A comparison of curated gene sets versus transcriptomics-derived gene signatures for detecting pathway activation in immune cells

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dc.identifier.uri http://dx.doi.org/10.15488/10629
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/10707
dc.contributor.author Liu, Bin
dc.contributor.author Lindner, Patrick
dc.contributor.author Jirmo, Adan Chari
dc.contributor.author Maus, Ulrich
dc.contributor.author Illig, Thomas
dc.contributor.author Deluca, David S.
dc.date.accessioned 2021-03-26T08:44:47Z
dc.date.available 2021-03-26T08:44:47Z
dc.date.issued 2020
dc.identifier.citation Liu, B.; Lindner, P.; Jirmo, A.C.; Maus, U.; Illig, T. et al.: A comparison of curated gene sets versus transcriptomics-derived gene signatures for detecting pathway activation in immune cells. In: BMC Bioinformatics 21 (2020), Nr. 1, 28. DOI: https://doi.org/10.1186/s12859-020-3366-4
dc.description.abstract Background: Despite the significant contribution of transcriptomics to the fields of biological and biomedical research, interpreting long lists of significantly differentially expressed genes remains a challenging step in the analysis process. Gene set enrichment analysis is a standard approach for summarizing differentially expressed genes into pathways or other gene groupings. Here, we explore an alternative approach to utilizing gene sets from curated databases. We examine the method of deriving custom gene sets which may be relevant to a given experiment using reference data sets from previous transcriptomics studies. We call these data-derived gene sets, "gene signatures" for the biological process tested in the previous study. We focus on the feasibility of this approach in analyzing immune-related processes, which are complicated in their nature but play an important role in the medical research. Results: We evaluate several statistical approaches to detecting the activity of a gene signature in a target data set. We compare the performance of the data-derived gene signature approach with comparable GO term gene sets across all of the statistical tests. A total of 61 differential expression comparisons generated from 26 transcriptome experiments were included in the analysis. These experiments covered eight immunological processes in eight types of leukocytes. The data-derived signatures were used to detect the presence of immunological processes in the test data with modest accuracy (AUC = 0.67). The performance for GO and literature based gene sets was worse (AUC = 0.59). Both approaches were plagued by poor specificity. Conclusions: When investigators seek to test specific hypotheses, the data-derived signature approach can perform as well, if not better than standard gene-set based approaches for immunological signatures. Furthermore, the data-derived signatures can be generated in the cases that well-defined gene sets are lacking from pathway databases and also offer the opportunity for defining signatures in a cell-type specific manner. However, neither the data-derived signatures nor standard gene-sets can be demonstrated to reliably provide negative predictions for negative cases. We conclude that the data-derived signature approach is a useful and sometimes necessary tool, but analysts should be weary of false positives. © 2020 The Author(s). eng
dc.language.iso eng
dc.publisher London : BioMed Central
dc.relation.ispartofseries BMC Bioinformatics 21 (2020), Nr. 1
dc.rights CC BY 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject gene set eng
dc.subject gene signature eng
dc.subject transcriptome eng
dc.subject.ddc 004 | Informatik ger
dc.subject.ddc 570 | Biowissenschaften, Biologie ger
dc.title A comparison of curated gene sets versus transcriptomics-derived gene signatures for detecting pathway activation in immune cells
dc.type Article
dc.type Text
dc.relation.essn 1471-2105
dc.relation.doi https://doi.org/10.1186/s12859-020-3366-4
dc.bibliographicCitation.issue 1
dc.bibliographicCitation.volume 21
dc.bibliographicCitation.firstPage 28
dc.description.version publishedVersion
tib.accessRights frei zug�nglich

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