#'Various functions for mapping b/w names & database identifiers
#'Given a list of compound names or ids, find matched name or ids from selected databases
#'@description Given a list of compound names or ids
#'find matched name or IDs from selected databases
#'@param mSetObj Input the name of the created mSetObj (see InitDataObjects).
#'@param q.type Input the query type, "name" for compound names, "hmdb" for HMDB IDs, "kegg" for KEGG IDs, "pubchem"
#'for PubChem CIDs, "chebi" for ChEBI IDs, "metlin" for METLIN IDs, and "hmdb_kegg" for a both KEGG and HMDB IDs.
#'@param hmdb Logical, T to cross reference to HMDB, F to not.
#'@param pubchem Logical, T to cross reference to PubChem, F to not.
#'@param chebi Logical, T to cross reference to CheBI, F to not.
#'@param kegg Logical, T to cross reference to KEGG, F to not.
#'@param metlin Logical, T to cross reference to MetLin, F to not.
#'@author Jeff Xia \email{jeff.xia@mcgill.ca}
#'McGill University, Canada
#'License: GNU GPL (>= 2)
#'@export
CrossReferencing <- function(mSetObj=NA, q.type, hmdb=T, pubchem=T, chebi=F, kegg=T, metlin=F){
mSetObj <- .get.mSet(mSetObj);
# record the filter for 8 major databases
mSetObj$return.cols <- c(hmdb, pubchem, chebi, kegg, metlin);
# record all the data
if(!exists("name.map", where = mSetObj)){
mSetObj$name.map <- list();
}
# distribute job
mSetObj$dataSet$q.type <- q.type;
if(.on.public.web){
.set.mSet(mSetObj);
MetaboliteMappingExact(mSetObj, q.type);
mSetObj <- .get.mSet(mSetObj);
}else{
mSetObj <- MetaboliteMappingExact(mSetObj, q.type);
}
# do some sanity check
todo.inx <- which(is.na(mSetObj$name.map$hit.inx));
if(length(todo.inx)/length(mSetObj$name.map$hit.inx) > 0.5){
mSetObj$msgSet$nmcheck.msg <- c(0, "Over half of the compound IDs could not be matched to our database. Please make
sure that correct compound IDs or common compound names are used.");
}else if (length(todo.inx) > 15){
mSetObj$msgSet$nmcheck.msg <- c(2, "There are >15 compounds without matches. You can either proceed or if necessary, update these compound IDs and upload again.");
}else{
mSetObj$msgSet$nmcheck.msg <- c(1, "Name matching OK, please inspect (and manual correct) the results then proceed.");
}
return(.set.mSet(mSetObj));
}
#'Mapping from different metabolite IDs
#'@description For compound names to other ids, can do exact or approximate matches
#'For other IDs, except HMDB ID, all others may return multiple/non-unique hits
#'Multiple hits or non-unique hits will allow users to manually select
#'@param mSetObj Input the name of the created mSetObj.
#'@param q.type Inpute the query-type, "name" for compound names, "hmdb" for HMDB IDs, "kegg" for KEGG IDs, "pubchem"
#'for PubChem CIDs, "chebi" for ChEBI IDs, "metlin" for METLIN IDs, and "hmdb_kegg" for a both KEGG and HMDB IDs.
#'@author Jeff Xia \email{jeff.xia@mcgill.ca}
#'McGill University, Canada
#'License: GNU GPL (>= 2)
#'@export
#'
MetaboliteMappingExact <- function(mSetObj=NA, q.type){
mSetObj <- .get.mSet(mSetObj);
qvec <- mSetObj$dataSet$cmpd;
# variables to record results
hit.inx <- vector(mode='numeric', length=length(qvec)); # record hit index, initial 0
names(hit.inx) <- qvec;
match.values <- vector(mode='character', length=length(qvec)); # the best matched values (hit names), initial ""
match.state <- vector(mode='numeric', length=length(qvec)); # match status - 0, no match; 1, exact match; initial 0
cmpd.db <- .read.metaboanalyst.lib("compound_db.rds");
if(q.type == "hmdb"){
n <- 5 # Number of digits for V3 of HMDB
hmdb.digits <- as.vector(sapply(cmpd.db$hmdb, function(x) strsplit(x, "HMDB")[[1]][2]))
hmdb.v3.ids <- paste0("HMDB", substr(hmdb.digits, nchar(hmdb.digits)-n+1, nchar(hmdb.digits)))
hit.inx.v3 <- match(tolower(qvec), tolower(hmdb.v3.ids));
hit.inx <- match(tolower(qvec), tolower(cmpd.db$hmdb));
hit.inx[is.na(hit.inx)] <- hit.inx.v3[is.na(hit.inx)]
match.values <- cmpd.db$name[hit.inx];
match.state[!is.na(hit.inx)] <- 1;
}else if(q.type == "pubchem"){
hit.inx <- match(tolower(qvec), tolower(cmpd.db$pubchem));
match.values <- cmpd.db$name[hit.inx];
match.state[!is.na(hit.inx)] <- 1;
}else if(q.type == "chebi"){
hit.inx <- match(tolower(qvec), tolower(cmpd.db$chebi));
match.values <- cmpd.db$name[hit.inx];
match.state[!is.na(hit.inx)] <- 1;
}else if(q.type == "metlin"){
hit.inx <- match(tolower(qvec), tolower(cmpd.db$metlin));
match.values <- cmpd.db$name[hit.inx];
match.state[!is.na(hit.inx)] <- 1;
}else if(q.type == "kegg"){
hit.inx <- match(tolower(qvec), tolower(cmpd.db$kegg));
#hit.inx2 <- match(tolower(qvec), rev(tolower(cmpd.db$kegg)));
# unique hits
#nonuniq.hits <- hit.inx + hit.inx2 != nrow(cmpd.db) + 1;
#hit.inx[nonuniq.hits] <- NA;
match.values <- cmpd.db$name[hit.inx];
match.state[!is.na(hit.inx)] <- 1;
}else if(q.type == "name"){
# first find exact match to the common compound names
hit.inx <- match(tolower(qvec), tolower(cmpd.db$name));
match.values <- cmpd.db$name[hit.inx];
match.state[!is.na(hit.inx)] <- 1;
# then try to find exact match to synanyms for the remaining unmatched query names one by one
syn.db <- .read.metaboanalyst.lib("syn_nms.rds")
syns.list <- syn.db$syns.list;
todo.inx <-which(is.na(hit.inx));
if(length(todo.inx) > 0){
for(i in 1:length(syns.list)){
syns <- syns.list[[i]];
hitInx <- match(tolower(qvec[todo.inx]), tolower(syns));
hitPos <- which(!is.na(hitInx));
if(length(hitPos)>0){
# record matched ones
orig.inx<-todo.inx[hitPos];
hit.inx[orig.inx] <- i;
# match.values[orig.inx] <- syns[hitInx[hitPos]]; # show matched synnames
match.values[orig.inx] <- cmpd.db$name[i]; # show common name
match.state[orig.inx] <- 1;
# update unmatched list
todo.inx<-todo.inx[is.na(hitInx)];
}
if(length(todo.inx) == 0) break;
}
}
}else{
print(paste("Unknown compound ID type:", q.type));
# guess a mix of kegg and hmdb ids
hit.inx <- match(tolower(qvec), tolower(cmpd.db$hmdb));
hit.inx2 <- match(tolower(qvec), tolower(cmpd.db$kegg));
nohmdbInx <- is.na(hit.inx);
hit.inx[nohmdbInx]<-hit.inx2[nohmdbInx]
match.values <- cmpd.db$name[hit.inx];
match.state[!is.na(hit.inx)] <- 1;
}
# empty memory
gc();
mSetObj$name.map$query.vec <- qvec;
mSetObj$name.map$hit.inx <- hit.inx;
mSetObj$name.map$hit.values <- match.values;
mSetObj$name.map$match.state <- match.state;
return(.set.mSet(mSetObj));
}
#' Perform detailed name match
#'@description Given a query, perform compound matching.
#'@param mSetObj Input name of the created mSet Object.
#'@param q Input the query.
#'@export
#'
PerformDetailMatch <- function(mSetObj=NA, q){
mSetObj <- .get.mSet(mSetObj);
if(mSetObj$dataSet$q.type == "name"){
PerformApproxMatch(mSetObj, q);
}else{
PerformMultiMatch(mSetObj, q);
}
}
#' Perform multiple name matches
#'@description Given a query, performs compound name matching.
#'@param mSetObj Input name of the created mSet Object.
#'@param q Input the query.
#'@export
#'
PerformMultiMatch <- function(mSetObj=NA, q){
mSetObj <- .get.mSet(mSetObj);
cmpd.db <- .read.metaboanalyst.lib("compound_db.rds");
matched.inx <- which(cmpd.db$kegg %in% q);
if(length(matched.inx) > 0) {
# record all the candidates,
candidates <- cbind(matched.inx, cmpd.db$name[matched.inx]);
mSetObj$dataSet$candidates <- candidates;
}else{
mSetObj$dataSet$candidates <- NULL;
}
return(.set.mSet(mSetObj));
}
#'Perform approximate compound matches
#'@description Given a query, perform approximate compound matching
#'@param mSetObj Input the name of the created mSetObj.
#'@param q Input the q vector.
#'@export
#'
PerformApproxMatch <- function(mSetObj=NA, q){
mSetObj <- .get.mSet(mSetObj);
cmpd.db <- .read.metaboanalyst.lib("compound_db.rds");
# only for none lipids
nonLipidInx <- cmpd.db$lipid == 0;
com.nms <- cmpd.db$name[nonLipidInx];
syn.db <- .read.metaboanalyst.lib("syn_nms.rds")
syns.vec <- syn.db$syns.vec[nonLipidInx];
syns.list <- syn.db$syns.list[nonLipidInx];
matched.dist <- NULL;
q.length <- nchar(q);
s <- c(0, 0.1, 0.2);
# init withno hits, then see if any hits
mSetObj$dataSet$candidates <- NULL;
for (j in s) {
new.q <- q;
if(q.length > 32){ # note: agrep fail for exact match when length over 32 characters
new.q<-substr(q, 1, 32);
}
matched <- FALSE;
matched.inx <- agrep(new.q, syns.vec, ignore.case=T, max.distance=j, useBytes=T);
if(length(matched.inx) > 0) {
# record all the candidates,
# don't use cbind, since all will be converted to character mode
# for data.frame specify "stringsAsFactors" to prevent convert value col into factor
candidates <- data.frame(index=vector(mode = "numeric", length=length(matched.inx)),
value=vector(mode = "character", length=length(matched.inx)),
score=vector(mode = "numeric", length=length(matched.inx)),
stringsAsFactors = FALSE);
for(n in 1:length(matched.inx)){
nm.vec<-syns.list[[matched.inx[n]]];
# try approximate match, note: in some cases, split into element will break match using whole string
hit3.inx <- agrep(q,nm.vec,ignore.case=T, max.distance=j, useBytes=T);
if(length(hit3.inx)>0){
hit3.nm <- vector(mode = "character", length=length(hit3.inx));
hit3.score <- vector(mode = "numeric", length=length(hit3.inx));
for(k in 1:length(hit3.inx)){
idx <- hit3.inx[k];
hit3.nm[k] <- nm.vec[idx];
hit3.score[k] <- j + abs(nchar(nm.vec[idx])-nchar(q))/(10*nchar(q));
}
# now get the best match, the rule is that the first two character should matches
# first check if first two character are digits or characters, otherwise will cause error
matches2 <- c();
if(length(grep("^[1-9a-z]{2}", q, ignore.case=T))>0){
matches2 <- grep(paste("^", substr(q, 1, 2), sep=""), hit3.nm);
}else if (length(grep("^[1-9a-z]", q, ignore.case=T))>0){
matches2 <- grep(paste("^", substr(q, 1, 1), sep=""), hit3.nm);
}
if(length(matches2)>0){
hit3.score[matches2] <- hit3.score[matches2] - 0.05;
}
best.inx<-which(hit3.score==min(hit3.score))[1];
candidates[n,1]<-matched.inx[n];
# candidates[n,2]<-hit3.nm[best.inx]; # show matched syn names
candidates[n,2]<-com.nms[matched.inx[n]] # show common names
candidates[n,3]<-hit3.score[best.inx];
}
}
rm.inx <- is.na(candidates[,2]) | candidates[,2]=="NA" | candidates[,2]=="";
mSetObj$dataSet$candidates<-candidates[!rm.inx, ];
mSetObj$dataSet$candidates<-candidates[order(candidates[,3], decreasing=F), , drop=F];
if(nrow(candidates) > 10){
mSetObj$dataSet$candidates<-candidates[1:10,];
}
return(.set.mSet(mSetObj));
}
}
return(.set.mSet(mSetObj));
}
#'Set matched name based on user selection from all potential hits
#'@description Note: to change object in the enclosing enviroment, use "<<-"
#'@param mSetObj Input the name of the created mSetObj (see InitDataObjects).
#'@param query_nm Input the query name.
#'@param can_nm Input the candidate name.
#'@author Jeff Xia \email{jeff.xia@mcgill.ca}
#'McGill University, Canada
#'License: GNU GPL (>= 2)
#'@export
SetCandidate <- function(mSetObj=NA, query_nm, can_nm){
mSetObj <- .get.mSet(mSetObj);
query_inx <- which(mSetObj$name.map$query.vec == query_nm);
can_mat <- mSetObj$dataSet$candidates;
if(!is.null(can_mat)){
cmpd.db <- .read.metaboanalyst.lib("compound_db.rds");
can_inx <- which(can_mat[,2] == can_nm);
if(can_inx <= nrow(can_mat)){
can_inx <- which(cmpd.db$name == can_nm);
hit <- cmpd.db[can_inx, ,drop=F];
mSetObj$name.map$hit.inx[query_inx] <- can_inx;
mSetObj$name.map$hit.values[query_inx] <- hit[,2];
mSetObj$name.map$match.state[query_inx] <- 1;
# re-generate the CSV file
csv.res <- mSetObj$dataSet$map.table;
if(ncol(csv.res) > 7){ # general utilities
csv.res[query_inx, ]<-c(csv.res[query_inx, 1],
mSetObj$name.map$hit.values[query_inx],
hit$hmdb_id,
hit$pubchem_id,
hit$chebi_id,
hit$kegg_id,
hit$metlin_id,
hit$smiles,
1);
}else{ # pathway analysis
csv.res[query_inx, ]<-c(csv.res[query_inx, 1],
mSetObj$name.map$hit.values[query_inx],
hit$hmdb_id,
hit$pubchem_id,
hit$kegg_id,
hit$smiles,
1);
}
write.csv(csv.res, file="name_map.csv", row.names=F);
mSetObj$dataSet$map.table <- csv.res;
}else{ #no match
mSetObj$name.map$hit.inx[query_inx] <- 0;
mSetObj$name.map$hit.values[query_inx] <- "";
mSetObj$name.map$match.state[query_inx] <- 0;
print("No name matches found.")
}
}
if(.on.public.web){
.set.mSet(mSetObj);
return(query_inx);
}else{
return(.set.mSet(mSetObj));
}
}
##############################################
##############################################
########## Utilities for web-server ##########
##############################################
##############################################
#'Get all candidate compound names for a given index
#'@description Returns 3 coloumns - inx, name, score
#'@param mSetObj Input the name of the created mSetObj (see InitDataObjects)
#'@author Jeff Xia \email{jeff.xia@mcgill.ca}
#'McGill University, Canada
#'License: GNU GPL (>= 2)
#'@export
GetCandidateList <- function(mSetObj=NA){
mSetObj <- .get.mSet(mSetObj);
can_hits <- mSetObj$dataSet$candidates;
if(is.null(can_hits)){
can.mat <- matrix("", nrow=1, ncol= 6);
}else{
# construct the result table with cells wrapped in html tags
# the unmatched will be highlighted in different background
can.mat <- matrix("", nrow=nrow(can_hits)+1, ncol= 6);
cmpd.db <- .read.metaboanalyst.lib("compound_db.rds");
# need to exclude lipids, to be consistent with approx matching part so that same index can be used to fetch db entries
nonLipidInx <- cmpd.db$lipid == 0;
cmpd.db <-cmpd.db[nonLipidInx,];
for (i in 1:nrow(mSetObj$dataSet$candidates)){
hit.inx <- mSetObj$dataSet$candidates[i, 1];
hit.name <- mSetObj$dataSet$candidates[i, 2];
hit <-cmpd.db[hit.inx, ,drop=F];
can.mat[i, ] <- c(hit.name,
paste(ifelse(hit$hmdb_id=="NA","", paste("<a href=http://www.hmdb.ca/metabolites/", hit$hmdb_id, " target='_blank'>",hit$hmdb_id,"</a>", sep="")), sep=""),
paste(ifelse(hit$pubchem_id=="NA", "", paste("<a href=http://pubchem.ncbi.nlm.nih.gov/summary/summary.cgi?cid=", hit$pubchem_id," target='_blank'>", hit$pubchem_id,"</a>", sep="")), sep=""),
paste(ifelse(hit$chebi_id=="NA","", paste("<a href=http://www.ebi.ac.uk/chebi/searchId.do?chebiId=", hit$chebi_id, " target='_blank'>",hit$chebi_id,"</a>", sep="")), sep=""),
paste(ifelse(hit$kegg_id=="NA","",paste("<a href=http://www.genome.jp/dbget-bin/www_bget?", hit$kegg_id, " target='_blank'>", hit$kegg_id,"</a>", sep="")), sep=""),
paste(ifelse(hit$metlin_id=="NA","",paste("<a href=http://metlin.scripps.edu/metabo_info.php?molid=", hit$metlin_id," target='_blank'>",hit$metlin_id,"</a>", sep="")), sep=""));
}
# add "none" option
can.mat[nrow(mSetObj$dataSet$candidates)+1,] <- c("None of the above", "", "", "", "", "");
}
# add the hit columns
return.cols <- c(TRUE, mSetObj$return.cols);
if(.on.public.web){
return(as.vector(can.mat[,return.cols, drop=F]));
}
mSetObj$name.map$hits.candidate.list <- can.mat[,mSetObj$return.cols, drop=F]
return(.set.mSet(mSetObj));
}
GetCanListRowNumber <- function(mSetObj=NA){
mSetObj <- .get.mSet(mSetObj);
if(is.null(mSetObj$dataSet$candidates)){
return(1);
}else{
return(nrow(mSetObj$dataSet$candidates)+1); # include the "none" row
}
}
GetQuery <- function(mSetObj=NA, inx){
mSetObj <- .get.mSet(mSetObj);
return(mSetObj$dataSet$cmpd[inx]);
}
#'Return the final (after user selection) map as dataframe
#'@description Returns three columns: original name, HMDB name and KEGG ID,
#'for enrichment and pathway analysis, respectively
#'@param mSetObj Input the name of the created mSetObj (see InitDataObjects)
#'@author Jeff Xia \email{jeff.xia@mcgill.ca}
#'McGill University, Canada
#'License: GNU GPL (>= 2)
#'@export
#'
GetFinalNameMap <- function(mSetObj=NA){
mSetObj <- .get.mSet(mSetObj);
hit.inx <- mSetObj$name.map$hit.inx;
hit.values <- mSetObj$name.map$hit.values;
match.state <- mSetObj$name.map$match.state;
qvec <- mSetObj$dataSet$cmpd;
nm.mat <- matrix(nrow=length(qvec), ncol=4);
colnames(nm.mat) <- c("query", "hmdb", "kegg", "hmdbid");
cmpd.db <- .read.metaboanalyst.lib("compound_db.rds");
for (i in 1:length(qvec)){
hit <-cmpd.db[hit.inx[i], ,drop=F];
if(match.state[i]==0){
hmdb.hit <- NA;
hmdb.hit.id <- NA;
kegg.hit <- NA;
}else{
hmdb.hit <- ifelse(nchar(hit.values[i])==0, NA, hit.values[i]);
hmdb.hit.id <- ifelse(nchar(hit$hmdb_id)==0, NA, hit$hmdb_id);
kegg.hit <- ifelse(nchar(hit$kegg_id)==0, NA, hit$kegg_id);
}
nm.mat[i, ]<-c(qvec[i], hmdb.hit, kegg.hit, hmdb.hit.id);
}
return(as.data.frame(nm.mat));
}
#'Get mapping table
#'@description Return results from compound name mapping in a table
#'@param mSetObj Input the name of the created mSetObj (see InitDataObjects)
#'@export
GetMapTable <- function(mSetObj=NA){
mSetObj <- .get.mSet(mSetObj);
print(xtable::xtable(mSetObj$dataSet$map.table, caption="Result from Compound Name Mapping"),
tabular.environment = "longtable", caption.placement="top", size="\\scriptsize");
}
#'Creates the mapping result table
#'@param mSetObj Input the name of the created mSetObj (see InitDataObjects)
#'@export
CreateMappingResultTable <- function(mSetObj=NA){
mSetObj <- .get.mSet(mSetObj);
qvec <- mSetObj$dataSet$cmpd;
if(is.null(qvec)){
return();
}
# style for highlighted background for unmatched names
pre.style<-NULL;
post.style<-NULL;
# style for no matches
if(mSetObj$dataSet$q.type == "name"){
no.prestyle<-"<strong style=\"background-color:yellow; font-size=125%; color=\"black\">";
no.poststyle<-"</strong>";
}else{
no.prestyle<-"<strong style=\"background-color:red; font-size=125%; color=\"black\">";
no.poststyle<-"</strong>";
}
hit.inx<-mSetObj$name.map$hit.inx;
hit.values<-mSetObj$name.map$hit.values;
match.state<-mSetObj$name.map$match.state;
# construct the result table with cells wrapped in html tags
# the unmatched will be highlighted in different background
html.res <- matrix("", nrow=length(qvec), ncol=8);
csv.res <- matrix("", nrow=length(qvec), ncol=9);
colnames(csv.res) <- c("Query", "Match", "HMDB", "PubChem", "ChEBI", "KEGG", "METLIN", "SMILES", "Comment");
cmpd.db <- .read.metaboanalyst.lib("compound_db.rds");
for (i in 1:length(qvec)){
if(match.state[i]==1){
pre.style<-"";
post.style="";
}else{ # no matches
pre.style<-no.prestyle;
post.style<-no.poststyle;
}
hit <-cmpd.db[hit.inx[i], ,drop=F];
html.res[i, ]<-c(paste(pre.style, qvec[i], post.style, sep=""),
paste(ifelse(match.state[i]==0, "", hit.values[i]), sep=""),
paste(ifelse(match.state[i]==0 || is.na(hit$hmdb_id) || hit$hmdb_id=="" || hit$hmdb_id=="NA","-", paste("<a href=http://www.hmdb.ca/metabolites/", hit$hmdb_id, " target='_blank'>",hit$hmdb_id,"</a>", sep="")), sep=""),
paste(ifelse(match.state[i]==0 || is.na(hit$pubchem_id) || hit$pubchem_id=="" || hit$pubchem_id=="NA", "-", paste("<a href=http://pubchem.ncbi.nlm.nih.gov/summary/summary.cgi?cid=", hit$pubchem_id," target='_blank'>", hit$pubchem_id,"</a>", sep="")), sep=""),
paste(ifelse(match.state[i]==0 || is.na(hit$chebi_id) || hit$chebi_id==""|| hit$chebi_id=="NA","-", paste("<a href=http://www.ebi.ac.uk/chebi/searchId.do?chebiId=", hit$chebi_id, " target='_blank'>",hit$chebi_id,"</a>", sep="")), sep=""),
paste(ifelse(match.state[i]==0 || is.na(hit$kegg_id) || hit$kegg_id==""|| hit$kegg_id=="NA","-",paste("<a href=http://www.genome.jp/dbget-bin/www_bget?", hit$kegg_id, " target='_blank'>", hit$kegg_id,"</a>", sep="")), sep=""),
paste(ifelse(match.state[i]==0 || is.na(hit$metlin_id) || hit$metlin_id==""|| hit$metlin_id=="NA","-",paste("<a href=http://metlin.scripps.edu/metabo_info.php?molid=", hit$metlin_id," target='_blank'>",hit$metlin_id,"</a>", sep="")), sep=""),
ifelse(match.state[i]!=1,"View",""));
csv.res[i, ]<-c(qvec[i],
ifelse(match.state[i]==0, "NA", hit.values[i]),
ifelse(match.state[i]==0, "NA", hit$hmdb_id),
ifelse(match.state[i]==0, "NA", hit$pubchem_id),
ifelse(match.state[i]==0, "NA", hit$chebi_id),
ifelse(match.state[i]==0, "NA", hit$kegg_id),
ifelse(match.state[i]==0, "NA", hit$metlin_id),
ifelse(match.state[i]==0, "NA", hit$smiles),
match.state[i]);
}
# return only columns user selected
# add query and match columns at the the beginning, and 'Detail' at the end
return.cols <- c(TRUE, TRUE, mSetObj$return.cols, TRUE);
html.res <- html.res[,return.cols, drop=F];
csv.res <- csv.res[,return.cols, drop=F];
# store the value for report
mSetObj$dataSet$map.table <- csv.res;
write.csv(csv.res, file="name_map.csv", row.names=F);
if(.on.public.web){
.set.mSet(mSetObj);
return(as.vector(html.res));
}else{
return(.set.mSet(mSetObj));
}
}
GetHitsRowNumber<-function(mSetObj=NA){
mSetObj <- .get.mSet(mSetObj);
return(length(mSetObj$name.map$hit.inx));
}
GetPathNames<-function(mSetObj=NA){
mSetObj <- .get.mSet(mSetObj);
return(mSetObj$dataSet$path.res[,1]);
}
GetMatchedCompounds<-function(mSetObj=NA){
mSetObj <- .get.mSet(mSetObj);
return(mSetObj$dataSet$path.res[,2]);
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.