Hello,

If you are asking to use 'solely' for MS-based metabolomics applications. If so, then our review would be useful to pick up some open source tools and softwares in metabolomics, which is an update for 2014-2015: http://onlinelibrary.wiley.com/doi/10.1002/elps.201500417/pdf

And self-promotion apart my views with the above tools are as follows:

1. SIEVE + ChromAlign: Commercial- need to buy- I have used but did not find anything exceptional though (apart from access to spectral databases within the software suite).

2. MAVEN: open-source (free) but not very user friendly. Needs some time to twitch and tweak to make it work- esp. peak annotations etc. Easy installation, though.

3. XC-MS: Need experience with R/ Bioconductor basics, but user friendly only if you choose to use XCMS Online which is more user friendly but not customizable (limited). Good figures but need polishing before publishing.

4. Mass Frontier: Commercial, never used, word of mouth- expensive. Unsure of difficulties/ ease.

5. MetaboAnalyst: Most user friendly, web-server, no need to install press-button, free, but for statistical analysis and visualization mostly- unlike the tools above where pre-processing, alignment are not priorities.

6. MetAlign: Windows-based, but failed to install with my systems/ run properly (feeble memory!), did not find anything exceptional a far as description/ literature is concerned.

Recommendations other than above:

1. MZMine v. 2.0: Easy installation, free, awesome annotation, all sorts of alignment and preprocessing, little bit of statistics and visualization, but images are not publication quality. Need to have R pre-installed on the PC/MAC system.

2. Mass++: Easy installation, free, annotation only against MassBank, Japan (both EI- and ESI-MS searches possible), peak alignment, processing options good, visualization and images OK types.

3. Worth trying: Workflow4Metabolomics 2.0, HayStack, MetaboNexus, metaP-server. Please look at the "Holistic Tools" section in the Review paper above:http://onlinelibrary.wiley.com/doi/10.1002/elps.201500417/pdf where these tools start with Raw data files and end up with good enough statistical analysis, and visualizations; and mostly are press-button tools.

Baseline to keep in mind: (1) Not a single  tool does the all the job perfectly. Need many of these combinations to accomplish a complete metabolomics job. (2) Commercial tools like from Thermo Scientific/ Agilent are NOT holisitic and they have their own pitfalls and limitations- even their visualizations are NOT directly publication quality, limited in statistical prowess, expensive for sure, and so on. (3) Open source is free, easy to use, larger user and developer community, constantly evolving, need of the hour and for future, (4) R- / Bioconductor based packages are the best; avoid MATLAB based has commercial issues; others far more difficult (5) All above are poorly "aesthetic" in figure generation and all figures need further improvisations on Powerpoint, Adobe or InkScape for publication quality images, .

For ID annotations (by 'low abundance' is very subjective- depends on your own peak-picking, pre-processing, defining the AUC, signal/noise ratios, cut-offs for AUCs used, resolution of your system, defining baseline and a zillion such considerations.) MZMine (free, can integrate HMDB, PubChem, Metlin, ChemSpider, BioCyc, KEGG) into the software and do it simultaneously, XCMS can be useful ins searching the same DBs as above, meta-P does fine (free), or you can do one-by-one at mzCloud (free), at METLIN DB; however Progenesis from Water's integrates a lot of these DBs for annotations (commercial), Sciex's XCMSPlus (does similar integration of DBs) (these later two can be expensive!), while the third commercial tool for these annotations would be "Elements for Metabolomics" from ProteomeSoftware, though commercial would be cheapest.

Hope the above helps a bit.

Thanks,

Biswa

Note- All above are from my personal experience/ views, and am not endorsing/ rejecting any tools- others might have differing opinions too!

Abbreviations: DBs: Databases, MS: Mass-spectrometry, ID: identifications, R- R statistical package,

I think Thermo will discontinue Sieve... inquire before starting the learning process.

Thank you Biswa! Very informative. I appreciate the insight.