Processing Duplicates

[RSSLGCGCUSER]

Hi, its been a while since i used the software & I am realizing how much I have forgotten. I am profiling a couple of alcoholic drinks. I ran them in duplicate. Initially I thought I would just detect the blobs, library search & export the blob table However what is apparent is that the duplicates contain blobs that whilst in both samples have different library matches. Looking at them they are the same it is just one of those things where one replicate gives a better match for compound X & one for compound Y. I am trying to think of the best workflow to process duplicates. Would it make more sense to build a composite template from the two injections & use the data from that as the definitive set? I probably need the dummies explanation to get me going again

[qtao]

Depending on your objectives, there are various ways to handle this

If the objective is to get the correct identification, you may add Hit 1 to 3 columns to Blob Table and compare them between two replicate runs.

If the objective is to get a consistent ID for non-targeted profiling, you may

1. process them through the Investigator program as shown here:
   https://www.gcimage.com/docs/quick-star ... emo-4.html
2. use Compound Finder to find common compounds:
   https://www.gcimage.com/docs/quick-star ... n-compound

[RSSLGCGCUSER]

Thank you,

The aim was to profile two gins and a vodka. I planned on providing semi-quantitative results against tentative ids. I was looking to ensure consistency in reporting the data. So making sure the same blobs in the duplicates had the same id.

How does the feature template deal with the different ids for the essentially the same blob in two different injections? Also is there a way to then pull out the areas rather than the percentage response etc? Basically so I can generate a semiquantitative set of results?

[qtao]

How does the feature template deal with the different ids for the essentially the same blob in two different injections?

The feature template is generated from the composite chromatogram. Feature areas are from peaks detected in that single composite chromatogram. The same peaks at the same RT space will be detected as one, as long as no significant chromatography difference between two replicate runs that could not be corrected by the built-in RT alignment. And its spectrum, used for library search, is equivalent to the average of the two runs.

Note that, if the runs from different samples, you will need Compound Finder to verify ID consistency.

Also is there a way to then pull out the areas rather than the percentage response etc?

You can configure the attributes loaded to include Volume. A simple way is to configure Blob Table when processing individual runs, and uncheck all Attributes options when loading images to Investigator. See here:
https://www.gcimage.com/gcxgc/usersguid ... Attributes