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1. Orchestrating high-throughput genomic analysis with Bioconductor.

Author

Huber, Wolfgang, Carey, Vincent, Gentleman, Robert, Anders, Simon, Carlson, Marc, Carvalho, Benilton, Bravo, Hector, Davis, Sean, Gatto, Laurent, Girke, Thomas, Gottardo, Raphael, Hahne, Florian, Hansen, Kasper, Irizarry, Rafael, Lawrence, Michael, Love, Michael, MacDonald, James, Obenchain, Valerie, Oleś, Andrzej, Pagès, Hervé, Reyes, Alejandro, Shannon, Paul, Smyth, Gordon, Tenenbaum, Dan, Waldron, Levi, and Morgan, Martin

Subjects
Computational Biology, Gene Expression Profiling, Genomics, High-Throughput Screening Assays, Programming Languages, Software, User-Computer Interface
Abstract

Bioconductor is an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology. The project aims to enable interdisciplinary research, collaboration and rapid development of scientific software. Based on the statistical programming language R, Bioconductor comprises 934 interoperable packages contributed by a large, diverse community of scientists. Packages cover a range of bioinformatic and statistical applications. They undergo formal initial review and continuous automated testing. We present an overview for prospective users and contributors.

Published
2015

3. Two Color Arrays

Author

Hahne, Florian, Huber, Wolfgang, Gentleman, Robert, editor, Hornik, Kurt, editor, Parmigiani, Giovanni, editor, Hahne, Florian, Huber, Wolfgang, and Falcon, Seth

Published
2008
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4. Solutions to Exercises

Author

Hahne, Florian, Huber, Wolfgang, Gentleman, Robert, Falcon, Seth, Gentleman, Robert, editor, Hornik, Kurt, editor, Parmigiani, Giovanni, editor, Hahne, Florian, Huber, Wolfgang, and Falcon, Seth

Published
2008
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5. Supplementary Table S1 Legend from Functional Profiling: From Microarrays via Cell-Based Assays to Novel Tumor Relevant Modulators of the Cell Cycle

Author

Arlt, Dorit, primary, Huber, Wolfgang, primary, Liebel, Urban, primary, Schmidt, Christian, primary, Majety, Meher, primary, Sauermann, Mamatha, primary, Rosenfelder, Heiko, primary, Bechtel, Stephanie, primary, Mehrle, Alexander, primary, Bannasch, Detlev, primary, Schupp, Ingo, primary, Seiler, Markus, primary, Simpson, Jeremy C., primary, Hahne, Florian, primary, Moosmayer, Petra, primary, Ruschhaupt, Markus, primary, Guilleaume, Birgit, primary, Wellenreuther, Ruth, primary, Pepperkok, Rainer, primary, Sültmann, Holger, primary, Poustka, Annemarie, primary, and Wiemann, Stefan, primary

Published
2023
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6. Supplementary Figure S1B from Functional Profiling: From Microarrays via Cell-Based Assays to Novel Tumor Relevant Modulators of the Cell Cycle

Author

Arlt, Dorit, primary, Huber, Wolfgang, primary, Liebel, Urban, primary, Schmidt, Christian, primary, Majety, Meher, primary, Sauermann, Mamatha, primary, Rosenfelder, Heiko, primary, Bechtel, Stephanie, primary, Mehrle, Alexander, primary, Bannasch, Detlev, primary, Schupp, Ingo, primary, Seiler, Markus, primary, Simpson, Jeremy C., primary, Hahne, Florian, primary, Moosmayer, Petra, primary, Ruschhaupt, Markus, primary, Guilleaume, Birgit, primary, Wellenreuther, Ruth, primary, Pepperkok, Rainer, primary, Sültmann, Holger, primary, Poustka, Annemarie, primary, and Wiemann, Stefan, primary

Published
2023
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7. Supplementary Figure S1A-2 from Functional Profiling: From Microarrays via Cell-Based Assays to Novel Tumor Relevant Modulators of the Cell Cycle

Author

Arlt, Dorit, primary, Huber, Wolfgang, primary, Liebel, Urban, primary, Schmidt, Christian, primary, Majety, Meher, primary, Sauermann, Mamatha, primary, Rosenfelder, Heiko, primary, Bechtel, Stephanie, primary, Mehrle, Alexander, primary, Bannasch, Detlev, primary, Schupp, Ingo, primary, Seiler, Markus, primary, Simpson, Jeremy C., primary, Hahne, Florian, primary, Moosmayer, Petra, primary, Ruschhaupt, Markus, primary, Guilleaume, Birgit, primary, Wellenreuther, Ruth, primary, Pepperkok, Rainer, primary, Sültmann, Holger, primary, Poustka, Annemarie, primary, and Wiemann, Stefan, primary

Published
2023
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8. Supplementary Methods and Materials from Functional Profiling: From Microarrays via Cell-Based Assays to Novel Tumor Relevant Modulators of the Cell Cycle

Author

Arlt, Dorit, primary, Huber, Wolfgang, primary, Liebel, Urban, primary, Schmidt, Christian, primary, Majety, Meher, primary, Sauermann, Mamatha, primary, Rosenfelder, Heiko, primary, Bechtel, Stephanie, primary, Mehrle, Alexander, primary, Bannasch, Detlev, primary, Schupp, Ingo, primary, Seiler, Markus, primary, Simpson, Jeremy C., primary, Hahne, Florian, primary, Moosmayer, Petra, primary, Ruschhaupt, Markus, primary, Guilleaume, Birgit, primary, Wellenreuther, Ruth, primary, Pepperkok, Rainer, primary, Sültmann, Holger, primary, Poustka, Annemarie, primary, and Wiemann, Stefan, primary

Published
2023
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9. Data from Functional Profiling: From Microarrays via Cell-Based Assays to Novel Tumor Relevant Modulators of the Cell Cycle

Author

Arlt, Dorit, primary, Huber, Wolfgang, primary, Liebel, Urban, primary, Schmidt, Christian, primary, Majety, Meher, primary, Sauermann, Mamatha, primary, Rosenfelder, Heiko, primary, Bechtel, Stephanie, primary, Mehrle, Alexander, primary, Bannasch, Detlev, primary, Schupp, Ingo, primary, Seiler, Markus, primary, Simpson, Jeremy C., primary, Hahne, Florian, primary, Moosmayer, Petra, primary, Ruschhaupt, Markus, primary, Guilleaume, Birgit, primary, Wellenreuther, Ruth, primary, Pepperkok, Rainer, primary, Sültmann, Holger, primary, Poustka, Annemarie, primary, and Wiemann, Stefan, primary

Published
2023
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10. Supplementary Figures S1-S3 Legends from Functional Profiling: From Microarrays via Cell-Based Assays to Novel Tumor Relevant Modulators of the Cell Cycle

Author

Arlt, Dorit, primary, Huber, Wolfgang, primary, Liebel, Urban, primary, Schmidt, Christian, primary, Majety, Meher, primary, Sauermann, Mamatha, primary, Rosenfelder, Heiko, primary, Bechtel, Stephanie, primary, Mehrle, Alexander, primary, Bannasch, Detlev, primary, Schupp, Ingo, primary, Seiler, Markus, primary, Simpson, Jeremy C., primary, Hahne, Florian, primary, Moosmayer, Petra, primary, Ruschhaupt, Markus, primary, Guilleaume, Birgit, primary, Wellenreuther, Ruth, primary, Pepperkok, Rainer, primary, Sültmann, Holger, primary, Poustka, Annemarie, primary, and Wiemann, Stefan, primary

Published
2023
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11. Supplementary Table S1 from Functional Profiling: From Microarrays via Cell-Based Assays to Novel Tumor Relevant Modulators of the Cell Cycle

Author

Arlt, Dorit, primary, Huber, Wolfgang, primary, Liebel, Urban, primary, Schmidt, Christian, primary, Majety, Meher, primary, Sauermann, Mamatha, primary, Rosenfelder, Heiko, primary, Bechtel, Stephanie, primary, Mehrle, Alexander, primary, Bannasch, Detlev, primary, Schupp, Ingo, primary, Seiler, Markus, primary, Simpson, Jeremy C., primary, Hahne, Florian, primary, Moosmayer, Petra, primary, Ruschhaupt, Markus, primary, Guilleaume, Birgit, primary, Wellenreuther, Ruth, primary, Pepperkok, Rainer, primary, Sültmann, Holger, primary, Poustka, Annemarie, primary, and Wiemann, Stefan, primary

Published
2023
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12. Does the amount of testing moderate the forward testing effect via subjective difficulty?

Author

Hausman, Hannah, Hahne, Florian, Rhodes, Matthew, and Kubik, Veit

Subjects
FOS: Psychology, Cognitive Psychology, Psychology, Social and Behavioral Sciences
Abstract

A replication of test difficulty with slightly different materials. The goal was to reduce the role of guessing from semantic memory on the interim tests and to measure subjective difficulty during the List 1 and List 2 review activities.

Published
2022
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14. Forward Testing Effect

Author

Hausman, Hannah, Kubik, Veit, and Hahne, Florian

Subjects
ComputingMilieux_GENERAL, FOS: Psychology, Data_FILES, Cognitive Psychology, Psychology, testing effect, forward effect of testing, self-regulated learning, cued recall, foreign language learning, Social and Behavioral Sciences
Abstract

Interim Test Difficulty

Published
2022
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15. Does test difficulty moderate the forward testing effect? An attempted conceptual replication

Author

Hausman, Hannah, Rhodes, Matthew, Hahne, Florian, and Kubik, Veit

Subjects
ComputingMilieux_GENERAL, FOS: Psychology, Data_MISCELLANEOUS, Data_FILES, Cognitive Psychology, Psychology, Social and Behavioral Sciences
Abstract

A replication of test difficulty with different materials. The goal was to reduce the role of guessing from semantic memory on the interim tests.

Published
2022
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16. Multitasking in Complex Environments: An Attempt to Generalize Individual Differences in Multitasking to a Realistic Task Setting

Author

Schindler, Hanna, Bista, Jayanti, Graffe, Philipp, Ivanova, Maria, Hahne, Florian, Kubik, Veit, Brüning, Jovita, and Rieger, Tobias

Abstract

Multitasking is a common feature of many modern work and home environments, and this study investigated the relationship between multitasking performance in two different paradigms: a more controlled task-switching paradigm (TSWP) and a more complex, semi-ecologically valid multitasking paradigm (SynWin). The study also explored whether parallel processors may have performance advantages in a complex dual-task environment. Results showed no significant correlation between individual multitasking efficiency in the TSWP and SynWin paradigms. Additionally, the results indicated that the combination of subtasks was the primary factor affecting performance in dual-task variants of the SynWin, rather than the use of a parallel processing mode. We conclude that there may be constraints with respect to the experimental conditions necessary to generalize findings from controlled multitasking paradigms to semi-ecologically valid tasks scenarios. Future research should prioritize efforts to understand how people multitask in more realistic settings and the underlying cognitive processes involved.

Published
2023
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19. Identification of Dlk1-Dio3 Imprinted Gene Cluster Noncoding RNAs as Novel Candidate Biomarkers for Liver Tumor Promotion

Author

Lempiäinen, Harri, Couttet, Philippe, Bolognani, Federico, Müller, Arne, Dubost, Valérie, Luisier, Raphaëlle, Del Rio Espinola, Alberto, Vitry, Veronique, Unterberger, Elif B., Thomson, John P., Treindl, Fridolin, Metzger, Ute, Wrzodek, Clemens, Hahne, Florian, Zollinger, Tulipan, Brasa, Sarah, Kalteis, Magdalena, Marcellin, Magali, Giudicelli, Fanny, Braeuning, Albert, Morawiec, Laurent, Zamurovic, Natasa, Längle, Ulrich, Scheer, Nico, Schübeler, Dirk, Goodman, Jay, Chibout, Salah-Dine, Marlowe, Jennifer, Theil, Diethilde, Heard, David J., Grenet, Olivier, Zell, Andreas, Templin, Markus F., Meehan, Richard R., Wolf, Roland C., Elcombe, Clifford R., Schwarz, Michael, Moulin, Pierre, Terranova, Rémi, and Moggs, Jonathan G.

Published
2013
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21. The LIFEdb database in 2006

Author

Mehrle, Alexander, Rosenfelder, Heiko, Schupp, Ingo, del Val, Coral, Arlt, Dorit, Hahne, Florian, Bechtel, Stephanie, Simpson, Jeremy, Hofmann, Oliver, Hide, Winston, Glatting, Karl-Heinz, Huber, Wolfgang, Pepperkok, Rainer, Poustka, Annemarie, and Wiemann, Stefan

Published
2006

22. flowClust: a Bioconductor package for automated gating of flow cytometry data

Author

Lo Kenneth, Hahne Florian, Brinkman Ryan R, and Gottardo Raphael

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background As a high-throughput technology that offers rapid quantification of multidimensional characteristics for millions of cells, flow cytometry (FCM) is widely used in health research, medical diagnosis and treatment, and vaccine development. Nevertheless, there is an increasing concern about the lack of appropriate software tools to provide an automated analysis platform to parallelize the high-throughput data-generation platform. Currently, to a large extent, FCM data analysis relies on the manual selection of sequential regions in 2-D graphical projections to extract the cell populations of interest. This is a time-consuming task that ignores the high-dimensionality of FCM data. Results In view of the aforementioned issues, we have developed an R package called flowClust to automate FCM analysis. flowClust implements a robust model-based clustering approach based on multivariate t mixture models with the Box-Cox transformation. The package provides the functionality to identify cell populations whilst simultaneously handling the commonly encountered issues of outlier identification and data transformation. It offers various tools to summarize and visualize a wealth of features of the clustering results. In addition, to ensure its convenience of use, flowClust has been adapted for the current FCM data format, and integrated with existing Bioconductor packages dedicated to FCM analysis. Conclusion flowClust addresses the issue of a dearth of software that helps automate FCM analysis with a sound theoretical foundation. It tends to give reproducible results, and helps reduce the significant subjectivity and human time cost encountered in FCM analysis. The package contributes to the cytometry community by offering an efficient, automated analysis platform which facilitates the active, ongoing technological advancement.

Published
2009
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23. flowCore: a Bioconductor package for high throughput flow cytometry

Author

Spidlen Josef, Sarkar Deepayan, Haaland Perry, Ellis Byron, Brinkman Ryan R, LeMeur Nolwenn, Hahne Florian, Strain Errol, and Gentleman Robert

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Recent advances in automation technologies have enabled the use of flow cytometry for high throughput screening, generating large complex data sets often in clinical trials or drug discovery settings. However, data management and data analysis methods have not advanced sufficiently far from the initial small-scale studies to support modeling in the presence of multiple covariates. Results We developed a set of flexible open source computational tools in the R package flowCore to facilitate the analysis of these complex data. A key component of which is having suitable data structures that support the application of similar operations to a collection of samples or a clinical cohort. In addition, our software constitutes a shared and extensible research platform that enables collaboration between bioinformaticians, computer scientists, statisticians, biologists and clinicians. This platform will foster the development of novel analytic methods for flow cytometry. Conclusion The software has been applied in the analysis of various data sets and its data structures have proven to be highly efficient in capturing and organizing the analytic work flow. Finally, a number of additional Bioconductor packages successfully build on the infrastructure provided by flowCore, open new avenues for flow data analysis.

Published
2009
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24. Extending pathways based on gene lists using InterPro domain signatures

Author

Wiemann Stefan, Poustka Annemarie, Arlt Dorit, Mehrle Alexander, Hahne Florian, and Beissbarth Tim

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background High-throughput technologies like functional screens and gene expression analysis produce extended lists of candidate genes. Gene-Set Enrichment Analysis is a commonly used and well established technique to test for the statistically significant over-representation of particular pathways. A shortcoming of this method is however, that most genes that are investigated in the experiments have very sparse functional or pathway annotation and therefore cannot be the target of such an analysis. The approach presented here aims to assign lists of genes with limited annotation to previously described functional gene collections or pathways. This works by comparing InterPro domain signatures of the candidate gene lists with domain signatures of gene sets derived from known classifications, e.g. KEGG pathways. Results In order to validate our approach, we designed a simulation study. Based on all pathways available in the KEGG database, we create test gene lists by randomly selecting pathway genes, removing these genes from the known pathways and adding variable amounts of noise in the form of genes not annotated to the pathway. We show that we can recover pathway memberships based on the simulated gene lists with high accuracy. We further demonstrate the applicability of our approach on a biological example. Conclusion Results based on simulation and data analysis show that domain based pathway enrichment analysis is a very sensitive method to test for enrichment of pathways in sparsely annotated lists of genes. An R based software package domainsignatures, to routinely perform this analysis on the results of high-throughput screening, is available via Bioconductor.

Published
2008
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25. Additional file 5: Figure S4. of Reciprocal changes in DNA methylation and hydroxymethylation and a broad repressive epigenetic switch characterize FMR1 transcriptional silencing in fragile X syndrome

Author

Brasa, Sarah, Mueller, Arne, SĂŠbastien Jacquemont, Hahne, Florian, Rozenberg, Izabela, Peters, Thomas, Yunsheng He, McCormack, Christine, Gasparini, Fabrizio, Salah-Dine Chibout, Grenet, Olivier, Moggs, Jonathan, Gomez-Mancilla, Baltazar, and RĂŠmi Terranova

Subjects
congenital, hereditary, and neonatal diseases and abnormalities, embryonic structures, sense organs, skin and connective tissue diseases
Abstract

Selected unrelated loci were interrogated by ChIP-qPCR to validate the specificity of changes observed at FMR1 in FXS patient cells. No significant change in H3K4me2, H4K20me1, H3K9me2, and me3 were observed at three selected loci (active locus RPL19 and two developmentally regulated loci Cdx2 and Oct4). (PDF 409Â kb)

Published
2016
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26. Additional file 10: Table S3. of Reciprocal changes in DNA methylation and hydroxymethylation and a broad repressive epigenetic switch characterize FMR1 transcriptional silencing in fragile X syndrome

Author

Brasa, Sarah, Mueller, Arne, SĂŠbastien Jacquemont, Hahne, Florian, Rozenberg, Izabela, Peters, Thomas, Yunsheng He, McCormack, Christine, Gasparini, Fabrizio, Salah-Dine Chibout, Grenet, Olivier, Moggs, Jonathan, Gomez-Mancilla, Baltazar, and RĂŠmi Terranova

Abstract

List of pyrosequencing assays. This table indicates the primers sequence as well as chromosome coordinates of the amplicon analyzed by pyrosequencing. (DOC 28Â kb)

Published
2016
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27. Additional file 2: Figure S1. of Reciprocal changes in DNA methylation and hydroxymethylation and a broad repressive epigenetic switch characterize FMR1 transcriptional silencing in fragile X syndrome

Author

Brasa, Sarah, Mueller, Arne, Jacquemont, Sébastien, Hahne, Florian, Rozenberg, Izabela, Peters, Thomas, Yunsheng He, McCormack, Christine, Gasparini, Fabrizio, Salah-Dine Chibout, Grenet, Olivier, Moggs, Jonathan, Gomez-Mancilla, Baltazar, and Terranova, Rémi

Subjects
congenital, hereditary, and neonatal diseases and abnormalities
Abstract

Selected FMR1 genomic regions of methylation change throughout the FMR1 locus (Fig. 2a, Additional file 1: Table S1) were interrogated by MeDIP-qPCR (5mC) in DNA extracted from four control (blue) and eight FXS (red) patient PBMCs samples (A). Data represent the enrichment relative to input in individual samples. The location of qPCR primer pairs used in this study is illustrated (B). (PDF 487 kb)

Published
2016
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28. Additional file 7: Figure S5. of Reciprocal changes in DNA methylation and hydroxymethylation and a broad repressive epigenetic switch characterize FMR1 transcriptional silencing in fragile X syndrome

Author

Brasa, Sarah, Mueller, Arne, SĂŠbastien Jacquemont, Hahne, Florian, Rozenberg, Izabela, Peters, Thomas, Yunsheng He, McCormack, Christine, Gasparini, Fabrizio, Salah-Dine Chibout, Grenet, Olivier, Moggs, Jonathan, Gomez-Mancilla, Baltazar, and RĂŠmi Terranova

Abstract

Linear regression analysis of the methylation (5mC) or hydroxymethylation (5hmC) assays and the different histones marks (H3K4me2, H3K9me2, H3K9me3, H4K20me1) in eight FXS patients PBMC samples. Graphs show the relationship with the highest coefficient of determination denoted RSq. The p value is indicated, and the dots gradient coloring represents the mRNA expression level for each sample, black for the highest expression level, and light grey for the lowest level. (PDF 547Â kb)

Published
2016
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29. Additional file 9: Table S2. of Reciprocal changes in DNA methylation and hydroxymethylation and a broad repressive epigenetic switch characterize FMR1 transcriptional silencing in fragile X syndrome

Author

Brasa, Sarah, Mueller, Arne, SĂŠbastien Jacquemont, Hahne, Florian, Rozenberg, Izabela, Peters, Thomas, Yunsheng He, McCormack, Christine, Gasparini, Fabrizio, Salah-Dine Chibout, Grenet, Olivier, Moggs, Jonathan, Gomez-Mancilla, Baltazar, and RĂŠmi Terranova

Abstract

List of the real-time qPCR assays. This table indicates the primers sequence as well as chromosome coordinates of amplicon analyzed by real-time qPCR. (DOC 37Â kb)

Published
2016
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30. Additional file 3: Figure S2. of Reciprocal changes in DNA methylation and hydroxymethylation and a broad repressive epigenetic switch characterize FMR1 transcriptional silencing in fragile X syndrome

Author

Brasa, Sarah, Mueller, Arne, Jacquemont, Sébastien, Hahne, Florian, Rozenberg, Izabela, Peters, Thomas, Yunsheng He, McCormack, Christine, Gasparini, Fabrizio, Salah-Dine Chibout, Grenet, Olivier, Moggs, Jonathan, Gomez-Mancilla, Baltazar, and Terranova, Rémi

Subjects
congenital, hereditary, and neonatal diseases and abnormalities
Abstract

Selected FMR1 genomic regions of methylation change throughout the FMR1 locus (Fig. 2a, Additional file 1: Table S1) were interrogated by hMeDIP-qPCR (5hmC) in DNA extracted from four control (blue) and eight FXS (red) patient PBMCs samples (A). Data represent the enrichment relative to input in individual samples. The location of qPCR primer pairs used in this study is illustrated (B). (PDF 497 kb)

Published
2016
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31. Additional file 4: Figure S3. of Reciprocal changes in DNA methylation and hydroxymethylation and a broad repressive epigenetic switch characterize FMR1 transcriptional silencing in fragile X syndrome

Author

Brasa, Sarah, Mueller, Arne, Jacquemont, Sébastien, Hahne, Florian, Rozenberg, Izabela, Peters, Thomas, Yunsheng He, McCormack, Christine, Gasparini, Fabrizio, Salah-Dine Chibout, Grenet, Olivier, Moggs, Jonathan, Gomez-Mancilla, Baltazar, and Terranova, Rémi

Subjects
congenital, hereditary, and neonatal diseases and abnormalities, fungi, nervous system diseases
Abstract

Selected FMR1 and unrelated loci (APRT and OCT4) were interrogated by ChIP-PCR in healthy and FXS fibroblasts, validating Fig. 3 FMR1 microarray results. Data represent the enrichment relative to input in individual samples. (PDF 519 kb)

Published
2016
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32. Mapping species-specific transcription factor-chromatin interactions during drug-induced liver tumor promotion

Author

Vitobello, Antonio, Kapur, Karen, Zhu, Jiang, Mueller, Arne, Beil, Johanna, Brasa, Sarah, Borowsky, Mark, Oakeley, Edward, Altorfer, Marc, Hahne, Florian, Marc, Philippe, Kelley, Nicholas, Peterson, Brant, Hoersch, Sebastian, Salah-Dine Chibout, Espinola, Alberto Del Rio, Couttet, Philippe, Grenet, Olivier, Moggs, Jonathan, and Terranova, Rémi

Published
2016
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33. QuasR: quantification and annotation of short reads in R

Author

Gaidatzis, Dimos, Lerch, Anita, Hahne, Florian, Stadler, Michael B., Gaidatzis, Dimos, Lerch, Anita, Hahne, Florian, and Stadler, Michael B.

Abstract

Summary: QuasR is a package for the integrated analysis of high-throughput sequencing data in R, covering all steps from read preprocessing, alignment and quality control to quantification. QuasR supports different experiment types (including RNA-seq, ChIP-seq and Bis-seq) and analysis variants (e.g. paired-end, stranded, spliced and allele-specific), and is integrated in Bioconductor so that its output can be directly processed for statistical analysis and visualization. Availability and implementation: QuasR is implemented in R and C/C++. Source code and binaries for major platforms (Linux, OS X and MS Windows) are available from Bioconductor (www.bioconductor.org/packages/release/bioc/html/QuasR.html). The package includes a ‘vignette' with step-by-step examples for typical work flows. Contact: michael.stadler@fmi.ch Supplementary information: Supplementary data are available at Bioinformatics online

Published
2017

34. Translational Safety Genetics

Author

Bhoumik, Priyasma, primary, Del Rio-Espinola, Alberto, additional, Hahne, Florian, additional, Moggs, Jonathan, additional, and Grenet, Olivier, additional

Published
2016
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35. Reciprocal changes in DNA methylation and hydroxymethylation and a broad repressive epigenetic switch characterize FMR1 transcriptional silencing in fragile X syndrome

Author

Brasa, Sarah, primary, Mueller, Arne, additional, Jacquemont, Sébastien, additional, Hahne, Florian, additional, Rozenberg, Izabela, additional, Peters, Thomas, additional, He, Yunsheng, additional, McCormack, Christine, additional, Gasparini, Fabrizio, additional, Chibout, Salah-Dine, additional, Grenet, Olivier, additional, Moggs, Jonathan, additional, Gomez-Mancilla, Baltazar, additional, and Terranova, Rémi, additional

Published
2016
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36. Orchestrating high-throughput genomic analysis with Bioconductor.

Author

UCL - SSS/DDUV - Institut de Duve, Huber, Wolfgang, Carey, Vincent J, Gentleman, Robert, Anders, Simon, Carlson, Marc, Carvalho, Benilton S, Bravo, Hector Corrada, Davis, Sean, Gatto, Laurent, Girke, Thomas, Gottardo, Raphael, Hahne, Florian, Hansen, Kasper D, Irizarry, Rafael A, Lawrence, Michael, Love, Michael I, MacDonald, James, Obenchain, Valerie, Oleś, Andrzej K, Pagès, Hervé, Reyes, Alejandro, Shannon, Paul, Smyth, Gordon K, Tenenbaum, Dan, Waldron, Levi, Morgan, Martin, UCL - SSS/DDUV - Institut de Duve, Huber, Wolfgang, Carey, Vincent J, Gentleman, Robert, Anders, Simon, Carlson, Marc, Carvalho, Benilton S, Bravo, Hector Corrada, Davis, Sean, Gatto, Laurent, Girke, Thomas, Gottardo, Raphael, Hahne, Florian, Hansen, Kasper D, Irizarry, Rafael A, Lawrence, Michael, Love, Michael I, MacDonald, James, Obenchain, Valerie, Oleś, Andrzej K, Pagès, Hervé, Reyes, Alejandro, Shannon, Paul, Smyth, Gordon K, Tenenbaum, Dan, Waldron, Levi, and Morgan, Martin

Abstract

Bioconductor is an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology. The project aims to enable interdisciplinary research, collaboration and rapid development of scientific software. Based on the statistical programming language R, Bioconductor comprises 934 interoperable packages contributed by a large, diverse community of scientists. Packages cover a range of bioinformatic and statistical applications. They undergo formal initial review and continuous automated testing. We present an overview for prospective users and contributors.

Published
2015

37. High throughput flow cytometry analysis with Bioconductor

Author

Le Meur, Nolwenn, Hahne, Florian, Sarkar, Deepayan, Ellis, Byron, Spidlen, Josef, Brinkman, Ryan R, Gentleman, Robert, Biological systems and models, bioinformatics and sequences (SYMBIOSE), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria), Fred Hutchinson Cancer Research Center [Seattle] (FHCRC), AdBrite Inc, Terry Fox Laboratory, BC Cancer Agency (BCCRC)-British Columbia Cancer Agency Research Centre, Groupe d'Etude de la Reproduction Chez l'Homme et les Mammiferes (GERHM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, and Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]
Abstract

International audience; Recent advances in automation technologies have enabled the use of flow cytometry high content screening (FH-HCS), in both basic and clinical research, generating large complex data sets with any covariates. However, data management and data analysis methods have not yet progressed sufficiently far from the initial small-scale studies to support modeling in the presence of multiple covariates. To those aims, we developed a set of computational tools in the R package flowCore to facilitate the analysis of these complex data. We propose R data structures to handle flow cytometry data through the main steps of importing, storing, assessing and preprocessing data from flow cytometry experiments. For example, this package provides facilities for compensation, transformation and filtering preprocessing steps. A key component of the flowCore package is to have suitable data structures that support the application of similar operations to a collection of samples or a clinical cohort. In addition, our software constitutes a shared and extensible research platform that enables collaboration between bioinformaticians, computer scientists, statisticians and biologists. The software has been used in the analysis of various data sets and its data structures have proven to be highly efficient in capturing and organizing the analytic work flow. Finally, a number of additional Bioconductor packages successfully build on the infrastructure provided by flowCore, offers new opportunities for flow data analysis.

Published
2009

39. Translational Safety Genetics.

Author

Bhoumik, Priyasma, Del Rio-Espinola, Alberto, Hahne, Florian, Moggs, Jonathan, and Grenet, Olivier

Subjects
GENETICS, DRUG development, HUMAN genetic variation, PHYSIOLOGY
Abstract

The emerging field of translational safety genetics is providing new opportunities to enhance drug discovery and development. Genetic variation in therapeutic drug targets, off-target interactors and relevant drug metabolism/disposition pathways can contribute to diverse drug pharmacologic and toxicologic responses between different animal species, strains and geographic origins. Recent advances in the sequencing of rodent, canine, nonhuman primate, and minipig genomes have dramatically improved the ability to select the most appropriate animal species for preclinical drug toxicity studies based on genotypic characterization of drug targets/pathways and drug metabolism and/or disposition, thus avoiding inconclusive or misleading animal studies, consistent with the principles of the 3Rs (replacement, reduction and refinement). The genetic background of individual animals should also be taken into consideration when interpreting phenotypic outcomes from toxicity studies and susceptibilities to spontaneous safety-relevant background findings. [ABSTRACT FROM AUTHOR]

Published
2017
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40. Heart Structure-Specific Transcriptomic Atlas Reveals Conserved microRNA-mRNA Interactions

Author

Vacchi-Suzzi, Caterina, primary, Hahne, Florian, additional, Scheubel, Philippe, additional, Marcellin, Magali, additional, Dubost, Valerie, additional, Westphal, Magdalena, additional, Boeglen, Catherine, additional, Büchmann-Møller, Stine, additional, Cheung, Ming Sin, additional, Cordier, André, additional, De Benedetto, Christopher, additional, Deurinck, Mark, additional, Frei, Moritz, additional, Moulin, Pierre, additional, Oakeley, Edward, additional, Grenet, Olivier, additional, Grevot, Armelle, additional, Stull, Robert, additional, Theil, Diethilde, additional, Moggs, Jonathan G., additional, Marrer, Estelle, additional, and Couttet, Philippe, additional

Published
2013
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41. Identification of Dlk1-Dio3 Imprinted Gene Cluster Noncoding RNAs as Novel Candidate Biomarkers for Liver Tumor Promotion

Author

Lempiäinen, Harri, primary, Couttet, Philippe, additional, Bolognani, Federico, additional, Müller, Arne, additional, Dubost, Valérie, additional, Luisier, Raphaëlle, additional, del Rio-Espinola, Alberto, additional, Vitry, Veronique, additional, Unterberger, Elif B., additional, Thomson, John P., additional, Treindl, Fridolin, additional, Metzger, Ute, additional, Wrzodek, Clemens, additional, Hahne, Florian, additional, Zollinger, Tulipan, additional, Brasa, Sarah, additional, Kalteis, Magdalena, additional, Marcellin, Magali, additional, Giudicelli, Fanny, additional, Braeuning, Albert, additional, Morawiec, Laurent, additional, Zamurovic, Natasa, additional, Längle, Ulrich, additional, Scheer, Nico, additional, Schübeler, Dirk, additional, Goodman, Jay, additional, Chibout, Salah-Dine, additional, Marlowe, Jennifer, additional, Theil, Diethilde, additional, Heard, David J., additional, Grenet, Olivier, additional, Zell, Andreas, additional, Templin, Markus F., additional, Meehan, Richard R., additional, Wolf, Roland C., additional, Elcombe, Clifford R., additional, Schwarz, Michael, additional, Moulin, Pierre, additional, Terranova, Rémi, additional, and Moggs, Jonathan G., additional

Published
2012
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46. Per-channel basis normalization methods for flow cytometry data

Author

Hahne, Florian, primary, Khodabakhshi, Alireza Hadj, additional, Bashashati, Ali, additional, Wong, Chao-Jen, additional, Gascoyne, Randy D., additional, Weng, Andrew P., additional, Seyfert-Margolis, Vicky, additional, Bourcier, Katarzyna, additional, Asare, Adam, additional, Lumley, Thomas, additional, Gentleman, Robert, additional, and Brinkman, Ryan R., additional

Published
2009
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50. Functional Profiling: From Microarrays via Cell-Based Assays to Novel Tumor Relevant Modulators of the Cell Cycle

Author

Arlt, Dorit, primary, Huber, Wolfgang, additional, Liebel, Urban, additional, Schmidt, Christian, additional, Majety, Meher, additional, Sauermann, Mamatha, additional, Rosenfelder, Heiko, additional, Bechtel, Stephanie, additional, Mehrle, Alexander, additional, Bannasch, Detlev, additional, Schupp, Ingo, additional, Seiler, Markus, additional, Simpson, Jeremy C., additional, Hahne, Florian, additional, Moosmayer, Petra, additional, Ruschhaupt, Markus, additional, Guilleaume, Birgit, additional, Wellenreuther, Ruth, additional, Pepperkok, Rainer, additional, Sültmann, Holger, additional, Poustka, Annemarie, additional, and Wiemann, Stefan, additional

Published
2005
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