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Messages - dlforrister

1
metaXCMS / fill peaks, check raw data
I am using metaXCMS to generate a large peaktable with all features found from many different species of plants. I first processed these individual species using XCMS, RTCor,grouping etc. I then used metaXCMS generate the all species peaktable. I am concerned that this method will generate a lot of false negatives if a feature is not picked up by the original peak picking parameters. I'd like to use fillpeaks or getPeaks to fill out the all species peak table. Anyone done this or know of a way?
2
XCMS / Re: Choose the best parameters to analyse UPLC-qTof data
Thanks for the quick response. I was able to get the convert.waters() to run, but I keep getting an error with convert.waters2()

masswolf.exe is in the working directory. I want to remove the lockscans so I chose funcs= c(1,2) is that correct? what are each of those func (func001, func002 and func003)?

here is what I used:

convert.waters2(infiles ="K:/XCMS_ANALYSIS/mzxml",outdir = "K:/XCMS_ANALYSIS/mzxml/converted",funcs = c(1,2))

I get the errors:

1) "In file.symlink(from = paste0(infiles, "/", to_copy),  ... :
  cannot symlink 'K:XCMS_ANALYSISmzxmlconverted' to 'K:/XCMS_ANALYSIS/mzxml/converted/temp.raw/converted', reason 'A required privilege is not held by the client'
2) running command 'masswolf --mzXML "K:/XCMS_ANALYSIS/mzxml/converted/temp.raw" "K:/XCMS_ANALYSIS/mzxml/converted/mzxml_func1.mzXML"' had status 65535


Thanks,

Dale
3
CAMERA / Re: annotation of doubly charged metabolites
I have a similar question regarding annotation of doubly charged metabolites. Below I have an example of two pcgroup's where camera has identified them as [M]2- due to the fact that there is a 0.5 da mass difference between features.

[attachment=2:2tij0bq6]peaktable.PNG[/attachment:2tij0bq6]

In both cases I believe this is incorrect because when I look at the actual raw data each peak is actually 1.0 da apart
[attachment=1:2tij0bq6]806_isotope.PNG[/attachment:2tij0bq6]

Based on some of the comments above I'm guessing, this is likely due to a grouping and over splitting features based on grouping parameters  that are too strict? We used ( xset3 <-group(xset2, method="density",bw=5, mzwid=0.05, minfrac=0.1))
which parameter is causing this over splitting? bw of 5 or mzwid=0.05?

Similarly,  in the above peak table pcgroup 4 also has a similar issue where features are separated by 0.5 da intervals, however, the raw data does not show this.

[attachment=0:2tij0bq6]1384_isotope.PNG[/attachment:2tij0bq6]
 
This case seems a bit different becuase the mass differences aren't exactly 1.0 da (see below). Why would these masses not be exactly 1.0? My initial thought is that it is due to the fact that these features are from a cluster [3M-2H]2- but I'm not exactly sure how that would change the mzdif. can someone explain this?

mass diff of [mz]2- to [mz+1]2- = 0.7318
mass diff of [mz+1]2- to [mz+2]2- = 0.9445
mass diff of [mz+2]2- to [mz+3]2- = 0.9631


Thanks in advance any guidance or advice!

[attachment deleted by admin]
4
XCMS / Re: Choose the best parameters to analyse UPLC-qTof data
Quote from: "Jan Stanstrup"
I added a function, convert.waters2, to my package (https://github.com/stanstrup/chemhelper) based on this idea of deleting the functions (in waters lingo) that should not go into the output file. You can select which functions to keep and a separate file for each will be written.

Hi Jan,

I am attempting to use the convert.waters2 function you have posted on git hub but the supplemental material you refer to here (http://https://github.com/stanstrup/convert.waters.raw) gives a 404 error. Can you re post those or provide more information on how to set up the conversion, i.e. "MassLynx need to be installed and masswolf need to be in path." what path do you refer to? Also, where to raw files need to be?

Thank you,

Dale Forrister
5
CAMERA / Re: Error in x$membership
Thank you. The solution at the very bottom of that thread worked. I hadn't seen that before.

Cheers
DF
6
CAMERA / Error in x$membership
Hi all,

I am trying to annotate my peak list using Camera. I get the following error on the first step:

> xsa <- xsAnnotate(xs=xset4,polarity="negative")
Error in x$membership : $ operator not defined for this S4 class


This error occurs on both R 3.1.3 and R 3.1.2

Some googling indicated that the issue is probably due to the using a newer version of R and of igraph 1.0.1. I've tried rolling back to previous versions of both R but have had issues.

Any suggestions?

Thank you,

DF
7
XCMS / Re: retention time correction for individual sample classes
Yes, this is a very severe batch effect! We have many samples so the overall run time for all samples has been months, which we understand is way less than ideal BUT is necessary for our project. To give a little perspective, if we were to re-run all samples having the machine run 24 hrs a day it would still take a minimum of 30 days...

 Based on the internal standard the mean shift is 0.1 mins. However, about 10% of our samples have shifted by 0.8 - 1.4 mins.

1) We could use our RT standard to do a rough initial shift for all peaks. My big fear of doing this that shifts in chromatography across a gradient tends to be nonlinear.

 You are recommending using default retcor(), Is this because as stated above no single sample will represent all samples because each sample class has a different set of metabolites? Does the default retcor have a minimum number of "well behaved peaks"? and will it fail if there are two few overlapping compounds between less similar sample classes.

2) Reading the forum it seems it is possible to merge and split samples after xcmsSET(), but when merging and splitting RT correction information is lost. Why is this? IS there a hack which would allow this information to be stored?

3) Given the consistency of the majority of our samples, we could potentially re-run all samples with a RT shift > an acceptable threshold. Is there a RT shift threshold where xcms effectively ignores small shifts (i.e based on our peak width of c(5,12) 0.2 mins, wouldn't shifts less than 0.2 mins still fall into the same peak width)?
8
XCMS / retention time correction for individual sample classes
We are working with xcms to analyze plant secondary metabolites for different species of closely related plants using a waters G2QTOF UPLC-MS.

We have a question regarding correcting for retention time shifts across many samples with a limited number of shared features. It is possible individual sample classes will share only a single internal standard.

Each species makes up a sample class with 5 individuals as replicates per class. However, given the total number of samples, data acquisition has occurred over time and some RT shifts have been observed on the order of (+/- 1.0 min)

Our understanding of the retcor-loess and Obiwarp methods indicates we will have issues aligning all sample classes because there are not enough shared features. Similarly, obiwarp chooses a single sample to align the rest with such a diverse set of samples the chosen sample will not be representative of all other samples. 

Does retcor() work by aligning samples within a sample class first then aligning across samples classes?

Is it possible to apply RT correction to each sample class individually then merge or save these corrected xcmsSET objects for a general analysis of all samples?

Thank you for your help!
9
XCMS / saving xcmsSET object to CDF or mzXML files
Is it possible to save rt corrected xcmsSET objects to CDF or mzXML files without discarding rt correction data?

We aim to compare many sample classes, with different metabolites in each class. Thus, few features are shared across classes and therefore retention time correction methods (i.e obiwarp) might not be effective. In fact the only feature shared across all samples is a single internal standard we used to check RT shifts.

Is it possible to apply rt correction to each sample class individually then save and or merge xcmsSet objects in order to perform a final general comparison between classes?


Thank you all,

DF