It should be noted that although the repeat identification algorithm generally works for any genome, some parts of the pipeline (e.g. (2010) and examples of its application can be found in a number of published papers (see Appendix). The analysis principles were described in Novak et al. The pipeline uses high-throughput genome sequencing data as an input and performs graph-based clustering analysis of sequence read similarities to identify repetitive elements within analyzed samples. RepeatExplorer is a computational pipeline for discovery and characterization of repetitive sequences in eukaryotic genomes. 5.6 Schematic representation of the RepeatExplorer pipeline.5.3.2 Adding RepeatExplorer to your local Galaxy installation.5.2 List of papers using graph-based read clustering for repeat identification.3.3 Example history #3: Clustering analysis using paired-end Illumina reads.3.2 Example history #2: Comparative analysis of repeats between two genomes.3.1 Example history #1: Clustering analysis of a small sample dataset of 454 reads followed by identification and phylogenetic analysis of retrotransposon RT domains in assembled contigs.2.5 Identification and analysis of LTR-retroelement protein domains.2.3.2.3 Archive with clustering results.2.1.3 Downloading sequences from EBI SRA.2.1 Getting your data to/from the server. This manual was written for original version of RepeatExplorer, manuall for RepeatExplorer2 can be found in this wiki
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