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Messages - ab123

1
Other / Feature intensity drift correction suggestions
I've got around 100 samples that suffer from feature intensity drift. Even the first five QCs (so in a matter of 30 injections) show drift in feature intensity sequentially (so from QC1 to QC5 there's drift visible in the PCA).

Apart from intCor, which didn't really help, does anyone have any good suggestions on how to correct this please?

Appreciate any help at this point.

Thank you.
2
XCMS / Re: Spectra versus XCMS/Camera
Thank you.
The problem I find most often with peak picking is that it picks random low intensity peaks within a certain retention time. And the other issue I seem to find are separated mzs, where you get essentially the same or very similar mz for the same RT.
3
Compound identification / Re: Fragmentation at 4.9 mz
Hi Jan,
Yes, I did think NH4 to Na made sense, but it would occur at least three times in a row.

The 26 difference is 26.0225, also at least 3 times in a row...

And why would it all be shifted by 5 mz between MS1 and MS2?
4
Compound identification / Fragmentation at 4.9 mz
Dear Forum members,

My MS1 files are showing multiple fragments at 26 mz apart with a strong base peak in between them. The more fragmented MS2 (I mean MSe here since this isn't MSMS) files are then showing the same peaks shifted by 4.9 mz each backwards.

Any idea what this may be?

5
XCMS / Re: Spectra versus XCMS/Camera
HI Jan,
Thank you!
Yes, I mean mz values. So the peaktable mz has a better accuracy than the peak mz shown in an actual spectrum at the same retention time?
6
XCMS / Spectra versus XCMS/Camera
Hello,

I just wanted to double check the following approach is not incorrect. I may be overthinking, but better safe than sorry.

For metabolite identification, I am searching for the feature xcms spat out, but I predominantly search the peaks that turn up in my spectra. Occasionally, these may not perfectly match either Camera or Xcms features.
I guess the question is: what's deemed more reliable - the xcms feature detection or the spectrum in identifying molec ions for compound identification?

Many thanks!
9
Compound identification / Mzmed - mz of fragment or compound?
Hello everyone,

I'm a tad confused as to the mz XCMS spits out after pre-processing.

Are these definitely compound masses or could they be fragments (not adducts) of a compound?
I'm asking because that obviously makes a huge difference for identification and I find that my spectra for select retention times don't match the mass, i.e. they often contain base peaks that may be higher than the mzmed given by XCMS.

So are the mzmed values both compounds and fragments thereof and if it's the latter how would you account for that (if it's not an adduct)?

Many thanks!
10
XCMS - FAQ / Outliers
Quick question: if I get an outlier sample, should I rerun all preprocessing steps in xcms (ie. group, retcor etc.)?

I'm using retcor with orbitrap and profstep=0.1 so the process is currently using the outlier sample as a center sample...suffice to say I'm wondering if that means retention time correction has to be repeated?

Thanks!
12
XCMS / Re: File conversion for XCMS
Thank you!

Sorry, but is there an alternative to MassLynx. It just keeps hanging too much...
13
XCMS / Re: File conversion for XCMS
Thank you Jan!

I'm completely new to MS, having done genomics before so getting going is a bit of a learning curve right now.

Just checked the TIC on a few of the RAW files, the three functions are all the same? TOF MS (50:1200) ES+

To the last part, yes, using
> list.files()
> xset <- xcmsset()

The files I am looking at are around 1GB each (that times 3 for each Raw file, but as you say I should only use 1 of the 3). If I only used 1 of the 3 that would bring down the total to around  40GB
14
XCMS / Re: File conversion for XCMS
Hi Jan,

Firstly, thanks for the reply.

I've been given the data so don't have much information on the experiment on hand.

My problem is that when I use Databridge to convert the raw file, it spits out 3 CDF files.
I have around 100 raw files. If I then try to load the newly converted CDFs into R using XCMS, the R or probably more likely the computer cannot (understandably) handle the huge size of these files.

Uploading to CDF is just as cumbersome as it takes forever.

Is there another way to convert these and make them smaller for use with XCMS in R or online.

Cheers!
15
XCMS / File conversion for XCMS
Hi guys,

I'm sure this is a fairly simple problem, but being new to XCMS it's a tad of a mystery to me.
I've been converting raw data into CDF files using Databridge.
The data transformation using DataBridge creates 3 different CDF files from a single original raw data set. Should that be the case?

If I load these in R they really clog up the system...they are huge. Do I need all three of them?

Cheers and much appreciated!