Skip to main content

Messages

This section allows you to view all Messages made by this member. Note that you can only see Messages made in areas you currently have access to.

Messages - Ricardo

2
XCMS / Export signal to noise ratio for each peak
Hi,
when I run findPeaks.centWave for a single sample I have 

sample@xcmsSet@peaks[1,]
      mz    mzmin    mzmax      rt    rtmin    rtmax    into    intb
883.9883 883.9843 883.9926  3.4120  2.0610  4.7630 788.7590 786.0570
    maxo      sn  egauss      mu    sigma        h        f    dppm
321.0089 320.0000      NA      NA      NA      NA 136.0000  9.0000
  scale    scpos    scmin    scmax    lmin    lmax  sample
  4.0000  3.0000  1.0000  7.0000  1.0000  5.0000  1.0000


and I can access the signal to noise ratio (sn), but for multiple samples it is not present

psample@xcmsSet@peaks[1,]
          mz        mzmin        mzmax          rt        rtmin        rtmax
  83.057046    83.057007    83.057068    1.829970    0.333661    6.427780
        into        maxo      sample
22459.443811  4354.406250    1.000000


is there an average or a combined value that I can export?

thks
3
CAMERA / Help building adduct rule table
Hi,

in CAMERA vignette it is stated "As default CAMERA calculate its own table, which contains every
possible combination from the standard ions H, Na, K, NH4 and CL, depending
on your ionization mode." , can we have access to this list?

Additionally, my partner asked me to try to see -H2O, but the rule tables for positive mode in CAMERA's rule folder only have positive massdiff, I'm wondering if my calculations are unreasonable.

https://dl.dropbox.com/u/10712588/my_ru ... ts_pos.csv

I also had understood the quasi field as "which adducts we probably will see together"
and the ips field as "which adduct group we should assign higher score" m I right? If I don't know for sure the best is to leave all equal 1?

thanks in advance

Ricardo
5
CAMERA / Integrate Positive and Negative Modes
Hello,

I don't know if I missed in the viggnete or man pages, do CAMERA have a function to integrate negative and positive modes and export then in a single annotation table?
6
XCMS / Intensity values ??minimally reliable
Hi,

I've been processing UPLC/Q-TOF according with

http://www.nature.com/nprot/journal/v7/ ... 54_T1.html

and then with CAMERA standard workflow. I finish with proposed mass peaks that seem reasonable, for example, for plants they match kegg's secondary metabolism, Porphyrin and chlorophyll metabolism, and so on. But when I look to peak intensities they are very low, some less than 1000. If a peak pass all filters, matching all samples, in my case 30 samples, can I trust it can be a real peak or not?

Looking at this table http://mzmatch.sourceforge.net/metabolo ... isobar.tsv

from a serial dilution there are peak intensity as low as 4000, from filtered peaks, can it be a possibility that in my case I have a problem of concentration?

thanks in advance...
7
XCMS / Re: Choose the best parameters to analyse UPLC-qTof data
Hi Jan,

it seems you were right, checking the peaks through scans they look the same for .cdf and mxXML converted

https://dl.dropbox.com/u/10712588/conv.pdf

Here is my "workaround"

# download massWolf from http://tools.proteomecenter.org/wiki/in ... e_software
# you to have to have massLynx instaled
# chage the var loc for massWolf.exe in your system
# paste a copy of a folder containing .raw files inside "My documents"
# load or paste the script below in R environment
# run raw2mzxml()

# warnings: the script will erase your .raw files, so change it or have a backup
# for some people the lock mass is FUN003 http://metabolomics-forum.com/viewtopic.php?f=25&t=191
# in this case change FUNC.*2 for 3

raw2mzxml <- function() {
   setwd("~")
   old.dir <- getwd()
   t1 <- as.numeric(strsplit(strsplit(date(), " ")[[1]][4], ":")[[1]])
   loc <- "C:/Documents and Settings/ricardo/Meus documentos/Downloads/massWolf-4.3.1/massWolf.exe"
   vfiles <- list.dirs(dir(), full.names=TRUE)
   vfiles <- vfiles[grep(".*\.raw$", vfiles)]

   dirs <- unique(sub("(.*\/).*raw","\1", vfiles))
   root <- paste(strsplit(dirs[1], "/")[[1]][1],"/",sep="")
   dirs <- as.vector(sapply(dirs, function(x) paste(strsplit(x, "/")[[1]][-1],collapse="/")))
   #dirs <- path.expand(paste("~/", dirs, sep=""))
   vlog <- c()
   for(i in 1:length(dirs)) {
      setwd(path.expand(paste("~/", root, sep="")))
      setwd(dirs)
      vfiles <- list.dirs(dir())
      vfiles <- vfiles[grep(".*\.raw$", vfiles)]
      
      for(j in 1:length(vfiles)) {
         file.remove(path.expand(paste(getwd(),"/",vfiles,"/",dir(vfiles)[grep(".*FUNC.*2.*", dir(vfiles))], sep="")))
          log <- shell(paste(""", loc, """, " --mzXML ", vfiles[j],sep=""))
          vlog <- append(vlog, log)
          unlink(vfiles[j], recursive=TRUE)
      }
   }
   setwd(old.dir)
    t2 <- as.numeric(strsplit(strsplit(date(), " ")[[1]][4], ":")[[1]])
   cat(paste("n The program took:", paste(t2-t1, collapse=":"), "to convert", length(vlog), "files", "n"))
   
}
8
XCMS / Re: Choose the best parameters to analyse UPLC-qTof data
Hi Jan,

thanks again for your answer, I completely agree with you about the "sanity checks" before automated analysis, we will always find patterns if we search, even if they don't make sense.

The main problem with my group is that I'm the responsible for data analysis and, I'm not even in the same city of people running the experiment....

I've read this post http://metabolomics-forum.com/viewtopic.php?f=25&t=191

where someone says:
"...simply deleting the FUNC0003 DAT IDX and STS files might be a simple option for MassWolf conversion... "
deleting this files from .raw (in my case FUNC002, it seems that for me the FUNC0003 are from diode array)  turned to give the same visual result as the .CDF after the conversion. Do you ever read how the water write the raw data, is it correct, can I just erase this files?

the first is the .CDF, the second mzXML from full .raw, and the third from .raw without FUNC002 files
https://dl.dropbox.com/u/10712588/TICs-conversion.pdf
9
XCMS / Re: Choose the best parameters to analyse UPLC-qTof data
Hi  Jan,

thank you very much for your reply.

I usually only deal with the mass list, and even less with lock mass.

So, are you saying that I can't use the msconvert or massWolf corvesion with lock mass?

"You need to understand if you have a reasonable data quality before there is a point in using XCMS"

that is exactly my point, but I thought I could to this with xcms, I don't have experience with massLinx, is there an automated way to export peaks there for later inference? Can I set the conversion of all .raw files to CDF files in a batch?
 
Can I search for base peak intensity (BPI) through all samples in xcms?
10
XCMS / Choose the best parameters to analyse UPLC-qTof data
Hello every one,

I'm trying to analyse UPLC-qTof data from waters ultima. As my partners are experimenting new protocols I don't know what we are missing. First, the spectras look very different from http://metabolomics-forum.com/viewtopic ... 9174cddfb0

Can I infer something from this trend already?
https://dl.dropbox.com/u/10712588/TICs.pdf

I also had to correct the "mz sorting violation" from massWolf conversion, and don't know if it can interfere...

I'm trying to extract peaks with
method='centWave', snthresh=3, prefilter=c(3,100)

and using the default parameters in the fallowing steps. When I use the extracted peaks to annotation with camera I have only fell peaks with a very low intensity.

Are there manuals explaining each step with consistence checks, that is, more extensive than  xcmsPreprocess vignette?