------------------
test_retrieveByPubmedID <- function()
{
print("--- test_retrieveByPubmedID")
psicquic <- PSICQUIC()
provider <- "iRefIndex"
if(provider %in% providers(psicquic)){
genes <- c("ALK", "MAP3K3")
tbl <- interactions(psicquic,
id=genes,
species="9606",
provider=provider, quiet=TRUE)
checkEquals(ncol(tbl), 16)
checkTrue(nrow(tbl) > 0)
tbl.2 <-interactions(psicquic, species="9606",
id=genes,
provider=provider, publicationID="15657099",
quiet=TRUE)
checkTrue(is.data.frame(tbl.2)) # got 0 hits in test (29 apr 2019)
tbl.3 <-interactions(psicquic, id=genes, species="9606",
provider=provider, publicationID="14743216",
quiet=TRUE)
checkEquals(ncol(tbl.3), 16)
checkTrue(nrow(tbl.3) > 0)
tbl.4 <-interactions(psicquic, id=genes, species="9606",
provider=provider,
publicationID=c("14743216", "15657099"))
checkTrue(nrow(tbl.4) > 0)
} # if provider
} # test_retrieveByPubmedID
#-------------------------------------------------------------------------------
test_retrieveByPubmedIdOnly <- function()
{
print("--- test_retrieveByPubmedIdOnly")
# first ensure that this works as a rawQuery
psicquic <- PSICQUIC(test=TRUE)
provider <- "IntAct";
if(!provider %in% providers(psicquic)){
printf("%s not available, skipping test_retrieveByPubmedIdOnly", provider);
return(TRUE)
}
# pmid: 20936779
# Nature Methods, 2010
# A human MAP kinase interactome, Sourav Bandyopadhyay et al
tbl <- rawQuery(psicquic, provider, "species:9606 AND pubid:20936779")
checkEquals(ncol(tbl), 15)
checkTrue(nrow(tbl) > 500)
# same results through the recommended api?
tbl.2 <- interactions(psicquic, species="9606",
provider=provider, publicationID="20936779",
quiet=TRUE)
checkEquals(ncol(tbl.2), 16)
checkTrue(nrow(tbl.2) > 500)
} # test_retrieveByPubmedIdOnly
#-------------------------------------------------------------------------------
test_retrieveByOmimId <- function()
{
print("--- test_retrieveByOmimId")
psicquic <- PSICQUIC(test=TRUE)
omim.1 <- "00109135"
omim.2 <- "00137800"
# http://www.ncbi.nlm.nih.gov/omim/?term=00109135
# describes the AXL receptor tryosine kinase, geneID 558,
# oddly, this gene appears in only 7/184 of the interactions
# returned, all of which come from STRING
# thus, a buggy retrieval, which we support nonetheless
tbl.1 <- interactions(psicquic, species="9606", publicationID=omim.1)
checkEquals(length(grep(omim.1, tbl.1$publicationID)), nrow(tbl.1))
tbl.2 <- interactions(psicquic, species="9606", publicationID=omim.2)
checkEquals(length(grep(omim.2, tbl.2$publicationID)), nrow(tbl.2))
if("STRING" %in% providers(psicquic)){
tbl.3 <- interactions(psicquic, provider="STRING",
publicationID=c(omim.1, omim.2),
quiet=TRUE)
# a weak test, appropriately so: the retrieval of interactions
# by STRING, from omim ids, is rather hard to fathom
checkTrue(nrow(tbl.3) > nrow(tbl.1))
checkTrue(nrow(tbl.3) > nrow(tbl.2))
} # if STRING is available
} # test_retrieveByPubmedIdOnly
#-------------------------------------------------------------------------------
test_retrieveByInteractionType <- function()
{
print("--- test_retrieveByInteractionType")
psicquic <- PSICQUIC(test=TRUE)
provider <- "BioGrid"
if(!provider %in% providers(psicquic))
return(sprintf("%s not available", provider))
tbl <- interactions(psicquic, id="ALK", species="9606", provider="BioGrid")
checkTrue(nrow(tbl) > 50)
checkEquals(ncol(tbl), 16)
# BioGrid ALK yields these interaction types
# psi-mi:MI:0407(direct interaction) 7
# psi-mi:MI:0915(physical association) 55
tbl.1 <- interactions(psicquic, id="ALK",
species="9606", provider="BioGrid",
type="physical association", quiet=TRUE)
checkTrue(nrow(tbl.1) > 50)
checkEquals(ncol(tbl.1), 16)
tbl.2 <- interactions(psicquic, id="ALK",
species="9606", provider="BioGrid",
type="direct interaction", quiet=TRUE)
checkTrue(nrow(tbl.2) > 5)
checkEquals(ncol(tbl.2), 16)
tbl.3 <- interactions(psicquic, id="ALK",
species="9606", provider="BioGrid",
type=c("physical association",
"direct interaction"),
quiet=TRUE)
checkTrue(nrow(tbl.3) > 50)
checkEquals(ncol(tbl.3), 16)
} # test_retrieveByInteractionType
#-------------------------------------------------------------------------------
# ALK interactions learned from pull down studies ("psi-mi:MI:0096(pull down)")
# are reported (as of 19 sep 2013) by
# BioGrid, InnateDB, IntAct, MINT, Reactome-FIs, STRING, UniProt, and iRefIndex
# the related laboratory method, "psi-mi:MI:0006(anti bait coip)"
# is reported too, but just from iRefIndex.
# here we try a few combinations of provider & detection method
test_retrieveByDetectionMethod <- function()
{
psicquic <- PSICQUIC(test=FALSE)
providers <- c("BioGrid","InnateDB","IntAct","MINT","Reactome-FIs","STRING",
"UniProt","iRefIndex")
if(!all(providers %in% providers(psicquic))){
print("expected psicquic sources not available, test_retrieveByDetectionMethod");
return(TRUE)
}
tbl.0 <- interactions(psicquic, id="ALK", species="9606",
detectionMethod="pull down")
checkEquals(unique(tbl.0$detectionMethod), "psi-mi:MI:0096(pull down)")
pullDown.count <- nrow (tbl.0)
tbl.1 <- interactions(psicquic, id="ALK", species="9606",
detectionMethod="anti bait coip")
# some surprising results here: both "anti bait coip" and
# "anti tag coip are returned
antiBaitCoip.count <- nrow(tbl.1)
methods <- sort(unique(tbl.1$detectionMethod))
checkTrue(length(grep("MI:0006", methods)) > 0)
both.methods <- c("pull down", "anti bait coip")
tbl.2 <- interactions(psicquic, id="ALK", species="9606",
detectionMethod=both.methods)
bothMethods.count <- nrow (tbl.2)
checkTrue(bothMethods.count >= (pullDown.count + antiBaitCoip.count))
} # test_retrieveByDetectionMethod
#-------------------------------------------------------------------------------
# most interactions are for human, mouse, yeast
# some interactions are between an infecting agent and the human host
# explore that capability here
#
# hepatitus C virus: taxid:11103
# speciesIds() drives your browser to the NCBI taxonomy browser
#
test_retrieveBySpeciesId <- function()
{
print("--- test_retrieveBySpeciesId")
psicquic <- PSICQUIC(test=TRUE)
provider <- "BioGrid"
if(!provider %in% providers(psicquic))
return(sprintf("%s not available", provider))
tbl <- interactions(psicquic,
species=hepC, speciesExclusive=FALSE,
provider="BioGrid", quiet=TRUE)
checkTrue(nrow(tbl) > 100) # 148 on (1 oct 2013)
counts <- as.list(with(tbl, table(c(taxonA, taxonB))))
# hepC ids should be present in every interaction
checkEquals(counts$`taxid:11103`, nrow(tbl))
# make sure that there is at least one hepC/human interaction
checkTrue("taxid:9606" %in% names(counts))
# as of (01 october 2013) BioGrid has no interactions
# restricted to hepC: every hepC interactions is with
# either human or rat proteins.
# therefore a speciesExclusive species query, limited
# to hepC, will at present return an empty data.frame
# but in time this may change, and a non-empty data.frame
# will be returned, but with only hepC proteins mentioned.
tbl.1 <- interactions(psicquic,
species=hepC, speciesExclusive=TRUE,
provider="BioGrid", quiet=TRUE)
if(nrow(tbl.1) > 0)
checkEquals(unique(c(tbl.1$taxonA, tbl.1$taxonB)), "taxid:11103")
# now request interactions between hepC AND human from BioGrid
# the total count should be equal to counts$`taxid:9606`
tbl.2 <- interactions(psicquic, species=c(hepC, human), provider="BioGrid",
quiet=TRUE, speciesExclusive=TRUE)
checkEquals(nrow(tbl.2), counts$`taxid:9606`)
tbl.3 <- interactions(psicquic, species=c(stickleback, human), provider="BioGrid",
quiet=TRUE, speciesExclusive=TRUE)
} # test_retrieveBySpeciesId
#-------------------------------------------------------------------------------
test_.restrictBySpecies <- function()
{
print("--- test_.restrictBySpecies")
psicquic <- PSICQUIC()
provider <- "mentha" # reports human, mouise, fly and cattle interactions for ALK
if(!provider %in% providers(psicquic)){
print("did not find %s in providers, skipping test_.restrictBySpecies")
return(TRUE)
}
tbl <- interactions(psicquic, id="ALK", provider=provider)
if(nrow(tbl) == 0){ # mentha sometimes behaves badly
printf("did not receive any results from provider '%s', skipping test_.restrictBySpecies", provider)
return(TRUE)
}
if(length(unique(c(tbl$taxonA, tbl$taxonB))) <= 1){
print("did not find multiple species in available providers, skipping test_.restrictBySpecies")
return(TRUE)
}
checkTrue(length(unique(c(tbl$taxonA, tbl$taxonB))) > 1)
# ensure that there are some non-9606 taxa reported
# in this result. for a detailed look:
xtab.taxa <- as.data.frame(table(c(tbl$taxonA, tbl$taxonB)))
taxa.variants <- xtab.taxa$Var1
checkTrue(length(grep("9606", taxa.variants)) < length(taxa.variants))
tbl.2 <- PSICQUIC:::.restrictBySpecies(tbl, "9606")
# ensure that every surving row has a the "9606" string
# in both taxon entries
all.taxa.restricted <- unique(c(tbl.2$taxonA, tbl.2$taxonB))
checkEquals(length(all.taxa.restricted), 1)
} # test_.restrictBySpecies
#-------------------------------------------------------------------------------
# 403 lines from MINT for TP53
# something awry on line 223?
# In scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, :
# EOF within quoted string
# dim(tbl) [1] 222 16
test_handleEmbeddedSingleQuotes <- function()
{
print("--- test_handleEmbeddedSingleQuote")
psicquic <- PSICQUIC(test=TRUE)
provider <- "MINT"
if(!provider %in% providers(psicquic))
return(sprintf("%s not available", provider))
mint.tp53.url <- paste("http://www.ebi.ac.uk/Tools/webservices/psicquic/mint",
"/webservices/current/search/query",
"/identifier:TP53%20AND%20species:9606",
sep="")
raw.text <- getURL(mint.tp53.url)
# first authors O'Connor and O'Neill bolix things up if
# single quotes are not disabled as quoting characters
# make sure that this query is still a good one.
checkEquals(grep("'", raw.text), 1)
raw.row.count <- length(strsplit(raw.text, "\n")[[1]]) # 445 on (10 oct 2013)
# make sure we get the same number of rows
tbl <- interactions(psicquic, species="9606", provider=provider, id="TP53",
quiet=TRUE, speciesExclusive=FALSE)
checkEquals(nrow(tbl), raw.row.count)
} # test_handleEmbeddedSingleQuotes
#-------------------------------------------------------------------------------
# if species for a or b is unspecified, probably by the designation "-",
# we want to make sure that we accept the accompanying interaction
# one case where this occurs: ChEMBL, where a drug belongs to
# to no species. the current solution is to issue the query without
# species restriction.
test_smallMoleculeWithoutSpeciesDesignation <- function()
{
print("--- test_smallMoleculeWithoutSpeciesDesignation")
psicquic <- PSICQUIC(test=FALSE)
provider <- "ChEMBL"
if(!provider %in% providers(psicquic))
return(sprintf("%s not available", provider))
tbl.chembl <- interactions(psicquic, id="imatinib",
provider=provider,
speciesExclusive=FALSE,
quiet=FALSE)
hit.count <- nrow(tbl.chembl)
checkTrue(hit.count > 100) # 141 on (23 dec 2013)
freq <- with(tbl.chembl, as.list(table(c(taxonA, taxonB))))
# 3 species: "-" indicates "not assigned" or "unspecified"
checkEquals(sort(names(freq)), c("-", "taxid:10090(mouse)", "taxid:9606(human)"))
# since the query is only for the drug imatinib, every returned row
# will include it, and thus the "unassigned" species token should
# be found once in every row -- though perhaps sometimes in
# taxonA and sometimes in taxonB
checkEquals(hit.count, freq[["-"]])
} # test_smallMoleculeWithoutSpeciesDesignation
#-------------------------------------------------------------------------------
# multi-species queries are, in general, less interesting than single-species
# queries, with two important exceptions:
#
# 1) infection
# 2) small-molecule protein interactions
#
# this exploratory function identifies the ins and outs of case 2, using the
# ChEMBL data source
# ChEMBL or ChEMBLdb is a manually curated chemical database of
# bioactive molecules with drug-like properties.[1] It is maintained
# by the European Bioinformatics Institute (EBI), based on the
# Wellcome Trust Genome Campus, Hinxton, UK.
#
explore_multiSpeciesQuery <- function()
{
print("--- explore_multiSpeciesQuery")
provider <- "ChEMBL"
psicquic <- PSICQUIC(test=TRUE)
if(!provider %in% providers(psicquic))
return(sprintf("%s not available", provider))
base.url <- PSICQUIC:::providerUrl(psicquic, provider)
fixed.site.url <- sub("psicquic$", "current/search/query/", base.url)
#args <- "identifier:imatinib"
args <- sprintf("identifier:(%s AND %s)", "imatinib", "ABL1")
full.url <- sprintf("%s%s", fixed.site.url, args)
tbl <- PSICQUIC:::.retrieveData(full.url)
# no factors!
colnames(tbl) <- c("A","B","altA","altB","aliasA","aliasB","detectionMethod",
"firstAuthor","publicationID","taxonA","taxonB","type",
"sourceDatabases","interactionID","confidenceScore")#,"provider")
coi <- c("A", "B", "aliasA", "aliasB", "taxonA", "taxonB")
coi <- c("A", "B", "taxonA", "taxonB")
tbl <- unique(tbl[, coi])
checkEquals(tbl$taxonA, rep("-", 3))
checkEquals(sort(tbl$taxonB), c("taxid:10090(mouse)","taxid:9606(human)",
"taxid:9606(human)"))
tbl.1 <- interactions(psicquic, id=c("imatinib","ABL1"), provider=provider)
freq <- as.list(table(c(tbl.1$taxonA, tbl.1$taxonB)))
checkEquals(sum(as.integer(freq)), 2 * nrow(tbl.1))
# identify a test query, and ensure that it is actually
# a meaninful test. the species-neutral query produces
# at least one human, one mouse, and many "-" (unspecified)
# for imatinib
checkTrue(length(grep("mouse", names(freq))) > 0) # just 1
checkTrue(length(grep("human", names(freq))) > 0) # 35
checkTrue(freq[["-"]] > 30) # (36 23 dec 2013)
# should get 35 interactions, with the one mouse interaction
# left out. currently returns zero...
tbl.human <- interactions(psicquic, id=c("imatinib","ABL1"),
species=c("9606", "-"),
provider=provider)
} # explore_multiSpeciesQuery
#-------------------------------------------------------------------------------
# skipped. GENEMANIA
doNot_test_GeneMANIA <- function()
{
psicquic <- PSICQUIC(test=TRUE)
tbl <- interactions(psicquic, species="9606", id="TP53", provider="GeneMANIA")
# this test fails now (30 oct 2014) due to GeneMANIA problems
# checkTrue(nrow(tbl) > 0)
} # doNot_test_genemania
#-------------------------------------------------------------------------------
if(!interactive())
paulsTests()
Try the PSICQUIC package in your browser
Any scripts or data that you put into this service are public.
PSICQUIC documentation built on Nov. 8, 2020, 6:37 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
# test_PSICQUIC.R
#-------------------------------------------------------------------------------
# options(stringsAsFactors=FALSE)
#-------------------------------------------------------------------------------
library(PSICQUIC)
library(RUnit)
library(RCurl)
#-------------------------------------------------------------------------------
kras <- "3845"
tp53 <- "7157"
myc <- "4609"
hepC <- "11103"
human <- "9606"
rat <- "10116"
stickleback <- "69293"
#-------------------------------------------------------------------------------
printf <- function(...) print(noquote(sprintf(...)))
#-------------------------------------------------------------------------------
paulsTests <- function()
{
test_initialConditions()
test_.loadRegistry()
test_ctor()
test_.retrieveData()
test_rawQuery()
test_.enumerateSearchPairs()
test_.restrictBySpecies()
test_interactions()
test_interactionsTwoGenes()
test_interactionsFourGenes()
test_handleEmbeddedSingleQuotes()
test_retrieveByPubmedID()
test_retrieveByPubmedIdOnly()
test_retrieveByOmimId()
test_retrieveByInteractionType()
test_retrieveByDetectionMethod()
test_retrieveBySpeciesId()
test_smallMoleculeWithoutSpeciesDesignation()
} # paulsTests
#-------------------------------------------------------------------------------
test_initialConditions <- function()
{
print("--- test_initialConditions")
# the PSICQUIC class avoids factors, using character strings always
# make sure that nothing in the environment will hide any failure
# to accomplish that
x <- data.frame(a=letters, b=LETTERS)
checkTrue(all(sapply(x, is.factor)))
} # test_initialConditions
#-------------------------------------------------------------------------------
test_.loadRegistry <- function()
{
print("--- test_.loadRegistry")
tbl <- PSICQUIC:::.loadRegistry()
# do some simple reasonableness tests
checkEquals(colnames(tbl), c("url"))
checkEquals(grep("^http", tbl$url), 1:nrow(tbl))
checkTrue(nrow(tbl) > 1) # ridiculously conservative number of rows
} # test_.loadRegistry
#-------------------------------------------------------------------------------
test_ctor <- function()
{
print("--- test_ctor")
psicquic <- PSICQUIC(test=TRUE)
checkTrue(is(providers(psicquic), "character"))
checkTrue(length(providers(psicquic)) > 0)
} # test_ctor
#-------------------------------------------------------------------------------
# this utility method is the ultimate endpoint of all queries for the
# interactions, and rawQuery methods.
# make sure it works when called directly
test_.retrieveData <- function()
{
print("--- test_.retrieveData")
#psicquic <- PSICQUIC(test=TRUE)
psicquic <- PSICQUIC()
available.providers <- providers(psicquic)
source <- "BioGrid"
if(!source %in% available.providers)
source <- "BIND"
if(!source %in% available.providers) # mentha ill-behaved on (14 oct 2015)
source <- "mentha"
if(!source %in% available.providers){
print("expected psicquic sources not available, skipping test_.retrieveData");
return(TRUE)
}
base.url <- PSICQUIC:::providerUrl(psicquic, source)
fixed.site.url <- sub("psicquic$", "current/search/query/", base.url)
args <- "identifier:TP53%20AND%20species:9606"
full.url <- sprintf("%s%s", fixed.site.url, args)
tbl <- PSICQUIC:::.retrieveData(full.url)
# no factors!
checkTrue(all(sapply(tbl, is.character)))
checkEquals(ncol(tbl), 15)
checkTrue(nrow(tbl) > 0) # 62 x 15 on (11 sep 2013)
suppressMessages({tbl <- PSICQUIC:::.retrieveData("http://intentionally.bogus")})
checkEquals(dim(tbl), c(0,0))
} # test_.retrieveData
#-------------------------------------------------------------------------------
test_rawQuery <- function()
{
print("--- test_rawQuery")
psicquic <- PSICQUIC(test=TRUE)
# the minimal query: id and species
available.providers <- providers(psicquic)
source <- "BioGrid"
if(!source %in% available.providers)
source <- "BIND"
if(!source %in% available.providers)
source <- "mentha"
if(!source %in% available.providers){
print("expected psicquic sources not available, skipping test_.retrieveData");
return(TRUE)
}
rawArgs.0 <- "identifier:TP53 AND species:9606"
tbl <- rawQuery(psicquic, source, rawArgs.0)
checkEquals(ncol(tbl), 15)
checkTrue(nrow(tbl) > 20)
# no column names added
checkEquals(colnames(tbl), paste("V", 1:15, sep=""))
# specify a AND b. IntAct and iRefIndex both
# report interactions between these two
if("iRefIndex" %in% available.providers){
rawArgs.1 <- "identifier:(ALK AND MAP3K3) AND species:9606"
tbl.2 <- rawQuery(psicquic, "iRefIndex", rawArgs.1)
checkEquals(nrow(tbl.2), 4)
# two references support interactions between these two at iRefIndex:
# 15657099: 1 row
# 14743216: 3 rows
rawArgs <- sprintf("%s AND pubid:(15657099 OR 14743216)", rawArgs.1)
tbl.3 <- rawQuery(psicquic, "iRefIndex", rawArgs)
checkEquals(nrow(tbl.3), 4)
rawArgs <- sprintf("%s AND pubid:15657099", rawArgs.1)
tbl.4 <- rawQuery(psicquic, "iRefIndex", rawArgs)
checkEquals(nrow(tbl.4), 1)
rawArgs <- sprintf("%s AND pubid:14743216", rawArgs.1)
tbl.5 <- rawQuery(psicquic, "iRefIndex", rawArgs)
checkEquals(nrow(tbl.5), 3)
} # if iRefIndexl
# BioGrid ALK yields these interaction types
# psi-mi:MI:0407(direct interaction) 7
# psi-mi:MI:0915(physical association) 55
if("BioGrid" %in% available.providers){
rawArgs <- sprintf("%s AND type:physical association", rawArgs.0)
tbl.6 <- rawQuery(psicquic, "BioGrid", rawArgs)
checkTrue(nrow(tbl.6) > 50) # 1331 (aug 2014) but just 55 (dec 2013)
checkEquals(ncol(tbl.6), 15)
rawArgs <- sprintf("%s AND type:direct interaction", rawArgs.0)
tbl.7 <- rawQuery(psicquic, "BioGrid", rawArgs)
checkTrue(nrow(tbl.7) >= 15) # 15 (dec 2013) 801 (aug 2014)
checkEquals(ncol(tbl.7), 15)
rawArgs <- sprintf("%s AND type:(direct interaction OR physical association)",
rawArgs.0)
tbl.8 <- rawQuery(psicquic, "BioGrid", rawArgs)
checkTrue(nrow(tbl.8) >= 62) # 62 (dec 2013) 2184 (aug 2014)
} # if BioGrid
} # test_rawQuery
#-------------------------------------------------------------------------------
test_.enumerateSearchPairs <- function()
{
print("--- test_.enumerateSearchPairs")
checkEquals(PSICQUIC:::.enumerateSearchPairs(c()), list(a=NA, b=NA))
checkEquals(PSICQUIC:::.enumerateSearchPairs(c("a")), list(a="a", b=NA))
checkEquals(PSICQUIC:::.enumerateSearchPairs(c("a", "b")), list(a="a", b="b"))
pairs <- PSICQUIC:::.enumerateSearchPairs(c("a", "b", "c"))
checkEquals(pairs, list(a=c("a", "a", "b"),
b=c("b", "c", "c")))
} # test_.enumerateSearchPairs
#-------------------------------------------------------------------------------
test_interactions <- function()
{
print("--- test_interactions")
psicquic <- PSICQUIC(test=FALSE)
providers <- c("mentha", "BioGrid")
if(!all(providers %in% providers(psicquic))){
print("expected psicquic sources not available, test_interactionTwoGenes");
return(TRUE)
}
# make sure that a failed request returns an empty data.frame
# with all of the expected column names
tbl.empty <- interactions(psicquic, provider=providers,
id="fubarCompletelyUnrecognizableGeneName",
species=stickleback)
checkEquals(dim(tbl.empty), c(0,16))
# ALK: anaplastic lymphoma kinase, entrez geneID 238
tbl <- interactions(psicquic, id="ALK",
species="9606", speciesExclusive=TRUE,
provider=providers, quiet=TRUE)
# no factors. confidence scores are (as of oct 2013) unparsed strings
checkTrue(all(sapply(tbl, is.character)))
#browser()
checkTrue(nrow(tbl) > 1) # 411 on (10 sep 2013), 165 on (6 jan 2015)
# except for "confidenceScore", which is numeric,
# all columns are character
# cross-tabulation gives a useful summary of the
# interactions: how determined, of what nature:
xtab <- as.data.frame(with(tbl, table(detectionMethod,type)),
stringsAsFactors=FALSE)
xtab <- xtab[xtab$Freq > 0,]
xtab <- xtab[order(xtab$Freq, decreasing=TRUE),]
# do a very simple single test:
# "physical association" is a common interaction type
checkTrue(length(grep("physical association", xtab$type)) >= 1)
# test now for a nonsensical call
checkException(interactions(psicquic, provider="bogus provider"),
silent=TRUE)
} # test_interactions
#-------------------------------------------------------------------------------
test_interactionsTwoGenes <- function()
{
print("--- test_interactionsTwoGenes")
psicquic <- PSICQUIC()
providers <- c("mentha", "BioGrid")
if(!all(providers %in% providers(psicquic))){
print("expected psicquic sources not available, test_interactionTwoGenes");
return(TRUE)
}
# ALK: anaplastic lymphoma kinase, entrez geneID 238
# SHC3: entrez geneID 53358
# JAK3: entrez geneID 3718
# HSPD1: entrez geneID 3329
tbl <- interactions(psicquic, species="9606", id=c("ALK", "JAK3"),
provider=providers, quiet=TRUE)
checkTrue(nrow(tbl) > 1) # (found nrow=5 on 6 jan 2015)
} # test_interactionsTwoGenes
#-------------------------------------------------------------------------------
test_interactionsFourGenes <- function()
{
print("--- test_interactionsFourGenes")
psicquic <- PSICQUIC(test=FALSE)
providers <- c("mentha", "BioGrid", "BIND")
if(!all(providers %in% providers(psicquic))){
print("expected psicquic sources not available, test_interactionFourGenes");
return(TRUE)
}
# ALK: anaplastic lymphoma kinase, entrez geneID 238
# SHC3: entrez geneID 53358
# JAK3: entrez geneID 3718
# HSPD1: entrez geneID 3329
tbl <- interactions(psicquic, species="9606", id=c("ALK", "JAK3", "SHC3", "HSPD1"),
provider=providers, quiet=TRUE)
checkTrue(nrow(tbl) > 1)
mapper <- IDMapper("9606")
tbl.2 <- addGeneInfo(mapper, tbl)
checkEquals(sort(unique(c(tbl.2$A.name, tbl.2$B.name))),
c("ALK", "HSPD1", "JAK3", "SHC3"))
} # test_interactionsFourGenes
#-------------------------------------------------------------------------------
test_retrieveByPubmedID <- function()
{
print("--- test_retrieveByPubmedID")
psicquic <- PSICQUIC()
provider <- "iRefIndex"
if(provider %in% providers(psicquic)){
genes <- c("ALK", "MAP3K3")
tbl <- interactions(psicquic,
id=genes,
species="9606",
provider=provider, quiet=TRUE)
checkEquals(ncol(tbl), 16)
checkTrue(nrow(tbl) > 0)
tbl.2 <-interactions(psicquic, species="9606",
id=genes,
provider=provider, publicationID="15657099",
quiet=TRUE)
checkTrue(is.data.frame(tbl.2)) # got 0 hits in test (29 apr 2019)
tbl.3 <-interactions(psicquic, id=genes, species="9606",
provider=provider, publicationID="14743216",
quiet=TRUE)
checkEquals(ncol(tbl.3), 16)
checkTrue(nrow(tbl.3) > 0)
tbl.4 <-interactions(psicquic, id=genes, species="9606",
provider=provider,
publicationID=c("14743216", "15657099"))
checkTrue(nrow(tbl.4) > 0)
} # if provider
} # test_retrieveByPubmedID
#-------------------------------------------------------------------------------
test_retrieveByPubmedIdOnly <- function()
{
print("--- test_retrieveByPubmedIdOnly")
# first ensure that this works as a rawQuery
psicquic <- PSICQUIC(test=TRUE)
provider <- "IntAct";
if(!provider %in% providers(psicquic)){
printf("%s not available, skipping test_retrieveByPubmedIdOnly", provider);
return(TRUE)
}
# pmid: 20936779
# Nature Methods, 2010
# A human MAP kinase interactome, Sourav Bandyopadhyay et al
tbl <- rawQuery(psicquic, provider, "species:9606 AND pubid:20936779")
checkEquals(ncol(tbl), 15)
checkTrue(nrow(tbl) > 500)
# same results through the recommended api?
tbl.2 <- interactions(psicquic, species="9606",
provider=provider, publicationID="20936779",
quiet=TRUE)
checkEquals(ncol(tbl.2), 16)
checkTrue(nrow(tbl.2) > 500)
} # test_retrieveByPubmedIdOnly
#-------------------------------------------------------------------------------
test_retrieveByOmimId <- function()
{
print("--- test_retrieveByOmimId")
psicquic <- PSICQUIC(test=TRUE)
omim.1 <- "00109135"
omim.2 <- "00137800"
# http://www.ncbi.nlm.nih.gov/omim/?term=00109135
# describes the AXL receptor tryosine kinase, geneID 558,
# oddly, this gene appears in only 7/184 of the interactions
# returned, all of which come from STRING
# thus, a buggy retrieval, which we support nonetheless
tbl.1 <- interactions(psicquic, species="9606", publicationID=omim.1)
checkEquals(length(grep(omim.1, tbl.1$publicationID)), nrow(tbl.1))
tbl.2 <- interactions(psicquic, species="9606", publicationID=omim.2)
checkEquals(length(grep(omim.2, tbl.2$publicationID)), nrow(tbl.2))
if("STRING" %in% providers(psicquic)){
tbl.3 <- interactions(psicquic, provider="STRING",
publicationID=c(omim.1, omim.2),
quiet=TRUE)
# a weak test, appropriately so: the retrieval of interactions
# by STRING, from omim ids, is rather hard to fathom
checkTrue(nrow(tbl.3) > nrow(tbl.1))
checkTrue(nrow(tbl.3) > nrow(tbl.2))
} # if STRING is available
} # test_retrieveByPubmedIdOnly
#-------------------------------------------------------------------------------
test_retrieveByInteractionType <- function()
{
print("--- test_retrieveByInteractionType")
psicquic <- PSICQUIC(test=TRUE)
provider <- "BioGrid"
if(!provider %in% providers(psicquic))
return(sprintf("%s not available", provider))
tbl <- interactions(psicquic, id="ALK", species="9606", provider="BioGrid")
checkTrue(nrow(tbl) > 50)
checkEquals(ncol(tbl), 16)
# BioGrid ALK yields these interaction types
# psi-mi:MI:0407(direct interaction) 7
# psi-mi:MI:0915(physical association) 55
tbl.1 <- interactions(psicquic, id="ALK",
species="9606", provider="BioGrid",
type="physical association", quiet=TRUE)
checkTrue(nrow(tbl.1) > 50)
checkEquals(ncol(tbl.1), 16)
tbl.2 <- interactions(psicquic, id="ALK",
species="9606", provider="BioGrid",
type="direct interaction", quiet=TRUE)
checkTrue(nrow(tbl.2) > 5)
checkEquals(ncol(tbl.2), 16)
tbl.3 <- interactions(psicquic, id="ALK",
species="9606", provider="BioGrid",
type=c("physical association",
"direct interaction"),
quiet=TRUE)
checkTrue(nrow(tbl.3) > 50)
checkEquals(ncol(tbl.3), 16)
} # test_retrieveByInteractionType
#-------------------------------------------------------------------------------
# ALK interactions learned from pull down studies ("psi-mi:MI:0096(pull down)")
# are reported (as of 19 sep 2013) by
# BioGrid, InnateDB, IntAct, MINT, Reactome-FIs, STRING, UniProt, and iRefIndex
# the related laboratory method, "psi-mi:MI:0006(anti bait coip)"
# is reported too, but just from iRefIndex.
# here we try a few combinations of provider & detection method
test_retrieveByDetectionMethod <- function()
{
psicquic <- PSICQUIC(test=FALSE)
providers <- c("BioGrid","InnateDB","IntAct","MINT","Reactome-FIs","STRING",
"UniProt","iRefIndex")
if(!all(providers %in% providers(psicquic))){
print("expected psicquic sources not available, test_retrieveByDetectionMethod");
return(TRUE)
}
tbl.0 <- interactions(psicquic, id="ALK", species="9606",
detectionMethod="pull down")
checkEquals(unique(tbl.0$detectionMethod), "psi-mi:MI:0096(pull down)")
pullDown.count <- nrow (tbl.0)
tbl.1 <- interactions(psicquic, id="ALK", species="9606",
detectionMethod="anti bait coip")
# some surprising results here: both "anti bait coip" and
# "anti tag coip are returned
antiBaitCoip.count <- nrow(tbl.1)
methods <- sort(unique(tbl.1$detectionMethod))
checkTrue(length(grep("MI:0006", methods)) > 0)
both.methods <- c("pull down", "anti bait coip")
tbl.2 <- interactions(psicquic, id="ALK", species="9606",
detectionMethod=both.methods)
bothMethods.count <- nrow (tbl.2)
checkTrue(bothMethods.count >= (pullDown.count + antiBaitCoip.count))
} # test_retrieveByDetectionMethod
#-------------------------------------------------------------------------------
# most interactions are for human, mouse, yeast
# some interactions are between an infecting agent and the human host
# explore that capability here
#
# hepatitus C virus: taxid:11103
# speciesIds() drives your browser to the NCBI taxonomy browser
#
test_retrieveBySpeciesId <- function()
{
print("--- test_retrieveBySpeciesId")
psicquic <- PSICQUIC(test=TRUE)
provider <- "BioGrid"
if(!provider %in% providers(psicquic))
return(sprintf("%s not available", provider))
tbl <- interactions(psicquic,
species=hepC, speciesExclusive=FALSE,
provider="BioGrid", quiet=TRUE)
checkTrue(nrow(tbl) > 100) # 148 on (1 oct 2013)
counts <- as.list(with(tbl, table(c(taxonA, taxonB))))
# hepC ids should be present in every interaction
checkEquals(counts$`taxid:11103`, nrow(tbl))
# make sure that there is at least one hepC/human interaction
checkTrue("taxid:9606" %in% names(counts))
# as of (01 october 2013) BioGrid has no interactions
# restricted to hepC: every hepC interactions is with
# either human or rat proteins.
# therefore a speciesExclusive species query, limited
# to hepC, will at present return an empty data.frame
# but in time this may change, and a non-empty data.frame
# will be returned, but with only hepC proteins mentioned.
tbl.1 <- interactions(psicquic,
species=hepC, speciesExclusive=TRUE,
provider="BioGrid", quiet=TRUE)
if(nrow(tbl.1) > 0)
checkEquals(unique(c(tbl.1$taxonA, tbl.1$taxonB)), "taxid:11103")
# now request interactions between hepC AND human from BioGrid
# the total count should be equal to counts$`taxid:9606`
tbl.2 <- interactions(psicquic, species=c(hepC, human), provider="BioGrid",
quiet=TRUE, speciesExclusive=TRUE)
checkEquals(nrow(tbl.2), counts$`taxid:9606`)
tbl.3 <- interactions(psicquic, species=c(stickleback, human), provider="BioGrid",
quiet=TRUE, speciesExclusive=TRUE)
} # test_retrieveBySpeciesId
#-------------------------------------------------------------------------------
test_.restrictBySpecies <- function()
{
print("--- test_.restrictBySpecies")
psicquic <- PSICQUIC()
provider <- "mentha" # reports human, mouise, fly and cattle interactions for ALK
if(!provider %in% providers(psicquic)){
print("did not find %s in providers, skipping test_.restrictBySpecies")
return(TRUE)
}
tbl <- interactions(psicquic, id="ALK", provider=provider)
if(nrow(tbl) == 0){ # mentha sometimes behaves badly
printf("did not receive any results from provider '%s', skipping test_.restrictBySpecies", provider)
return(TRUE)
}
if(length(unique(c(tbl$taxonA, tbl$taxonB))) <= 1){
print("did not find multiple species in available providers, skipping test_.restrictBySpecies")
return(TRUE)
}
checkTrue(length(unique(c(tbl$taxonA, tbl$taxonB))) > 1)
# ensure that there are some non-9606 taxa reported
# in this result. for a detailed look:
xtab.taxa <- as.data.frame(table(c(tbl$taxonA, tbl$taxonB)))
taxa.variants <- xtab.taxa$Var1
checkTrue(length(grep("9606", taxa.variants)) < length(taxa.variants))
tbl.2 <- PSICQUIC:::.restrictBySpecies(tbl, "9606")
# ensure that every surving row has a the "9606" string
# in both taxon entries
all.taxa.restricted <- unique(c(tbl.2$taxonA, tbl.2$taxonB))
checkEquals(length(all.taxa.restricted), 1)
} # test_.restrictBySpecies
#-------------------------------------------------------------------------------
# 403 lines from MINT for TP53
# something awry on line 223?
# In scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, :
# EOF within quoted string
# dim(tbl) [1] 222 16
test_handleEmbeddedSingleQuotes <- function()
{
print("--- test_handleEmbeddedSingleQuote")
psicquic <- PSICQUIC(test=TRUE)
provider <- "MINT"
if(!provider %in% providers(psicquic))
return(sprintf("%s not available", provider))
mint.tp53.url <- paste("http://www.ebi.ac.uk/Tools/webservices/psicquic/mint",
"/webservices/current/search/query",
"/identifier:TP53%20AND%20species:9606",
sep="")
raw.text <- getURL(mint.tp53.url)
# first authors O'Connor and O'Neill bolix things up if
# single quotes are not disabled as quoting characters
# make sure that this query is still a good one.
checkEquals(grep("'", raw.text), 1)
raw.row.count <- length(strsplit(raw.text, "\n")[[1]]) # 445 on (10 oct 2013)
# make sure we get the same number of rows
tbl <- interactions(psicquic, species="9606", provider=provider, id="TP53",
quiet=TRUE, speciesExclusive=FALSE)
checkEquals(nrow(tbl), raw.row.count)
} # test_handleEmbeddedSingleQuotes
#-------------------------------------------------------------------------------
# if species for a or b is unspecified, probably by the designation "-",
# we want to make sure that we accept the accompanying interaction
# one case where this occurs: ChEMBL, where a drug belongs to
# to no species. the current solution is to issue the query without
# species restriction.
test_smallMoleculeWithoutSpeciesDesignation <- function()
{
print("--- test_smallMoleculeWithoutSpeciesDesignation")
psicquic <- PSICQUIC(test=FALSE)
provider <- "ChEMBL"
if(!provider %in% providers(psicquic))
return(sprintf("%s not available", provider))
tbl.chembl <- interactions(psicquic, id="imatinib",
provider=provider,
speciesExclusive=FALSE,
quiet=FALSE)
hit.count <- nrow(tbl.chembl)
checkTrue(hit.count > 100) # 141 on (23 dec 2013)
freq <- with(tbl.chembl, as.list(table(c(taxonA, taxonB))))
# 3 species: "-" indicates "not assigned" or "unspecified"
checkEquals(sort(names(freq)), c("-", "taxid:10090(mouse)", "taxid:9606(human)"))
# since the query is only for the drug imatinib, every returned row
# will include it, and thus the "unassigned" species token should
# be found once in every row -- though perhaps sometimes in
# taxonA and sometimes in taxonB
checkEquals(hit.count, freq[["-"]])
} # test_smallMoleculeWithoutSpeciesDesignation
#-------------------------------------------------------------------------------
# multi-species queries are, in general, less interesting than single-species
# queries, with two important exceptions:
#
# 1) infection
# 2) small-molecule protein interactions
#
# this exploratory function identifies the ins and outs of case 2, using the
# ChEMBL data source
# ChEMBL or ChEMBLdb is a manually curated chemical database of
# bioactive molecules with drug-like properties.[1] It is maintained
# by the European Bioinformatics Institute (EBI), based on the
# Wellcome Trust Genome Campus, Hinxton, UK.
#
explore_multiSpeciesQuery <- function()
{
print("--- explore_multiSpeciesQuery")
provider <- "ChEMBL"
psicquic <- PSICQUIC(test=TRUE)
if(!provider %in% providers(psicquic))
return(sprintf("%s not available", provider))
base.url <- PSICQUIC:::providerUrl(psicquic, provider)
fixed.site.url <- sub("psicquic$", "current/search/query/", base.url)
#args <- "identifier:imatinib"
args <- sprintf("identifier:(%s AND %s)", "imatinib", "ABL1")
full.url <- sprintf("%s%s", fixed.site.url, args)
tbl <- PSICQUIC:::.retrieveData(full.url)
# no factors!
colnames(tbl) <- c("A","B","altA","altB","aliasA","aliasB","detectionMethod",
"firstAuthor","publicationID","taxonA","taxonB","type",
"sourceDatabases","interactionID","confidenceScore")#,"provider")
coi <- c("A", "B", "aliasA", "aliasB", "taxonA", "taxonB")
coi <- c("A", "B", "taxonA", "taxonB")
tbl <- unique(tbl[, coi])
checkEquals(tbl$taxonA, rep("-", 3))
checkEquals(sort(tbl$taxonB), c("taxid:10090(mouse)","taxid:9606(human)",
"taxid:9606(human)"))
tbl.1 <- interactions(psicquic, id=c("imatinib","ABL1"), provider=provider)
freq <- as.list(table(c(tbl.1$taxonA, tbl.1$taxonB)))
checkEquals(sum(as.integer(freq)), 2 * nrow(tbl.1))
# identify a test query, and ensure that it is actually
# a meaninful test. the species-neutral query produces
# at least one human, one mouse, and many "-" (unspecified)
# for imatinib
checkTrue(length(grep("mouse", names(freq))) > 0) # just 1
checkTrue(length(grep("human", names(freq))) > 0) # 35
checkTrue(freq[["-"]] > 30) # (36 23 dec 2013)
# should get 35 interactions, with the one mouse interaction
# left out. currently returns zero...
tbl.human <- interactions(psicquic, id=c("imatinib","ABL1"),
species=c("9606", "-"),
provider=provider)
} # explore_multiSpeciesQuery
#-------------------------------------------------------------------------------
# skipped. GENEMANIA
doNot_test_GeneMANIA <- function()
{
psicquic <- PSICQUIC(test=TRUE)
tbl <- interactions(psicquic, species="9606", id="TP53", provider="GeneMANIA")
# this test fails now (30 oct 2014) due to GeneMANIA problems
# checkTrue(nrow(tbl) > 0)
} # doNot_test_genemania
#-------------------------------------------------------------------------------
if(!interactive())
paulsTests()
Try the PSICQUIC package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.