Overview

When you publish manuscripts based on data generated at our facility, we would greatly appreciate an acknowledgement of our efforts. Please cite our facility as follows (for example):

Basic processing of the raw data were performed by the University of Illinois at Chicago Research Informatics Core (UICRIC).

We adhere to a general policy for acknowledgements and authorship as established by the Association for Biomolecular Resource Facilities (ABRF) , and we support the following statement from the ABRF.

The existence of core facilities depends in part on proper acknowledgment in publications. This is an important metric of the value of most core facilities. Proper acknowledgment of core facilities enables them to obtain financial and other support so that they may continue to provide their essential services in the best ways possible. It also helps core personnel to advance in their careers, adding to the overall health of the core facility.

Please contact us for assistance in drafting manuscripts.

Sample list
Sample OriginalID
1_RP_001 1_RP_001
1_RP_002 1_RP_002
1_RP_003 1_RP_003
1_RP_004 1_RP_004
1_RP_011 1_RP_011
1_RP_012 1_RP_012
1_RP_013 1_RP_013
1_RP_014 1_RP_014

  • Filtering of LC-MS data

Method: OpenMS FileFilterRost, H.L., Sachsenberg, T., Aiche, S., Bielow, C., Weisser, H., Aicheler, F., Andreotti, S., Ehrlich, H.-C., Gutenbrunner, P., Kenar, E., Liang, X., Nahnsen, S., Nilse, L., Pfeuffer, J., Rosenberger, G., Rurik, M., Schmitt, U., Veit, J., Walzer, M., Wojnar, D., Wolski, W.E., Schilling, O., Choudhary, J.S., Malmstrom, L., Aebersold, R., Reinert, K., Kohlbacher, O. (2016) OpenMS: A flexible open-source software platform for mass spectrometry data analysis. Nat. Methods 13. doi:10.1038/nmeth.3959

LC-MS data were filtered to remove data outside specified retention time and/or m/z window.

Custom Parameters
  • -rt = 46:1020

  • Detect LC-MS features

Method: OpenMS FeatureFinderMetaboRost, H.L., Sachsenberg, T., Aiche, S., Bielow, C., Weisser, H., Aicheler, F., Andreotti, S., Ehrlich, H.-C., Gutenbrunner, P., Kenar, E., Liang, X., Nahnsen, S., Nilse, L., Pfeuffer, J., Rosenberger, G., Rurik, M., Schmitt, U., Veit, J., Walzer, M., Wojnar, D., Wolski, W.E., Schilling, O., Choudhary, J.S., Malmstrom, L., Aebersold, R., Reinert, K., Kohlbacher, O. (2016) OpenMS: A flexible open-source software platform for mass spectrometry data analysis. Nat. Methods 13. doi:10.1038/nmeth.3959

Metabolite features were detected using singleton mass traces.

Custom Parameters
  • -ini = /mmfs1/projects/rrc_shared/common/references/openms-inifiles/uplc_qtof.ini

  • Align LC-MS features

Method: OpenMS MapAligngerPoseClusteringRost, H.L., Sachsenberg, T., Aiche, S., Bielow, C., Weisser, H., Aicheler, F., Andreotti, S., Ehrlich, H.-C., Gutenbrunner, P., Kenar, E., Liang, X., Nahnsen, S., Nilse, L., Pfeuffer, J., Rosenberger, G., Rurik, M., Schmitt, U., Veit, J., Walzer, M., Wojnar, D., Wolski, W.E., Schilling, O., Choudhary, J.S., Malmstrom, L., Aebersold, R., Reinert, K., Kohlbacher, O. (2016) OpenMS: A flexible open-source software platform for mass spectrometry data analysis. Nat. Methods 13. doi:10.1038/nmeth.3959

Features were aligned among the different samples using a POSE clustering approach.

Custom Parameters
  • mz_diff = 20 ppm
  • rt_diff = 30

Method: OpenMS FeatureLinkerUnlabeledQTRost, H.L., Sachsenberg, T., Aiche, S., Bielow, C., Weisser, H., Aicheler, F., Andreotti, S., Ehrlich, H.-C., Gutenbrunner, P., Kenar, E., Liang, X., Nahnsen, S., Nilse, L., Pfeuffer, J., Rosenberger, G., Rurik, M., Schmitt, U., Veit, J., Walzer, M., Wojnar, D., Wolski, W.E., Schilling, O., Choudhary, J.S., Malmstrom, L., Aebersold, R., Reinert, K., Kohlbacher, O. (2016) OpenMS: A flexible open-source software platform for mass spectrometry data analysis. Nat. Methods 13. doi:10.1038/nmeth.3959

Groups corresponding features from multiple, aligned samples using a QT clustering approach.

Custom Parameters
  • mz_diff = 20 ppm
  • rt_diff = 30

Figure 1 . Feature counts per sample

Figure 2 . Density of features (number of samples and number of shared features)

Figure 3 . Cumulative count of features by number of samples

Table 1 . Feature counts per sample

Table 1 . Feature counts per sample
Sample Total features Unique features
1_RP_001 6803 1698
1_RP_002 5782 1256
1_RP_003 4467 296
1_RP_004 3969 243
1_RP_011 4359 317
1_RP_012 4321 308
1_RP_013 4333 651
1_RP_014 4342 379

Table 2 . Density of features (number of samples and number of shared features)

Table 2 . Density of features (number of samples and number of shared features)
Sample count Feature count
8 1652
7 582
6 590
5 625
4 788
3 979
2 1592
1 5148

  • Annotate detected features

Method: OpenMS AccurateMassSearchRost, H.L., Sachsenberg, T., Aiche, S., Bielow, C., Weisser, H., Aicheler, F., Andreotti, S., Ehrlich, H.-C., Gutenbrunner, P., Kenar, E., Liang, X., Nahnsen, S., Nilse, L., Pfeuffer, J., Rosenberger, G., Rurik, M., Schmitt, U., Veit, J., Walzer, M., Wojnar, D., Wolski, W.E., Schilling, O., Choudhary, J.S., Malmstrom, L., Aebersold, R., Reinert, K., Kohlbacher, O. (2016) OpenMS: A flexible open-source software platform for mass spectrometry data analysis. Nat. Methods 13. doi:10.1038/nmeth.3959

Features were annotated using searches for exact mass matches from a spectrum against a database

Custom Parameters
  • -algorithm:mass_error_value = 5
  • -algorithm:mass_error_unit = ppm
  • -algorithm:keep_unidentified_masses = true
  • -algorithm:isotopic_similarity = true
  • -algorithm:ionization_mode = positive
  • adducts =

Citations