## Copyright (C) 2020 by University of Luxembourg ## Licensed under the Apache License, Version 2.0 (the "License"); ## you may not use this file except in compliance with the License. ## You may obtain a copy of the License at ## http://www.apache.org/licenses/LICENSE-2.0 ## Unless required by applicable law or agreed to in writing, software ## distributed under the License is distributed on an "AS IS" BASIS, ## WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ## See the License for the specific language governing permissions and ## limitations under the License. stripext<-function(fn) { bits<-strsplit(fn,split="\\.")[[1]] if (length(bits)> 1) paste(head(bits,-1),collapse=".") else fn} get_mz_cmp_l<-function(id,adduct,cmpL) { ind<-match(id,cmpL$ID) mz<-cmpL$mz[[ind]] smiles<-cmpL$SMILES[[ind]] res<-if (!is.null(mz) && !is.na(mz)) { mz } else if (nchar(smiles)>0) { mde<-as.character(adduct) wh<-ADDUCTMAP[[mde]] RChemMass::getSuspectFormulaMass(smiles)[[wh]] } else stop("Both SMILES and mz fields, for ID ",id,", found empty in the compound list. Aborting.") res } calc_mz_from_formula_outer <- function(chform,adduct,id) { check_chform <- enviPat::check_chemform(ISOTOPES,chform) wind <- which(check_chform$warning) if (length(wind) > 0) stop("Cannot understand the following formulas: ", paste(check_chform$new_formula[wind],collapse = ",")) mol_form <- check_chform$new_formula l_mol <- length(mol_form) l_add <- length(adduct) adds <- ADDUCTS[Name %in% adduct,.(Name, add=as.character(Formula_add), ded=as.character(Formula_ded), charge=Charge)] dt <- dtable(ID = rep(id,each = l_add), mol_form = rep(mol_form,each = l_add), adduct = rep(adds$Name,l_mol), add = rep(adds$add,l_mol), ded = rep(adds$ded,l_mol), charge= rep(adds$charge,l_mol)) merger <- function (mol_form,add,ded) { full_form <- rep(NA_character_,length(mol_form)) both_ind <- which(add != 'FALSE' & ded != 'FALSE') add_only_ind <- which(add != 'FALSE' & ded == 'FALSE') ded_only_ind <- which(ded != 'FALSE' & add == 'FALSE') ainds <- c(both_ind,add_only_ind) full_form[ainds] <- vapply(ainds,function (i) enviPat::mergeform(mol_form[[i]],add[[i]]),FUN.VALUE = character(1), USE.NAMES = F) dinds <- c(both_ind,ded_only_ind) full_form[dinds] <- vapply(dinds,function (i) { z <- check_ded2(mol_form[[i]],ded[[i]]) if (z) enviPat::subform(mol_form[[i]],ded[[i]]) else NA_character_ }, FUN.VALUE = character(1)) full_form } dt[,("full_form"):=.(merger(mol_form,add,ded))] dt[!is.na(full_form),("mz"):=.(mapply(function(ff,ch) enviPat::isopattern(ISOTOPES,chemforms = ff, charge = ch, verbose = F)[[1]][1], full_form, charge, USE.NAMES = F))] dt[is.na(full_form),("mz"):=NA_real_] dt } calc_mz_from_formula <- function(chform,adduct,id) { check_chform <- enviPat::check_chemform(ISOTOPES,chform) wind <- which(check_chform$warning) if (length(wind) > 0) stop("Cannot understand the following formulas: ", paste(check_chform$new_formula[wind],collapse = ",")) mol_form <- check_chform$new_formula uad <- unique(adduct) uadds <- lapply(uad,function(a) ADDUCTS[Name==a,.(Name, add=as.character(Formula_add), ded=as.character(Formula_ded), charge=Charge),on=""]) names(uadds) <- uad adds <- rbindlist(l=lapply(adduct,function(a) uadds[[a]])) merger <- function (mol_form,add,ded) { res <- numeric(length(mol_form)) both_ind <- which(add != 'FALSE' & ded != 'FALSE') add_only_ind <- which(add != 'FALSE' & ded == 'FALSE') ded_only_ind <- which(ded != 'FALSE' & add == 'FALSE') ainds <- c(both_ind,add_only_ind) res[ainds] <- vapply(ainds,function (i) enviPat::mergeform(mol_form[[i]],add[[i]]),FUN.VALUE = character(1), USE.NAMES = F) dinds <- c(both_ind,ded_only_ind) res[dinds] <- vapply(dinds,function (i) { z <- check_ded2(mol_form[[i]],ded[[i]]) if (z) enviPat::subform(mol_form[[i]],ded[[i]]) else NA_character_ }, FUN.VALUE = character(1)) res } forms <- merger(mol_form,adds$add,adds$ded) mz <- the_ifelse(!is.na(forms), mapply(function(ff,ch) enviPat::isopattern(ISOTOPES,chemforms = ff, charge = ch, verbose = F)[[1]][1], forms, adds$charge, USE.NAMES = F), NA_real_) mz } calc_mz_from_smiles <- function(smiles,adduct,id) { mol <- lapply(smiles,function(s) try(RMassBank::getMolecule(s), silent = T)) check <- which(is.atomic(mol)) if (length(check) > 0) stop("Errors in SMILES with IDs:",paste(id[which],collapse = ',')) mol_form <- sapply(mol,function(x) (rcdk::get.mol2formula(x))@string,USE.NAMES = F) names(mol_form) <- id calc_mz_from_formula(mol_form,adduct,id) } calc_mz_from_smiles_outer <- function(smiles,adduct,id) { mol <- lapply(smiles,function(s) try(RMassBank::getMolecule(s), silent = T)) check <- which(is.atomic(mol)) if (length(check) > 0) stop("Errors in SMILES with IDs:",paste(id[which],collapse = ',')) mol_form <- sapply(mol,function(x) (rcdk::get.mol2formula(x))@string,USE.NAMES = F) names(mol_form) <- id calc_mz_from_formula_outer(mol_form,adduct,id) } get_col_from_cmp_l<-function(id,cname,cmpL) { ind<-match(id,cmpL$ID) x<-cmpL[[cname]][[ind]] if (!is.null(x)) x else NA } gen_clean_state_summ<-function(summ) { summ$Comments <- "" summ[c("MS1","MS2","Alignment","AboveNoise")] <- T summ["MS2rt"] <- NA_real_ summ["iMS2rt"] <- NA_integer_ summ["rt"]<-NA_real_ summ["checked"]<-'NONE' summ } pp_touch_q<-function(summ) { ## Returns indices that are ok to be auto processed. which(summ$checked==SUMM_CHK_NONE | summ$checked==SUMM_CHK_AUTO) } preProc <- function (summ,noiseFac=3,errRT=0.5,intThreshMS1=1e5,intThreshMS2=5000.) { wds<-unique(summ$wd) fn_spec<-function(wd) readRDS(file.path(wd,FN_SPEC)) message("Loading RDS-es ...") allData<-lapply(wds,fn_spec) names(allData)<-wds message("... done with RDSs") ## QA check plan: ## ## If MS1 does not exist, set MS1 to F, as well as everything else except MS2. ## If it exists, proceed to noise check. ## If noise check fails, set AboveNoise and Alignment to F. ## ## ## MS2 will be checked independently. ## If MS2 does not exist, set MS2 and Alignment to F. ## If it does, check the Alignment. ## If Alignment is wrong, set Alignment to F. ## ## Terminology: MS1 does not exist if the intensity is below the ## intensity threshold. MS2 does not exist if it was not picked up ## during the dataframe generation stage. In this case, the file ## with the corresponding ID will not be there. okinds<- pp_touch_q(summ) for (ind in okinds) { wd <- summ$wd[ind] id <- summ$ID[ind] eics<-allData[[wd]]$eic nid<-id2name(id) ii<-match(nid,MSnbase::fData(eics)[["ID"]]) #id, because id-s, not nid-s are in fData for ms1 eics; eic1<-eics[[ii]] eic<-data.frame(rt=MSnbase::rtime(eic1)/60.,intensity=MSnbase::intensity(eic1)) colnames(eic)<-c("rt","intensity") maxInt <- NULL if (nrow(eic)==0) { warning("No chromatogram for id ",id," found in", wd, " . Skipping.") next } ms1MaxInd<-which.max(eic$intensity) maxInt<-eic$intensity[[ms1MaxInd]] summ[ind,"rt"]<-eic$rt[[ms1MaxInd]] ##If MS1 does not exist, set entry to F. if (maxInt < intThreshMS1) { summ[ind,"MS1"] <- F ## Other checks automatically fail, too. summ[ind,"Alignment"] <- F summ[ind,"AboveNoise"] <- F } else { ## Noisy? if (summ[ind,"AboveNoise"]) { mInt <- mean(eic$intensity) if (maxInt < noiseFac*mInt) { summ[ind,"AboveNoise"] <- F summ[ind,"Alignment"] <- F ## If noisy, this is ## probably meaningles, so ## F. } } } ## MS2 checks. ms2<-allData[[wd]]$ms2 ms2nids<-names(ms2) if (! (nid %in% ms2nids)) { summ[ind,"MS2"] <- F summ[ind,"Alignment"] <- F } else { sp<-ms2[[nid]] ## Alignment still makes sense to be checked? if (summ[ind,"Alignment"]) { ## rtInd <- ms1MaxInd #match(maxInt,eic$intensity) rtMS1Peak <- eic$rt[[ms1MaxInd]] msms<-MSnbase::fData(sp)[,c("rtm","maxI")] colnames(msms)<-c("rt","intensity") rtInd <- which((msms$rt > rtMS1Peak - errRT) & (msms$rt < rtMS1Peak + errRT)) #Close enough? rtIndMS1 <- which((eic$rt > rtMS1Peak - errRT) & (eic$rt < rtMS1Peak + errRT)) #Filter the relevant MS1 part. eicFilt<- eic[rtIndMS1,] eicFilt<- eicFilt[which(eicFilt$intensity>intThreshMS1),] mInt<- maxInt #mean(eicFilt$intensity) rtInd <- rtInd[which(msms$intensity[rtInd]>intThreshMS2)] #Intense enough? msmsRT <- msms$rt[rtInd] msmsInt<- msms$intensity[rtInd] if (length(msmsRT) > 0) { msmsRTind <- which.min(abs(msmsRT - rtMS1Peak)) summ[ind,"iMS2rt"] <- rtInd[msmsRTind] summ[ind,"MS2rt"] <- msmsRT[msmsRTind] } else { summ[ind,"Alignment"] <- F } } } summ[ind,"checked"]<-SUMM_CHK_AUTO } summ } smiles2img <- function(smiles, kekulise=TRUE, width=300, height=300, zoom=1.3,style="cow", annotate="off", abbr="on",suppressh=TRUE, showTitle=FALSE, smaLimit=100, sma=NULL) { dep <- rcdk::get.depictor(width = width, height = height, zoom = zoom, style = style, annotate = annotate, abbr = abbr, suppressh = suppressh, showTitle = showTitle, smaLimit = smaLimit, sma = NULL) mol <- RMassBank::getMolecule(smiles) z<-rcdk::view.image.2d(mol, depictor=dep) grid::rasterGrob(z) } gen_ms2_spec_data <- function(id,tag,iMS2rt,data,luckyN=NA) { ## Given the id, tag and the index of the MS2 spectrum, return the ## dataframe of the spectrum, with luckyN number of lagerst ## intensity peaks. nid<-id2name(id) if (!is.na(iMS2rt)) { d <- data$ms2[[nid]][[iMS2rt]] if (!is.null(d)) { x<-data.frame(mz=MSnbase::mz(d),intensity=MSnbase::intensity(d)) res<-if (!is.na(luckyN)) { ord<-order(x$intensity,decreasing = T) len<-length(ord) sz<-min(len,luckyN) nx<-x[ord,] nx<-nx[1:sz,] ord<-order(nx$mz) nx[ord,] } else x return(res) } else { return(NULL)} } else return(NULL) } gen_ms2_spec_fn <- function(id,tag,adduct,set,width=6) { suppressWarnings({ iid<-as.numeric(id) iid<- if (!is.na(iid)) iid else id num <- formatC(iid,width = width,format='d',flag='0') ss<-trimws(paste(num,adduct,tag,set,sep="_"),which='both') paste(ss,".csv",sep='') }) } plot_id_msn <- function(ni, data, rtMS1, rtMS2, iMS2rt, mass, smile, tags, summ, prop, theme, pal="Dark2", cex=0.75, rt_digits=2, m_digits=4) { clean_range<-function(def,rng) { x1 <- rng[1] x2 <- rng[2] if (is.na(x1) || x1 == 0) x1 <- def[1] if (is.na(x2) || x2 == 0) x2 <- def[2] c(x1,x2) } mk_title<-function() paste("EIC (", "m/z = ", formatC(mass,format='f',digits=m_digits), ")",sep='') mk_leg_lab<-function(tag,rt) {paste(tag,"; rt= ",formatC(rt[[tag]],format='f',digits=rt_digits),"min")} sci10<-function(x) {ifelse(x==0, "0", parse(text=gsub("[+]", "", gsub("e", " %*% 10^", scales::scientific_format()(x)))))} i<-name2id(ni) dfChrMS1<-NULL dfChrMS2<-NULL dfSpecMS2<-NULL ## MS1 time series. dfschrms1<-lapply(tags,function(tag) {d<-data[[tag]]$eic ind<-match(ni,MSnbase::fData(d)[["ID"]]) cg<-d[[ind]] data.frame(rt=MSnbase::rtime(cg)/60., intensity=MSnbase::intensity(cg),tag=as.character(tag),legend=mk_leg_lab(tag,rtMS1)) }) dfChrMS1<-do.call(rbind,c(dfschrms1,list(make.row.names=F))) ## MS2 spectral time series. dfsChrMS2<-lapply(tags,function(tag) { d<-data[[tag]]$ms2[[ni]] if (!is.null(d)) { df<-MSnbase::fData(d)[,c("rtm","maxI")] colnames(df)<-c("rt","intensity") df$tag<-as.character(tag) df$legend=mk_leg_lab(tag,rtMS2) df } else NULL }) dfsChrMS2<-dfsChrMS2[!is.null(dfsChrMS2)] if (!all(sapply(dfsChrMS2,is.null))) dfChrMS2<-do.call(rbind,c(dfsChrMS2,list(make.row.names=F))) ## MS2 Spectrum. if (!all(sapply(dfsChrMS2,is.null))) { dfsSpecMS2<-lapply(tags,function(tag) { d<-data[[tag]]$ms2[[ni]] if (!is.null(d)) { ind<-iMS2rt[[tag]] if (!is.na(ind)) { x<-data.frame(mz=MSnbase::mz(d[[ind]]),intensity=MSnbase::intensity(d[[ind]])) x$tag<-tag x } else NULL } }) dfsSpecMS2<-dfsSpecMS2[!is.null(dfsSpecMS2)] dfSpecMS2<-do.call(rbind,c(dfsSpecMS2,list(make.row.names=F))) } ## Ranges if (!is.null(dfChrMS1)) { rrtMS1<-range(dfChrMS1$rt) rrtMS1 <- if (is.null(prop$ms1$rt)) rrtMS1 else clean_range(rrtMS1,prop$ms1$rt) rrtMS2<-rrtMS1 rintMS1<-range(dfChrMS1$intensity) rintMS1 <- if (is.null(prop$ms1$irng)) rintMS2 else clean_range(rintMS1,prop$ms1$irng) } if (!is.null(dfChrMS2)) { rrtMS2 <- if (is.null(prop$ms2$rt)) rrtMS2 else clean_range(rrtMS2,prop$ms2$rt) rintMS2<-range(dfChrMS2$intensity) rintMS2 <- if (is.null(prop$ms2$irng)) rintMS2 else clean_range(rintMS2,prop$ms2$irng) } if (is.data.frame(dfSpecMS2)) { rmzSpMS2<-range(dfSpecMS2$mz) rintSpMS2<-range(dfSpecMS2$intensity) rmzSpMS2<- if (is.null(prop$spec$mzrng)) rmzSpMS2 else clean_range(rmzSpMS2,prop$spec$mzrng) rintSpMS2<- if (is.null(prop$spec$irng)) rintSpMS2 else clean_range(rintSpMS2,prop$spec$irng) } ch_ms1_deco<-function(ggobj) { titMS1<-mk_title() scale_y<-if (!prop$ms1$axis=="log") { ggplot2::scale_y_continuous } else { ggplot2::scale_y_log10 } ggobj+ ggplot2::geom_line(ggplot2::aes(colour=legend),key_glyph=KEY_GLYPH)+ ggplot2::coord_cartesian(xlim = rrtMS1, ylim = rintMS1)+ ggplot2::labs(x=CHR_GRAM_X,y=CHR_GRAM_Y, title=titMS1,tag=i, colour=PLOT_MS1_LEG_TIT)+ scale_y(labels=sci10)+theme() } ch_ms2_deco<-function(ggobj) { scale_y<-if (!prop$ms2$axis=="log") { ggplot2::scale_y_continuous } else { ggplot2::scale_y_log10 } ggobj+ ggplot2::geom_linerange(ggplot2::aes(colour=legend),key_glyph=KEY_GLYPH)+ ggplot2::coord_cartesian(xlim = rrtMS2, ylim = rintMS2)+ ggplot2::labs(x=CHR_GRAM_X,y=CHR_GRAM_Y,title=NULL,subtitle = "MS2",tag = " ")+ scale_y(labels=sci10)+ ggplot2::labs(colour=PLOT_MS2_LEG_TIT)+theme() } ch_spec_deco<-function(ggobj) { scale_y<-if (!prop$spec$axis=="log") { ggplot2::scale_y_continuous } else { ggplot2::scale_y_log10 } ggobj+ ggplot2::geom_linerange(ggplot2::aes(colour=tag),key_glyph=KEY_GLYPH)+ ggplot2::coord_cartesian(xlim = rmzSpMS2, ylim = rintSpMS2)+ ggplot2::labs(subtitle="MS2",y="intensity")+ scale_y(labels=sci10)+theme() } ## MS1 time series. plMS1<- if(is.data.frame(dfChrMS1) && nrow(dfChrMS1)>0) { ch_ms1_deco(ggplot2::ggplot(data=dfChrMS1,ggplot2::aes(x=rt,y=intensity,group=legend))) } else NULL ## Empty plEmpty<-ggplot2::ggplot(data=dfChrMS1,ggplot2::aes(x=rt,y=intensity))+ggplot2::theme_void() ## MS2 time series. plMS2 <- if (!all(sapply(dfsChrMS2,is.null))) { ch_ms2_deco(ggplot2::ggplot(data=dfChrMS2,ggplot2::aes(x=rt,ymin=0,ymax=intensity,group=legend))) } else plEmpty ## Structure if (!is.null(smile) && !is.na(smile) && !nchar(smile)<1) { g<-smiles2img(smile,width=500,height=500,zoom=4.5) plStruc<-ggplot2::ggplot(data=dfChrMS1,ggplot2::aes(x=rt,y=intensity))+ ggplot2::geom_blank()+ggplot2::annotation_custom(g)+ggplot2::theme_void() } else plStruc<-plEmpty ## MS2 Spectrum if (!all(sapply(dfsChrMS2,is.null))) { plSpecMS2<-if (is.data.frame(dfSpecMS2)) { #sometimes #dfSpecMS2 ends up #as a list of #logicals; this #probably happens #when either MS2 is #bad in some way, #or the RT #intervals are #mismatched. ch_spec_deco(ggplot2::ggplot(data=dfSpecMS2, ggplot2::aes(x=mz, ymin=0, ymax=intensity,group=tag))) } else plEmpty } else plSpecMS2<-plEmpty ## Lucky N the most intense N TODO ## lckN<-if (is.data.frame(dfSpecMS2)) { ## ord<-order(dfSpecMS2$intensity,decreasing=T) ## ll<-length(ord) ## theL<-min(ll,MS2_1ST_N) ## mzN<-dfSpecMS2$mz[ord][1:theL] ## inN<-dfSpecMS2$intensity[ord][1:theL] ## df<-data.frame("m/z"=mzN,"intensity"=inN) ## message("DF:") ## str(df) ## message("---DF") ## gridExtra::tableGrob(df) #+ggplot2::labs(subtitle="Top m/z") ## } else NULL res<- if (!is.null(plMS1)) cowplot::plot_grid(plMS1,plStruc,plMS2,plEmpty,plSpecMS2,align = "hv",axis='l',ncol = 2,nrow=3,rel_widths=c(3,1)) else NULL res } add_wd_to_mzml <- function(fn,proj) { wd<-basename(tools::file_path_sans_ext(fn)) file.path(proj,wd) } getEntryFromComp<-function(entry,id,set,adduct,compTab) { ind <- which(compTab$ID %in% id & compTab$set %in% set & compTab$adduct %in% adduct) res<- if (length(ind)==1) compTab[ind,entry] else { if (length(ind)>1) { warning("Nonunique selection in comprehensive table:") for (i in ind) { message('ID: ',compTab$ID[[i]],' set: ',compTab$set[[i]],' adduct: ',compTab$adduct[[i]]) } warning("The compound set table likely containes duplicate IDs per set/adduct combination. Please correct this.") } else { warning("Entries not found for id ", id,"set ",set, "and adduct ", adduct, " .") } } res names(res)<-entry res } ## add_comp_summ <- function(ft,ctab) { ## nR<-nrow(ft) ## mzCol<-rep(NA,nR) ## nmCol<-rep("",nR) ## rtCol<-rep(NA,nR) ## for (ir in 1:nR) { ## id<-ft[ir,"ID"] ## set<-ft[ir,"set"] ## m<-ft[ir,"adduct"] ## entries<-getEntryFromComp(c("mz","Name","rt"),id,set,m,ctab) ## mzCol[[ir]]<- entries[["mz"]] ## nm<-entries[["Name"]] ## nmCol[[ir]]<- if (!is.na(nm)) nm else "" ## rtCol[[ir]]<- entries[["rt"]] ## } ## ft$mz<-mzCol ## ft$Name<-nmCol ## ft$rt<-rtCol ## ft ## } get_set_adduct <- function(s,mzml) { unique(mzml[set == s,adduct]) } vald_comp_tab<-function(df,ndf,checkSMILES=F,checkMz=F,checkNames=F) { ## Fields. if (is.null(df$ID)) stop("Column ID missing in ",ndf," .") if (checkMz && is.null(df$mz)) stop("Column mz missing in ", ndf, " .") if (checkSMILES && is.null(df$SMILES)) stop("Column SMILES missing in", ndf, " .") if (checkNames && is.null(df$Name)) warning("Column Name missing in ", ndf," , continuing without.") if (is.null(df$RT) && is.null(df$rt)) { warning("Column RT (alternatively, rt) missing in ", ndf, ", continuing without.") } else { if (is.null(df$rt)) { df$rt<-df$RT df$RT<-NULL } } ## Missing IDs? ind<-which(is.na(df$ID)) if (length(ind)>0) { for (i in ind) { warning("ID missing at row: ",i," . Big trouble ahead.") } return(NULL) } ## Unique IDs? luids<-length(unique(df$ID)) if (length(df$ID) > luids) { warning("Duplicate IDs in ", ndf, " are not allowed.") return(NULL) } ## Missing SMILES? if (checkSMILES) { ind<-which(is.na(df$SMILES)) if (length(ind)>0) { for (i in ind) { warning("SMILES missing at row: ",i, "; ID: ",df$ID[[i]]," .") } return(NULL) } lsmiles<-nrow(df) ll<-length(unique(df$SMILES)) if (ll<lsmiles) { warning("There are duplicate SMILES in the compound list. Trouble ahead.") } } ## Missing mz? if (checkMz) { ind<-which(is.na(df$mz)) if (length(ind)>0) { for (i in ind) { warning("mz missing at row: ",i, "; ID: ",df$ID[[i]]," .") } return(NULL) } } df } read_setid <- function(fn,cmpds) { assert(file.exists(fn),msg=paste("Please provide valid compounds set table:", fn)) assert(nrow(cmpds) > 0,msg="Please provide at least one compounds list.") setid <- file2tab(fn,colClasses=c(ID="character")) x<-cmpds[setid,on='ID'][,.SD,.SDcols=c(colnames(setid),'known')] sids <- unique(setid$ID) cids <- unique(cmpds$ID) diff <- setdiff(sids,cids) assert(length(diff)==0,msg=paste("The following IDs from set table have not been found in the compound table:","------",print_table(dtable(diff)),"------",sep = "\n")) x } write_conf <- function(m,fn) { m$conf$data <- file.path(m$conf$project,FN_DATA_TAB) yaml::write_yaml(x=m$conf,file=fn) } write_state <- function(m,fn_conf) { write_conf(m,fn_conf) tab2file(tab=m$input$tab$mzml,file=file.path(m$conf$project,FN_DATA_TAB)) } read_conf <- function(fn) { cf <- yaml::yaml.load_file(fn) fnl <- cf$compound$lists if (!is.null(fnl)) { nms <- character(0) for (i in 1:length(fnl)) { nms <- gen_uniq_lab(nms,pref = 'L') } names(fnl) <- nms } cf$compound$lists <- fnl ## conf_trans(cf) cf } ##' @export get_fn_comp <- function(m) { file.path(m$conf$project,FN_COMP_TAB) } ##' @export get_fn_summ <- function(m) { file.path(m$conf$project, FN_SUMM) } ##' @export get_fn_extr <- function(m) { file.path(m$conf$project, "extracted.rds") } init_state <- function(m) { m$out$tab <- list() m$input$datafiles <- NULL m$input$tab$mzml <- EMPTY_MZML lab <- gen_uniq_lab(list(),pref="L") m$input$tab$lists <- list() m$input$tab[[lab[[1]]]] <- EMPTY_CMPD_LIST m } base_conf <- function () { m <- list() m$conf <- list(project=getwd(), compounds=list(lists=list(), sets="", data=""), extr=list(fn=""), debug = F) m } extr_conf <- function(m) { m$conf$tolerance <- list("ms1 coarse"=MS1_ERR_COARSE, "ms1 fine"=MS1_ERR_FINE, "eic"=EIC_ERR, "rt"=RT_EXTR_ERR) m } presc_conf <- function(m) { m$conf$prescreen <- list("ms1_int_thresh"=1e5, "ms2_int_thresh"=2.5e3, "s2n"=3, "ret_time_shift_tol"=0.5) m } new_conf <- function() presc_conf( extr_conf( base_conf())) verify_cmpd_l <- function(dt,fn) { fields <- colnames(EMPTY_CMPD_LIST) dtflds <- colnames(dt) assert('ID' %in% dtflds, msg = paste('ID column must be present and filled in', fn)) ess <- c('SMILES','Formula','mz') pres <- ess %in% dtflds assert(length(pres) > 0, msg = paste('Compound list from ',fn, 'does not contain any of "SMILES", "Formula", or "mz". \nThe compound list needs at least one of those to be valid.')) exst <- ess[pres] x <- lapply(exst,function (nm) do.call(all,as.list(is.na(dt[[nm]])))) assert(!do.call(all,x), msg = paste('At least one of', paste(exst,collapse = ','), '\nmust contain some values in compound list from',fn)) invisible(T) } ## INPUT TRANSLATORS grab_unit <- function(entry,unit) { what <- paste0("\\<",unit,"\\>$") entry <- trimws(entry,which="both") if (grepl(what,entry)) suppressWarnings(as.numeric(sub(paste0("^(.*)",unit),"\\1",entry))) else NA_real_ } conf_trans_pres <- function(pres_list) { ## Translate and validate prescreening input. pres_list[CONF_PRES_NUM] <- sapply(pres_list[CONF_PRES_NUM],as.numeric) for (par in CONF_PRES_NUM) { assert(!suppressWarnings(is.na(pres_list[[par]])),msg=paste("Prescreen parameter",par,"is not a number.")) } for (par in CONF_PRES_TU) { xs <- grab_unit(pres_list[[par]],"s") xm <- grab_unit(pres_list[[par]],"min") x <- if (is.na(xm)) xs else xm assert(!is.na(x),msg = paste("Time unit parameter error for",par,"Only s(econds) or min(utes) allowed.")) pres_list[[par]] <- x } pres_list } ## PRESCREENING create_qa_table <- function(ms,conf_presc) { ## The first input argument is the extracted `ms`, table ## containing MS1 and MS2 spectra. The argument `conf_presc` is ## m$conf$prescreen, the prescreening parameters given in the conf ## file. ## The qa table is just a copy of ms with added quality control ## columns QA_COLS. ## The QA_FLAGS columns are flags specifying which properties of ## compounds are known well, or not. ## For each compound (mass) we ask the following questions: ## qa_ms1_exists -- does the MS1 spectrum exist at all? ## qa_ms2_exists -- do we have any MS2 spectra at all? ## qa_ms1_above_noise -- is MS1 above the noise treshold? ## qa_ms2_near -- is there any MS2 spectrum inside the tolerated ## retention time window around the MS1 peak? That is, are we ## non-RT-shifted? ## qa_ms2_good_int -- Is there any MS2 spectral intensity greater ## than the MS2 threshold and less than the MS1 peak? ## qa_pass -- did the spectrum pass all the checks? ## The columns in QA_NUM_REAL are: ## ## ms1_int -- the maximum intensity of MS1 spectrum over the ## entire run; ## ## ms1_rt -- the retention time of the peak MS1. ## The columns in QA_NUM_INT are: ## ## ms2_sel -- index of the selected MS2 spectrum; if not NA, the ## associated spectrum passed all the checks (qa_pass == T); the ## spectrum itself is in one of the member sublists of the `spec' ## column. The integer `ms2_sel' is then the index of the spectrum ## in that sublist. ## ## ms1_rt_ind -- TODO (but not important to end users). qa <- list(prescreen=conf_presc) qa$ms <- data.table::copy(ms) qa$ms[,(QA_FLAGS):=T] # All checks true by default. Dangerous, # but we need to believe in our # filters. Also, the humans who check the # results. :) qa$ms[,(QA_NUM_INT):=NA_integer_] qa$ms[,(QA_NUM_REAL):=NA_real_] qa } assess_ms1 <- function(m) { qa <- m$qa ## Calculate auxiliary variables and indices. qa$ms[,c("ms1_rt_ind"):=.(sapply(eicMS1,function(e) which.max(e$intensity)))] qa$ms[length(ms1_rt_ind)==0,("ms1_rt_ind"):=NA_integer_] qa$ms[,c("ms1_rt","ms1_int","ms1_mean"):=.(NA_real_,NA_real_,NA_real_)] qa$ms[!is.na(ms1_rt_ind),c("ms1_int","ms1_rt","ms1_mean"):=.(mapply(function (e,i) e$intensity[[i]],eicMS1,ms1_rt_ind), mapply(function (e,i) e$rt[[i]],eicMS1,ms1_rt_ind), mapply(function (e,i) mean(e$intensity),eicMS1,ms1_rt_ind))] check_ms1 <- function(qa) { qa$ms[(!is.na(ms1_int)),"qa_ms1_exists" := .(ms1_int > qa$prescreen$ms1_int_thresh)] qa$ms[is.na(ms1_int),("qa_ms1_exists"):=F] qa$ms[(!qa_ms1_exists),(QA_FLAGS):=F] qa } check_ms1_noise <- function(qa) { qa$ms[(qa_ms1_exists==T),"qa_ms1_above_noise" := .(ms1_int > qa$prescreen$s2n*ms1_mean)] qa$ms[(!qa_ms1_above_noise),c("qa_ms2_good_int","qa_ms2_near","qa_ms2_exists","qa_pass"):=F] qa } qa <- check_ms1_noise(check_ms1(qa)) m$qa <- qa m } assess_ms2 <- function(m) { presconf <- conf_trans_pres(m$conf$prescreen) ## This function takes a spectral list, looks for the members ## inside the retention time window and returns either the indices ## of those that are, or NA. pick_ms2_rtwin <- function(rtMS1,sp_list,rt_win) { rt <- sapply(sp_list,function (x) x$rt) rtl <- rtMS1 - rt_win/2. rtr <- rtMS1 + rt_win/2. which(rt > rtl & rt < rtr) } ## Only return the index which satisfies the intensity ## range. pick_ms2_int <- function(sp_list,int_lo,int_hi) { ints <- sapply(sp_list,function (x) max(x$spec$intensity)) which(int_lo < ints & ints < int_hi) } ## Test only rows that passed MS1 checks and have MS2 spec. To ## test existence of MS2, it is only necessary to make sure that ## either spec member sublist has more than one entry, or if not, ## that the single entry in the sublist is not NA. m$qa$ms[qa_ms1_exists==T,qa_ms2_exists := .(sapply(spec,function (sl) length(sl)>1 || !is.na(sl[[1]])))] irows <- which(m$qa$ms$qa_ms1_exists & m$qa$ms$qa_ms2_exists) rt_win <- 2 * presconf$ret_time_shift_tol ## List of lists of spec indices where MS2 are within the rt ## window. okind_rt_ms2 <- m$qa$ms[irows, ][, .(tmp=mapply(function (rt1,spl) pick_ms2_rtwin(rt1,spl,rt_win), ms1_rt, spec, USE.NAMES=F, SIMPLIFY=F))]$tmp m$qa$ms[irows,"qa_ms2_near"] <- sapply(okind_rt_ms2,function (x) length(x) > 0) m$qa$ms[-irows,"qa_ms2_near"] <- F ## List of lists of spec indices where MS2 are within the desired ## intensity range. okind_int_ms2 <- m$qa$ms[irows, ][, .(tmp=mapply(pick_ms2_int, spec, presconf$ms2_int_thresh, ms1_int, SIMPLIFY=F))]$tmp m$qa$ms[irows,"qa_ms2_good_int"] <- sapply(okind_int_ms2,function (x) length(x) > 0) m$qa$ms[-irows,"qa_ms2_good_int"] <- F ## Candidates for the MS2 choices. okind <- mapply(intersect,okind_int_ms2,okind_rt_ms2) m$qa$ms[irows,"qa_pass"] <- sapply(okind,function (x) length(x) > 0) m$qa$ms[-irows,"qa_pass"] <- F ## Throw out the possibly empty members. really_okind <- okind[m$qa$ms[irows, ]$qa_pass] m$qa$ms[which(qa_pass),ms2_sel:=.(mapply(function (spl,inds,ms1rt) { rtdiff <- sapply(spl[inds],function (x) abs(x$rt-ms1rt)) closest <- which.min(rtdiff) inds[[closest]] }, spec, really_okind, ms1_rt, SIMPLIFY=T))] m } gen_mz_err_f <- function(entry,msg) { eppm <- grab_unit(entry,"ppm") eda <- grab_unit(entry,"Da") shinyscreen:::assert(xor(is.na(eda), is.na(eppm)), msg = msg) if (is.na(eda)) function(mz) eppm*1e-6*mz else function (mz) eda } gen_rt_err <- function(entry,msg) { em <- grab_unit(entry,"min") es <- grab_unit(entry,"s") shinyscreen:::assert(xor(is.na(em), is.na(es)), msg = msg) if (is.na(em)) es/60. else em } fig_path <- function(top,set,group,id,suff,ext="pdf") { base <- paste("plot",set,group,id,suff,sep="_") fn <- paste0(base,".",ext) fn <- gsub("\\[","",fn) fn <- gsub("\\]","",fn) fn <- gsub("\\+","p",fn) fn <- gsub("-","m",fn) if (!is.null(top)) file.path(top,fn) else fn }