Open Access Software

PyMS: a Python toolkit for processing of gas chromatography-mass spectrometry (GC-MS) data. Application and comparative study of selected tools

Sean O'Callaghan12, David P De Souza12, Andrew Isaac3, Qiao Wang4, Luke Hodkinson5, Moshe Olshansky6, Tim Erwin7, Bill Appelbe8, Dedreia L Tull12, Ute Roessner27, Antony Bacic129, Malcolm J McConville1102 and Vladimir A Likić12*

Author Affiliations

1 Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, 3010, Australia

2 Metabolomics Australia, Bio21 Institute, The University of Melbourne, Parkville, Victoria, 3010, Australia

3 Victorian Life Science Computational Initiative, The University of Melbourne, Parkville, Victoria, 3010, Australia

4 National ICT Australia (NICTA), The University of Melbourne, Parkville, Victoria, 3010, Australia

5 Centre for Astrophysics & Supercomputing, Swinburne University of Technology, Hawthorn, Victoria, 3122, Australia

6 Walter and Eliza Hall Institute of Medical Research, 1 G Royal Parade, Parkville, Victoria, 3052, Australia

7 Australian Centre for Plant and Functional Genomics, School of Botany, The University of Melbourne, Parkville, Victoria, 3010, Australia

8 Victorian Partnership for Advanced Computing, 110 Victoria Street, Carlton South, Victoria, 3053, Australia

9 ARC Centre of Excellence in Plant Cell Walls, School of Botany, The University of Melbourne, Parkville, Victoria, 3010, Australia

10 Department of Biochemistry and Molecular Biology, The University of Melbourne, Parkville, Victoria, 3010, Australia

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BMC Bioinformatics 2012, 13:115  doi:10.1186/1471-2105-13-115

Published: 30 May 2012

Additional files

Additional file 1:

Table of signals shown in Figure 3. The table lists signals shown in Figure 3. The tables lists signals present in the data as delineated by manual analysis and shown in Figure 3. For each signal (a) the retention time and five top m/z ions are given; (b) it was marked whether it was found by each of the programs (PyMS, AMDIS, AnalyzerPro, XCMS).

Format: PDF Size: 35KB Download file

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Open Data

Additional file 2:

Table of signals shown in Figure 4. The table lists signals shown in Figure 4. The tables lists signals present in the data as delineated by manual analysis and shown in Figure 4. For each signal (a) the retention time and five top m/z ions are given; (b) it was marked whether it was found by each of the programs (PyMS, AMDIS, AnalyzerPro, XCMS).

Format: PDF Size: 33KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional file 3:

Table of signals shown in Figure 5. The tables lists signals present in the data as delineated by manual analysis and shown in Figure 5. For each signal (a) the retention time and five top m/z ions are given; (b) it was marked whether it was found by each of the programs (PyMS, AMDIS, AnalyzerPro, XCMS).

Format: PDF Size: 32KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data

Additional file 4:

Table of signals shown in Figure 6. The table lists signals shown in Figure 6. The tables lists signals present in the data as delineated by manual analysis and shown in Figure 6. For each signal (a) the retention time and five top m/z ions are given; (b) it wasmarked whether it was found by each of the programs (PyMS, AMDIS, AnalyzerPro, XCMS).

Format: PDF Size: 31KB Download file

This file can be viewed with: Adobe Acrobat Reader

Open Data