| Title: | Internal Fragment Identification from Top-Down Mass Spectrometry |
|---|---|
| Description: | Top-Down mass spectrometry aims to identify entire proteins as well as their (post-translational) modifications or ions bound (eg Chen et al (2018) <doi:10.1021/acs.analchem.7b04747>). The pattern of internal fragments (Haverland et al (2017) <doi:10.1007/s13361-017-1635-x>) may reveal important information about the original structure of the proteins studied (Skinner et al (2018) <doi:10.1038/nchembio.2515> and Li et al (2018) <doi:10.1038/nchem.2908>). However, the number of possible internal fragments gets huge with longer proteins and subsequent identification of internal fragments remains challenging, in particular since the the accuracy of measurements with current mass spectrometers represents a limiting factor. This package attempts to deal with the complexity of internal fragments and allows identification of terminal and internal fragments from deconvoluted mass-spectrometry data. |
| Authors: | Wolfgang Raffelsberger [aut, cre] |
| Maintainer: | Wolfgang Raffelsberger <[email protected]> |
| License: | GPL-3 |
| Version: | 1.0.2 |
| Built: | 2025-02-15 04:40:11 UTC |
| Source: | https://github.com/cran/wrTopDownFrag |
This function provides basic settings for what types of fragments may accomodate which type of modifications : $knownMods: information about which modifications may be considered, $specAAMod: specifc AA sites (if applicable), $specAAMod: specifc AA sites (if applicable). For example, here 'p' codes for gain of mass for HPO3 only at S, T and Y residues. Note: $knownMods$Nterm and $knownMods$Cterm are treated as mutually exclusive
AAfragSettings(outTy = "all")AAfragSettings(outTy = "all")
outTy |
(character) default "all" or any of the list-elements |
list ($knownMods, $knspecAAMods, $modChem, $neutralLossOrGain)
makeFragments, fragmentSeq, massDeFormula
AAfragSettings()AAfragSettings()
Adjust/add mass for modifications from 'modTy' to all peptides in 'pepTab' based on count 'cou' of occurances of modifications :
Either fixed or variable modifications will be added to the mass of initial peptides from argument papTab.
Terminal ionization (like 'b' or 'y' -fragments) is treated as fixed modification and the resulting masses will correspond to standard mono-protonated ions.
Since variable and fixed modification types can't be run in a single instance, the function has to get calles twice, it is recommended to always start with the fixed modfications,
In the case of fixed modifications (like defining 'b' or 'y' fragments) neutral peptide masses should be given to add the corresponding mass-shift (and to obtain mono-protonated ions).
In case of variable modifications (like 'd' or 'p'), the corresponding ions from the fixed modifications should get furnished to add the corresponding mass-shift,
the masses resulting from the initial fixed modifications run can be used.
Note, that transforming a neutral precursor M into MH+ is also considered a modification.
The results are also correct with obligatory fragments that can't occur the same time (eg x & y ions can't be same time, need to make add'l lines...).
This function has a multiprocessor mode, with small data-sets (like the toy example below) there is typcally no gain in performance.
addMassModif( cou, pepTab, combTerm, modTy, lastIndex = NULL, modChem = NULL, basVarMod = "basMod", massTy = "mono", knownMods = NULL, nProc = 1, parallDefault = TRUE, silent = FALSE, debug = FALSE, callFrom = NULL )addMassModif( cou, pepTab, combTerm, modTy, lastIndex = NULL, modChem = NULL, basVarMod = "basMod", massTy = "mono", knownMods = NULL, nProc = 1, parallDefault = TRUE, silent = FALSE, debug = FALSE, callFrom = NULL )
cou |
(list) list of matrixes with counts for number of modifications per peptide |
pepTab |
(matrix) table with peptide properties |
combTerm |
(matrix) table with separate rows for $basMod that are exclusive (ie can't be accumulated, eg x & y ions) |
modTy |
(character) list of modification types to be considered |
lastIndex |
(integer) index-1 (ie last index from prev matrix) from which new peptide-variants should start from |
modChem |
(character) optional modifications |
basVarMod |
(character) toggle if fixed ('basMod') or variable ('varMod') modificatons should be calculated |
massTy |
(character) default 'mono' |
knownMods |
(list) optional custom definition whoch modification is N-term, etc (see |
nProc |
(integer) number of processors in case of multi-processor use (requires Bioconductor package |
parallDefault |
(logical) for use of other/previously set |
silent |
(logical) suppress messages |
debug |
(logical) for bug-tracking: more/enhanced messages and intermediate objects written in global name-space |
callFrom |
(character) allows easier tracking of message(s) produced |
list of $pepTab (table of peptide as single charge positive ions), $abc ('representative' list of all combinations to add). Main result in $pepTab
pep1 <- c(pe1="KPEPTI") # The table of possible terminal fragments (for simplicity terminal only) pepTab1 <- makeFragments(pep1, min=3, max=7, internFra=FALSE) # Which fragment may be subject to how many modification (including ionization by H+) cou1 <- countPotModifAAs(pepTab=pepTab1, modTy=list(basMod=c("b","y"))) # Add modifications (here: ionize all pepptides by H+) preMa1 <- addMassModif(cou=cou1$cou, pepTab=pepTab1, combTerm=cou1$combTerm, modTy=list(basMod=c("b","y")), basVarMod="basMod") preMa1 ## Example including variable modifications modT3 <- list(basMod=c("b","y"),varMod=c("p","h","d")) cou3 <- countPotModifAAs(pepTab=pepTab1, modTy=modT3) ## Now we re-use/inject the results for the fixed modificatons preMa3 <- addMassModif(cou=cou3$cou, pepTab=preMa1$pepTab, combTerm=cou1$combTerm, modTy=modT3, basVarMod="varMod") head(preMa3$pepTab,12)pep1 <- c(pe1="KPEPTI") # The table of possible terminal fragments (for simplicity terminal only) pepTab1 <- makeFragments(pep1, min=3, max=7, internFra=FALSE) # Which fragment may be subject to how many modification (including ionization by H+) cou1 <- countPotModifAAs(pepTab=pepTab1, modTy=list(basMod=c("b","y"))) # Add modifications (here: ionize all pepptides by H+) preMa1 <- addMassModif(cou=cou1$cou, pepTab=pepTab1, combTerm=cou1$combTerm, modTy=list(basMod=c("b","y")), basVarMod="basMod") preMa1 ## Example including variable modifications modT3 <- list(basMod=c("b","y"),varMod=c("p","h","d")) cou3 <- countPotModifAAs(pepTab=pepTab1, modTy=modT3) ## Now we re-use/inject the results for the fixed modificatons preMa3 <- addMassModif(cou=cou3$cou, pepTab=preMa1$pepTab, combTerm=cou1$combTerm, modTy=modT3, basVarMod="varMod") head(preMa3$pepTab,12)
Check & complete settings for mixed of variable and fixed modifications. The final format is a list with $basMod, $varMod and $varMo2
checkModTy(modTy, knownMods = NULL, silent = TRUE, callFrom = NULL)checkModTy(modTy, knownMods = NULL, silent = TRUE, callFrom = NULL)
modTy |
(character) list of modification types to be considered |
knownMods |
(character) optonal custom list of known modifications, default from |
silent |
(logical) suppress messages |
callFrom |
(character) allow easier tracking of message(s) produced |
corrected list of mixed of variable and fixed modifications ($basMod, $varMod and $varMo2)
modTy1 <- list(basMod=c("b","y","h"),varMod=c("p","o","q")) checkModTy(modTy1)modTy1 <- list(basMod=c("b","y","h"),varMod=c("p","o","q")) checkModTy(modTy1)
Use for all preparing all combinations of non-compulsatory, ie variable, mass modifications
Variable modifications may or may not be present. Thus, for a given amino-acid with a variable modification two versions of the molecular weight need to be considered.
Most (variable) modifications are linked to a type of amino acid, like serine-residues for phosphorlylation.
Thus in this case, each instance of the amino acid in question may or may not be modified.
So, for example if there are 2 serines, 0, 1 or 2 phosphorylation modifications may be present.
For this reason the is the argument nMax to stay within biologically relevant ranges (external knowledge) and reduce complexity significantly.
Some modifications are exclusive to others, argument notSingle : An (artificially occuring) de-phosphorylation event during fragmentation can only happen if the amino acid was already phosphorylated in the first place.
combinateAllAndSum( nMax, modVal, notSingle = NULL, silent = TRUE, callFrom = NULL )combinateAllAndSum( nMax, modVal, notSingle = NULL, silent = TRUE, callFrom = NULL )
nMax |
(integer or data.frame with 1 line) maximum number of modifications |
modVal |
(numeric, has to have names !) the change of molecular mass introduced by given modifications (as specified by the name of the value) |
notSingle |
(character) names of 'modVal' where 1st element of 'notSingle' cannot happen/appear if 2nd element not present (eg de-phospho/phosphorylation) |
silent |
(logical) suppress messages |
callFrom |
(character) allow easier tracking of message(s) produced |
named (concatenated names of modVal) numeric vector
## to follow easily the results, hypothetical mass-modification values were chosen mo1 <- c(a=10, b=1, c=0.1, d=0.01); nMa1 <- c(1,2,0,3) combinateAllAndSum(nMa1, mo1) ## # like 'b' for phospho & 'd' for de-phospho (which can't happen without phospho event) combinateAllAndSum(nMa1, mo1, notSingle=c("d","b"))## to follow easily the results, hypothetical mass-modification values were chosen mo1 <- c(a=10, b=1, c=0.1, d=0.01); nMa1 <- c(1,2,0,3) combinateAllAndSum(nMa1, mo1) ## # like 'b' for phospho & 'd' for de-phospho (which can't happen without phospho event) combinateAllAndSum(nMa1, mo1, notSingle=c("d","b"))
This functions helps identifying fragments ('parent') characterized by a start- and end-position, that got split into 2 'children' fragments.
So, each one of the new 'children' conserves either the start- or end-site of the parent and the the remaining ends are on consecutive positions.
For example if the sequence 'BCDEFG' (parent) gets split into 'BCD' (positions 1-3) and 'EFG' (positions 4-6),
this will be identified as a children/parent 'family' which could be represented as 'a+b=c' case.
Note : At this point only settings with 2 children are considered, for more complex scenarions one may build trees using buildTree (however, this function does not identify 'parents').
In proteomics-applications some start- and end-sites may occur multiple times, representing eg unmodified and modified versions of the same basal peptide-sequence.
Such duplicated start- and end-cases are handeled as allowed, a 'child' (characterized by its start- and end-position) may occur multiple times, and the
corresponding redundant rownames (eg peptide sequence like 'BCD') will be conserved. However, information reflecting eg different peptide modifications must be stored separately.
If redudant start- and end-sites accur with different row-names, repeated start- and end-sites will display NA.
countChildrenParent( fragments, output = "count", silent = FALSE, callFrom = NULL )countChildrenParent( fragments, output = "count", silent = FALSE, callFrom = NULL )
fragments |
(matrix or data.frame) integer values in 1st column, for start site of fragment, and in 2nd column as end-sites of fragments, rownames as IDs |
output |
(character) choose simply returning results as counts or as list with |
silent |
(logical) suppress messages |
callFrom |
(character) allows easier tracking of message(s) produced |
either numeric vector with cumulated counts (corresponding to rows of fragments) or list with $count and $detailIndex (list with indexes refering to non-redundant entries of all a+b=c settings identified)
simpleFragFig for graphical representation,countSameStartEnd; for building longer consecutive trees (without identification of 'parent') buildTree and contribToContigPerFrag
frag3 <- cbind(beg=c(4,2,3,7,13,13,15, 2,9,2,9), end=c(14,6,12,8,18,20,20, 8,12,12,18)) rownames(frag3) <- c("K","A","E","B","C","D","F", "H","G","I","J") countChildrenParent(frag3) ## example with duplicate start- and end-position positions frag3c <- cbind(beg=c(4,2,3,7, 7,13, 13,13,15, 2,9,2,9,9), end=c(14,6,12,8, 8,18, 18,20,20, 8,12,12,12,18)) rownames(frag3c) <- c("K","A","E", "B","B", "C","C","D","F", "H","G","I","G","J") countChildrenParent(frag3c, out="det")frag3 <- cbind(beg=c(4,2,3,7,13,13,15, 2,9,2,9), end=c(14,6,12,8,18,20,20, 8,12,12,18)) rownames(frag3) <- c("K","A","E","B","C","D","F", "H","G","I","J") countChildrenParent(frag3) ## example with duplicate start- and end-position positions frag3c <- cbind(beg=c(4,2,3,7, 7,13, 13,13,15, 2,9,2,9,9), end=c(14,6,12,8, 8,18, 18,20,20, 8,12,12,12,18)) rownames(frag3c) <- c("K","A","E", "B","B", "C","C","D","F", "H","G","I","G","J") countChildrenParent(frag3c, out="det")
Makes table 'cou' with counts of (potential) modification sites based on column 'seq' in matrix 'pepTab'. Note: if multiple N-or C-term modifs, then only the first is shown in resulting table 'cou'.
countPotModifAAs( pepTab, modTy, maxMod = c(p = 3, h = 1, k = 1, o = 1, m = 1, n = 1, u = 1, r = 1, s = 1), specAAMod = NULL, knownMods = NULL, silent = FALSE, callFrom = NULL, debug = FALSE )countPotModifAAs( pepTab, modTy, maxMod = c(p = 3, h = 1, k = 1, o = 1, m = 1, n = 1, u = 1, r = 1, s = 1), specAAMod = NULL, knownMods = NULL, silent = FALSE, callFrom = NULL, debug = FALSE )
pepTab |
(matrix) peptide sequences, start and end sites, typically result from |
modTy |
(list) modifications : $basMod for character vector of fixed modifications and $varMod for variable modifications. For one letter-code see AAfragSettings("modChem") |
maxMod |
(integer) maximal number variable modifications will be considered in given fragment (may increase complexity and RAM consumption) |
specAAMod |
(list) optional custom list showing which AA to be considered with which (one-letter) modification code (default |
knownMods |
(list) optional custom list showing which modification appears at what type of location, eg N-terminal, internal ... (default |
silent |
(logical) suppress messages |
callFrom |
(character) allow easier tracking of message(s) produced |
debug |
(logical) for bug-tracking: more/enhanced messages and intermediate objects written in global name-space |
list of matrixes $cou and $combTerm, with number of modifications per peptides (line in 'pepTab') for basMod, varMod & varMo2
protP2 <- c(mesp="MESPEPTIDES", pepe="PEPEPEP") pepTab1 <- makeFragments(protTab=protP2, minFra=6, internFr=TRUE, massTy="mono") cou1 <- countPotModifAAs(pepTab=pepTab1, modTy=list(basMod=c("b","y"), varMod=c("p","h")), debug=FALSE) modTy2 <- list(basMod=c("b","y","h"), varMod=c("x","p","o","q","e","j")) cou2 <- countPotModifAAs(pepTab=pepTab1, modTy=modTy2)protP2 <- c(mesp="MESPEPTIDES", pepe="PEPEPEP") pepTab1 <- makeFragments(protTab=protP2, minFra=6, internFr=TRUE, massTy="mono") cou1 <- countPotModifAAs(pepTab=pepTab1, modTy=list(basMod=c("b","y"), varMod=c("p","h")), debug=FALSE) modTy2 <- list(basMod=c("b","y","h"), varMod=c("x","p","o","q","e","j")) cou2 <- countPotModifAAs(pepTab=pepTab1, modTy=modTy2)
Evaluate selected lines of pepTab (iso-mass) for preferential cutting sites. Such sites are taken by default from .prefFragPattern() simplified from a publication
by the Kelleher group (Haverland 2017, J Am Soc Mass Spectrom) or can be furnished by the user.
evalIsoFragm( z, prefFragPat = NULL, seqCol = "seq", silent = FALSE, callFrom = NULL )evalIsoFragm( z, prefFragPat = NULL, seqCol = "seq", silent = FALSE, callFrom = NULL )
z |
(matrix) main input, must contain cols specified as seqCol and "no","tailAA","precAA" |
prefFragPat |
(matrix) specifies preferential fragmentation (which combination of AA to consider cols cTer,nTer,score), default made by |
seqCol |
(character) column names for the column containing the sequence to search for preferential cutting sites |
silent |
(logical) suppress messages |
callFrom |
(character) allows easier tracking of message(s) produced |
line ID-numbers (pepTab[,"no"]) for those below median score (ie to remove from pepTab) or NULL if nothing to remove due to preferential fragmentation
peTab <- matrix(c("9","13","14","15", "LPVIAGHEAAG","PVIAGHEAAGI","EKKPFSI","KKPFSIE", "P","L","E","E", "I","V","E","E"),nr=4,dimnames=list(NULL,c("no","seq","precAA","tailAA"))) evalIsoFragm(peTab)peTab <- matrix(c("9","13","14","15", "LPVIAGHEAAG","PVIAGHEAAGI","EKKPFSI","KKPFSIE", "P","L","E","E", "I","V","E","E"),nr=4,dimnames=list(NULL,c("no","seq","precAA","tailAA"))) evalIsoFragm(peTab)
Makes internal/terminal fragments of a SINGLE peptide/protein input (as single letter amino-acid code) and returns list of all possible sequences ($full, $Nter, $Cter, $inter).
fragmentSeq( sequ, minSize = 3, maxSize = 300, internFragments = TRUE, separTerm = FALSE, keepRedSeqs = TRUE, prefName = NULL, silent = FALSE, callFrom = NULL )fragmentSeq( sequ, minSize = 3, maxSize = 300, internFragments = TRUE, separTerm = FALSE, keepRedSeqs = TRUE, prefName = NULL, silent = FALSE, callFrom = NULL )
sequ |
(character, length=1) sequence used for fragmenting, as as mono-aminoacid letter code (so that cuting will be perfomed between all the letters/characters) |
minSize |
(integer) min number of AA residues for considering peptide fragments |
maxSize |
(integer) max number of AA residues for considering peptide fragments |
internFragments |
(logical) logical (return only terminal fragments if 'FALSE') |
separTerm |
(logical) if 'TRUE', separate N-terminal, C-terminal and internal fragments in list |
keepRedSeqs |
(logical) if 'FALSE' remove fragments with redundant content (but my be from different origin in 'sequ'); remove redundant so far only when no separation of Nterm/Cterm/intern as list |
prefName |
(logical) alternative name for all fragments (default the sequence itself), avoid separators '.' and '-' |
silent |
(logical) suppress messages |
callFrom |
(character) allow easier tracking of message(s) produced |
numeric vector with mass
fragmentSeq("ABCDE") fragmentSeq("ABCDE", minSize=3, internFragments=FALSE) fragmentSeq("ABCDE", minSize=3, internFragments=TRUE) ## Run multiple peptides/proteins twoPep <- cbind(c("a","ABCABCA"), c("e","EFGEFGEF")) apply(twoPep, 2, function(x) fragmentSeq(x[2], mi=3, kee=FALSE, sep=TRUE, pre=x[1])) ## Ubiquitin example P0CG48 <- "MQIFVKTLTGKTITLEVEPSDTIENVKAKIQDKEGIPPDQQRLIFAGKQLEDGRTLSDYNIQKESTLHLVLRLRGG" system.time( fra1 <- (fragmentSeq(P0CG48, mi=5, kee=FALSE))) # < 0.5 secfragmentSeq("ABCDE") fragmentSeq("ABCDE", minSize=3, internFragments=FALSE) fragmentSeq("ABCDE", minSize=3, internFragments=TRUE) ## Run multiple peptides/proteins twoPep <- cbind(c("a","ABCABCA"), c("e","EFGEFGEF")) apply(twoPep, 2, function(x) fragmentSeq(x[2], mi=3, kee=FALSE, sep=TRUE, pre=x[1])) ## Ubiquitin example P0CG48 <- "MQIFVKTLTGKTITLEVEPSDTIENVKAKIQDKEGIPPDQQRLIFAGKQLEDGRTLSDYNIQKESTLHLVLRLRGG" system.time( fra1 <- (fragmentSeq(P0CG48, mi=5, kee=FALSE))) # < 0.5 sec
Identify peptide/protein fragment based on experimental m/z values 'expMass' for given range of aa-length.
Internally all possible fragments will be predicted and their mass compared to the experimental values (argument expMass).
identifFixedModif( prot, expMass, minFragSize = 5, maxFragSize = 60, indexStart = 1, suplPepTab = NULL, internFra = TRUE, filtChargeCatch = TRUE, maxMod = c(p = 3, h = 1, k = 1, o = 1, m = 1, n = 1, u = 1, r = 1, s = 1), modTy = NULL, specModif = NULL, knownMods = NULL, identMeas = "ppm", limitIdent = 5, filtAmbiguous = FALSE, recalibrate = FALSE, chargeCatchFilter = TRUE, massTy = "mono", prefFragPat = NULL, silent = FALSE, debug = FALSE, callFrom = NULL )identifFixedModif( prot, expMass, minFragSize = 5, maxFragSize = 60, indexStart = 1, suplPepTab = NULL, internFra = TRUE, filtChargeCatch = TRUE, maxMod = c(p = 3, h = 1, k = 1, o = 1, m = 1, n = 1, u = 1, r = 1, s = 1), modTy = NULL, specModif = NULL, knownMods = NULL, identMeas = "ppm", limitIdent = 5, filtAmbiguous = FALSE, recalibrate = FALSE, chargeCatchFilter = TRUE, massTy = "mono", prefFragPat = NULL, silent = FALSE, debug = FALSE, callFrom = NULL )
prot |
(character) amino-acid sequene of peptide or protein |
expMass |
(numeric) erperimental masses to identify peptides from |
minFragSize |
(integer) min number of AA residues for considering peptide fragments |
maxFragSize |
(integer) max number of AA residues for considering peptide fragments |
indexStart |
(integer) for starting at correct index (if not 1) |
suplPepTab |
(matrix) additional peptides to be add to theoretical peptides |
internFra |
(logical) decide whether internal fragments should be cosiered |
filtChargeCatch |
(logical) by default removing of all fragments not containing a (polar) charge-cathing residue |
maxMod |
(integer) maximum number of residue modifications to be consiered in fragments (values >1 will increase complexity and RAM consumption) |
modTy |
(character) type of fixed and variable modifications |
specModif |
(list) supplemental custom fixed or variable modifications (eg Zn++ at given residue) |
knownMods |
(character) optional custom alternative to |
identMeas |
(character) default 'ppm' |
limitIdent |
(character) thershold for identification in 'identMeas' units |
filtAmbiguous |
(logical) allows filtering/removing ambiguous results (ie same mass peptides) |
recalibrate |
(logical or numeric) may be direct recalibration-factor (numeric,length=1), if 'TRUE' fresh determination of 'recalibFact' or 'FALSE' (no action); final recalibration-factor used exported in result as $recalibFact |
chargeCatchFilter |
(logical) optionally remove all peptides not containing charge-catch AAs (K, R, H, defined via |
massTy |
(character) 'mono' or 'average' |
prefFragPat |
(numeric) pattern for preferential fragmentation (see also Haverland 2017), if |
silent |
(logical) suppress messages |
debug |
(logical) additional messages and objects exportet to current session for debugging |
callFrom |
(character) allow easier tracking of message(s) produced |
list, ie result of massMatch() on 'pepTab' and 'expMass'
protP <- c(protP="PEPTIDEKR") obsMassX <- cbind(a=c(199.1077,296.1605,397.2082,510.2922,625.3192), b=c(227.1026,324.1554,425.2031,538.2871,653.3141), x=c(729.2937,600.2511,503.1984,402.1507,289.0666), y=c(703.3145,574.2719,477.2191,376.1714,263.0874)) rownames(obsMassX) <- c("E","P","T","I","D") # all 1 & 7 ions not included identP1 <- identifFixedModif(prot=protP, expMass=as.numeric(obsMassX), minFragSize=2, maxFragSize=7,modTy=list(basMod=c("b","y"))) # looks ok identP2 <- identifFixedModif(prot=protP, expMass=as.numeric(obsMassX), minFragSize=2, maxFragSize=7, modTy=list(basMod=c("a","x"), varMod=c("h","o","r","m"))) head(identP1$preMa,n=17) # predicted masses incl fixed modif head(identP2$preMa,n=17) # predicted masses incl fixed modifprotP <- c(protP="PEPTIDEKR") obsMassX <- cbind(a=c(199.1077,296.1605,397.2082,510.2922,625.3192), b=c(227.1026,324.1554,425.2031,538.2871,653.3141), x=c(729.2937,600.2511,503.1984,402.1507,289.0666), y=c(703.3145,574.2719,477.2191,376.1714,263.0874)) rownames(obsMassX) <- c("E","P","T","I","D") # all 1 & 7 ions not included identP1 <- identifFixedModif(prot=protP, expMass=as.numeric(obsMassX), minFragSize=2, maxFragSize=7,modTy=list(basMod=c("b","y"))) # looks ok identP2 <- identifFixedModif(prot=protP, expMass=as.numeric(obsMassX), minFragSize=2, maxFragSize=7, modTy=list(basMod=c("a","x"), varMod=c("h","o","r","m"))) head(identP1$preMa,n=17) # predicted masses incl fixed modif head(identP2$preMa,n=17) # predicted masses incl fixed modif
Makes terminal and internal fragments based on protein-sequence and present as matrix including heading and/or tailing amino-acid or theoretical molecular mass of all fragments.
As the number of theoretically possible fragments increases with the size of the peptide/protein treated it is recommended to adopt arguments like masFragSize to
realizstic values for the type of mass spectrometer used, since efficient filtering will reduce considerably the amount of memory (RAM) needed and will improve overal performance.
makeFragments( protTab, minFragSize = 6, maxFragSize = 300, internFra = TRUE, knownMods = NULL, redRedundSeq = FALSE, prefFragPat = NULL, remNonConfPrefFragm = TRUE, ambigLab = c(duplSequence = "duplSequence", isoMass = "isoMass"), massTy = "mono", specModif = NULL, silent = FALSE, debug = FALSE, callFrom = NULL )makeFragments( protTab, minFragSize = 6, maxFragSize = 300, internFra = TRUE, knownMods = NULL, redRedundSeq = FALSE, prefFragPat = NULL, remNonConfPrefFragm = TRUE, ambigLab = c(duplSequence = "duplSequence", isoMass = "isoMass"), massTy = "mono", specModif = NULL, silent = FALSE, debug = FALSE, callFrom = NULL )
protTab |
(character or matrix) named vector of protein-seqences to fragment or matrix (character) with lines for initial proteins/peptides, cols as name/sequence/mass |
minFragSize |
(integer) minimum number of amino-acids for being considered |
maxFragSize |
(integer) maximum number of amino-acids for being considered |
internFra |
(logical) toggle if internal framents will be produced or not |
knownMods |
(character) optional custom alternative to |
redRedundSeq |
(logical) reduce redundant sequences to 1st appearance in all further treatments |
prefFragPat |
(matrix) for preferential fragmentation rules (see also |
remNonConfPrefFragm |
(logical) allows to remove (peptide-)fragments non conform with preferential fragmentation rules (using |
ambigLab |
(character) text-labels for ambiguities (first for duplicated sequences second for iso-mass) |
massTy |
(character) default 'mono' for mono-isotopic masses (alterative 'average') |
specModif |
(list) supplemental custom fixed or variable modifications (eg Zn++ at given residue) |
silent |
(logical) suppress messages |
debug |
(logical) for bug-tracking: more/enhanced messages |
callFrom |
(character) allow easier tracking of message(s) produced |
matrix with fragment sequence, mass, start- and end-position, heading and tailing AA (or NA if terminal fragment)
makeFragments; evalIsoFragm, from package wrProteo convAASeq2mass, AAmass, massDeFormula
protP <- c(protP="PEPTIDE") pepT1 <- makeFragments(protTab=protP, minFragSize=2, maxFragSize=9, internFra=TRUE) tail(pepT1)protP <- c(protP="PEPTIDE") pepT1 <- makeFragments(protTab=protP, minFragSize=2, maxFragSize=9, internFra=TRUE) tail(pepT1)
This simple function allows plotting the expected number of theoretical fragments from random fragmentation of peptides/proteins (in mass spectrometry). Here, only the pure fragmentation without any variable fragmentation is considered, all fragment-sizes are included (ie, no gating). For simplicity, possible (variable) modifications like loss of neutrals, etc, are not considered.
plotNTheor( x, tit = "Number of term and intern fragm", xlab = "Number of aa", ylab = "", col = 2:3, log = "", mark = NULL, cexMark = 0.75 )plotNTheor( x, tit = "Number of term and intern fragm", xlab = "Number of aa", ylab = "", col = 2:3, log = "", mark = NULL, cexMark = 0.75 )
x |
(integer) length (in amino-acids) of input peptides/proteins to be considered |
tit |
(character) custom title |
xlab |
(character) custom x-axis label |
ylab |
(character) custom y-axis label |
col |
(character or integer) cutsom colors |
log |
(character) define which axis should be log (use "xy" for drawing both x- and y-axis as log-scale) |
mark |
(matrix) first column for text and second column for where it should be stated along the top border of the figure (x-coordinate) |
cexMark |
(numeric) cex expansion-factor for text from argument |
figure only
marks <- data.frame(name=c("Ubiquitin\n76aa", "Glutamate dehydrogenase 1\n501aa"), length=c(76,501)) plotNTheor(x=20:750, log="", mark=marks)marks <- data.frame(name=c("Ubiquitin\n76aa", "Glutamate dehydrogenase 1\n501aa"), length=c(76,501)) plotNTheor(x=20:750, log="", mark=marks)
Make score based on cumulative search for AA with given potential to catch charge (H+, or optionally any charge). Note : at current cumulative scoring large peptides may get priviliged.
scoreChargeCatch( resTab, pepCol = "seq", scale01 = TRUE, chargeMode = "pos", silent = FALSE, callFrom = NULL )scoreChargeCatch( resTab, pepCol = "seq", scale01 = TRUE, chargeMode = "pos", silent = FALSE, callFrom = NULL )
resTab |
(matrix or data.frame) matrix or data.frame of results for SINGLE protein (here only the column specified with argument 'pepCol' will be used) |
pepCol |
(character) column name of 'resTab' containing the peptide sequence to be scored |
scale01 |
(logical) linear rescale output to maximum 1.0 |
chargeMode |
(character) this value may be 'pos' (default) for the positively charged amino-acids K,R and H or, if this argument has any other value, than all charged amino-acids (K,R,H, S,T,N,Q, D,E, W and Y) will be considered. |
silent |
(logical) suppress messages |
callFrom |
(character) allow easier tracking of message(s) produced |
numeric vector with score for each peptide of resTab (even if scale01=TRUE minimum may be >0 if all peptides do contain charge-catching AAs)
resTa <- matrix(c(1:4,"PEPTID","PEPTIK","PEPTRK","AGV"), ncol=2, dimnames=list(NULL,c("predInd","seq"))) scoreChargeCatch(resTa)resTa <- matrix(c(1:4,"PEPTID","PEPTIK","PEPTRK","AGV"), ncol=2, dimnames=list(NULL,c("predInd","seq"))) scoreChargeCatch(resTa)