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Topic: How to convert NIST library (GCMS) into .msp format to use in MS-DIAL? (Read 171 times) previous topic - next topic

How to convert NIST library (GCMS) into .msp format to use in MS-DIAL?

How to convert NIST library (GCMS) into .msp format to use in MS-DIAL? Can the NIST library of GCMS used for compound identification for LCMS data?

Re: How to convert NIST library (GCMS) into .msp format to use in MS-DIAL?

Reply #1 –
Hi Kumar M,
Please take a look here. http://www.metabolomics-forum.com/index.php?topic=1439.msg4270#msg4270

Besides,
 GCMS library is not suitable for LCMS data as GCMS uses hard ionization while LCMS uses soft one and the fragments of a given substance in these two systems could vary a lot. For annotating LCMS data, Hiroshi's team has compiled publicly available libraries in both positive and negative modes. You can download libraries here http://prime.psc.riken.jp/compms/msdial/main.html#MSP.

Best,
Sukis

Re: How to convert NIST library (GCMS) into .msp format to use in MS-DIAL?

Reply #2 –
I would like to know what all are the libraries should I consider for GCMS analysis. I cannot procure commercial library so I would like to know what all list of libraries I can use for compiling into one .msp file. Below here there is a some information regarding the list and method of compiling the library. But I would like to know if we need more than this.

Biswapriya Misra 2019. Steps for Building an Open Source EI-MS Mass Spectral Library for GC-MS -based Metabolomics. protocols.io
https://dx.doi.org/10.17504/protocols.io.8txhwpn
Warm regards,
Sisu

Re: How to convert NIST library (GCMS) into .msp format to use in MS-DIAL?

Reply #3 –
In GC-MS, first, you should choose the msp library that contains retention index (RI) by the same column as you use.
The RI value should be reliable. (but hopefully, if you do TMS-derivative metabolite profiling, analyzing standards of sugar compounds like glucose and galactose is needed to validate the results because they have very similar RI/RT values.

Then, you may use the library like "All records with Kovats RI" that contains experimental/predicted RI values. Not all of RI values should be compatible with your experimental data, but the annotation using this wider coverage library will be helpful for your annotation pipeline.

Hiroshi