SPP 1530: Flowering Time Control - from Natural Variation to Crop Improvement

PP-6: Grosse, Hinneburg, Zimmermann

RNA-seq data analysis for the PP-1530 consortium



Purpose of the project is the analysis of RNA-seq data in close collaboration with several consortium partners who produce such data sets at a large scale.  This analysis comprises the annotation of genomes, the assembly and annotation of transcriptomes from RNA-seq data, and the quantification of differential expression.


Together with our external partners, we will develop tools and pipelines for the analysis of RNA-seq data in cases where they do not exist or where they are not tailored toward flowering time regulation in higher plants.  Together with our consortium partners, we will establish an iterative process of experiments, predictions, and experimental tests that helps in each iteration to refine the tools and pipelines and to design the next set of experiments, leading to improved predictions in each iteration and to a continuously growing amount of experimentally tested results.

Project-related publications

Köster T, Meyer K, Weinholdt C, Smith LM, Lummer M, Speth C, Grosse I, Weigel D, Staiger D (2014). Regulation of pri-miRNA processing by the hnRNP-like protein AtGRP7 in Arabidopsis. Nucl. Acids Res., doi: 10.1093/nar/gku716

Eggeling R, Roos T, Myllymäki P, Grosse I (2014). Robust learning of inhomogeneous PMMs. Journal of Machine Learning Research 33: 229-237

Hedtke I, Lemnian IM, Müller-Hannemann M, Grosse I (2014). On optimal read trimming in next generation sequencing and its complexity. In Proceedings of AlCoB 2014, volume 8542 of LNBI, pages 83–94. Springer.

Nettling M, Thieme N, Both A, Grosse I (2014). Disk repository with update management and select option for high throughput sequencing data. BMC Bioinformatics 15, 38.

Grau J, Keilwagen J, Gohr A, Paponov IA, Posch S, Seifert M, Strickert M, Grosse I (2013). Dispom: A discriminative de-novo motif discovery tool based on the Jstacs library. Journal of Bioinformatics and Computational Biology 11, 1340006

Quint M, Drost HG, Gabel A, Ullrich KK, Bönn M, Grosse I (2012). A transcriptomic hourglass in plant embryogenesis. Nature 490: 98-101.

Grau J, Keilwagen J, Gohr A, Haldemann B, Posch S, Grosse I (2012). Jstacs: a Java Framework for statistical analysis and classification of biological sequences.Journal of Machine Learning Research 13, 1967-1971.

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