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Open thesis topics
Metatranscriptome assembly (M.Sc.) -- TAKEN
Background
Advances in sequencing technologies have enabled the study of microbial communities, their composition and their genetic potential. In a culture-independent approach known as metagenomics, DNA is obtained directly from the environment and the resulting sequence data is analyzed in order to derive taxonomic community profiles as well as metabolic potential. In a similar manner, translated mRNA of bacterial communities is sequenced (environmental ``RNA-Seq'' or metatranscriptomics) and processed, thereby allowing to identify transcribed genes and perform differential gene expression analysis.
For the management, storage and analysis of such datasets, we have developed and operate the MGX platform, a client-server framework enabling scientists to conveniently process sequence data obtained from microbial communities. MGX offers a wide range of different analysis workflows for taxonomic and functional profiling of metagenome datasets based on unassembled sequence data. Recently, MGX was also extended with a pipeline based on the Common Workflow Language (CWL) supporting metagenome assembly, gene prediction, quantification and taxonomic binning.
Within the scope of de.NBI, the German network for bioinformatics infrastructure, MGX is provided as one the flagship services by the Bielefeld-Giessen Center for microbial bioinformatics.
Thesis aims
- Design and implementation of a bioinformatics pipeline for the de novo assembly, quantification, and binning of metatranscriptome datasets based on CWL,
- performance evaluation of the pipeline with regard to choice of transcriptome
assembler software (e.g. Trinity, rnaSPAdes) , and - exemplary analysis of a sample metatranscriptome dataset.
Prerequisites
- In-depth knowledge of the Linux command line
- Prior experience with workflow systems, preferably Common Workflow Language (CWL)
- Ability to work independently
- Methodical way of working
Contact: Sebastian Jaenicke
Also, additional thesis topics are offered by the group for Algorithmic Bioinfomatics of Prof. Stefan Janssen; a comprehensive list of open theses is available.