| 1. |
- de Weerd, Hendrik A., et al.
(författare)
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MODifieR : an ensemble R package for inference of disease modules from transcriptomics networks
- 2020
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Ingår i: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811 .- 1460-2059. ; 36:12, s. 3918-3919
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Tidskriftsartikel (refereegranskat)abstract
- MOTIVATION: Complex diseases are due to the dense interactions of many disease-associated factors that dysregulate genes that in turn form so-called disease modules, which have shown to be a powerful concept for understanding pathological mechanisms. There exist many disease module inference methods that rely on somewhat different assumptions, but there is still no gold standard or best performing method. Hence, there is a need for combining these methods to generate robust disease modules.RESULTS: We developed MODule IdentiFIER (MODifieR), an ensemble R package of nine disease module inference methods from transcriptomics networks. MODifieR uses standardized input and output allowing the possibility to combine individual modules generated from these methods into more robust disease-specific modules, contributing to a better understanding of complex diseases.AVAILABILITY: MODifieR is available under the GNU GPL license and can be freely downloaded from https://gitlab.com/Gustafsson-lab/MODifieR and as a Docker image from https://hub.docker.com/r/ddeweerd/modifier.SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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| 2. |
- Lindlöf, Angelica, et al.
(författare)
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In silico analysis of promoter regions from cold-induced genes in rice (Oryza sativa L.) and Arabidopsis thaliana reveals the importance of combinatorial control
- 2009
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 25:11, s. 1345-1348
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Cold acclimation involves a number of different cellular processes that together increase the freezing tolerance of an organism. The DREB1/CBFs are transcription factors (TFs) that are prominent in the regulation of cold responses in Arabidopsis thaliana, rice and many other crops. We investigated if the expression of DREB1/CBFs and co-expressed genes relies on combinatorial control by several TFs. Our results support this notion and indicate that methods for studying the regulation of complex cellular processes should include identification of combinations of motifs, in addition to searching for individual overrepresented binding sites.
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| 3. |
- Weishaupt, Holger, et al.
(författare)
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Batch-normalization of cerebellar and medulloblastoma gene expression datasets utilizing empirically defined negative control genes
- 2019
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Ingår i: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811. ; 35:18, s. 3357-3364
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Medulloblastoma (MB) is a brain cancer predominantly arising in children. Roughly 70% of patients are cured today, but survivors often suffer from severe sequelae. MB has been extensively studied by molecular profiling, but often in small and scattered cohorts. To improve cure rates and reduce treatment side effects, accurate integration of such data to increase analytical power will be important, if not essential.Results: We have integrated 23 transcription datasets, spanning 1350 MB and 291 normal brain samples. To remove batch effects, we combined the Removal of Unwanted Variation (RUV) method with a novel pipeline for determining empirical negative control genes and a panel of metrics to evaluate normalization performance. The documented approach enabled the removal of a majority of batch effects, producing a large-scale, integrative dataset of MB and cerebellar expression data. The proposed strategy will be broadly applicable for accurate integration of data and incorporation of normal reference samples for studies of various diseases. We hope that the integrated dataset will improve current research in the field of MB by allowing more large-scale gene expression analyses.
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