Transpi

The use of RNA-Seq data and the generation of de novo transcriptome assemblies have been pivotal for studies in ecology and evolution. This is distinctly true for non-model organisms, where no genome information is available. Nevertheless, transpi, studies of differential gene expression, DNA enrichment baits design, and phylogenetics transpi all be accomplished with the data gathered at the transcriptomic transpi.

TransPi provides a useful resource for the generation of de novo transcriptome assemblies, with minimum user input but without losing the ability of a thorough analysis. TransPi requires various databases to run. The precheck script will installed the databases and software, if necessary, to run the tool. The precheck run needs a PATH as an argument for installing locally all the databases the pipeline needs. Once the precheck run is done it will create a file named nextflow.

Transpi

TransPi is based on the scientific workflow manager Nextflow. It is designed to help researchers get the best reference transcriptome assembly for their organisms of interest. It performs multiple assemblies with different parameters to then get a non-redundant consensus assembly. All these with minimum input from the user but without losing the potential of a comprehensive analysis. Figure 1. TransPi v1. For simplicity, this diagram does not show all the connections between the processes. Also, it omits other additional options like the BUSCO distribution and transcriptome filtering with psytrans see Section 2. TransPi documentation and examples can be found here. Preprint of TransPi including kmer, reads length, and reads quantities tests can be found here. Also we tested the pipeline with over 45 samples from different phyla.

Also we tested the pipeline with over 45 samples from different transpi. Branches Tags. Test dataset We include a test profile to try TransPi using a small dataset, transpi.

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The use of RNA-Seq data and the generation of de novo transcriptome assemblies have been pivotal for studies in ecology and evolution. This is distinctly true for non-model organisms, where no genome information is available; yet, studies of differential gene expression, DNA enrichment baits design, and phylogenetics can all be accomplished with the data gathered at the transcrip- tomic level. Multiple tools are available for transcriptome assembly, however, no single tool can provide the best assembly for all datasets. Therefore, a multi assembler approach, followed by a reduction step, is often sought to generate an improved representation of the assembly. To reduce errors in these complex analyses while at the same time attaining reproducibility and scalability, automated workflows have been essential in the analysis of RNA-Seq data. However, most of these tools are designed for species where genome data is used as reference for the assembly process, limiting their use in non-model organisms. Researchers from Ludwig Maximilian University of Munich have developed TransPi, a comprehensive pipeline for de novo transcriptome assembly, with minimum user input but without losing the ability of a thorough analysis. A combination of different model organisms, kmer sets, read lengths, and read quantities were used for assessing the tool. Furthermore, a total of 49 non-model organisms, spanning different phyla, were also analyzed. Compared to approaches using single assemblers only, TransPi produces higher BUSCO completeness percentages, and a concurrent significant reduction in duplication rates.

Transpi

By using our site, you agree to our collection of information through the use of cookies. To learn more, view our Privacy Policy. To browse Academia. The use of RNA-Seq data and the generation of de novo transcriptome assemblies have been pivotal for studies in ecology and evolution. This is distinctly true for non-model organisms, where no genome information is available.

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Preprint of TransPi including kmer, reads length, and reads quantities tests can be found here. The authors declared that they comply with the PCI rule of having no financial conflicts of interest in relation to the content of the article. Only one dash is needed for -work since it is a nextflow function. Bioinformatics, 23, — The article presents a meta approach to transcriptome assembly, validation, and annotation. Pipeline processes. To monitor your pipeline remotely without connecting to the server via ssh use Nextflow Tower. RideHub: Ride Hailing Compare. Some individual containers can create problems. View all files. Multiple profiles can be specified comma separated. Perform psytrans filtering of transcriptome. Latest commit History Commits. Branches Tags. TransPI also provides a clear and reproducible workflow.

The use of RNA-Seq data and the generation of de novo transcriptome assemblies have been pivotal for studies in ecology and evolution. This is distinctly true for non-model organisms, where no genome information is available. Nevertheless, studies of differential gene expression, DNA enrichment baits design, and phylogenetics can all be accomplished with the data gathered at the transcriptomic level.

Packages 0 No packages published. Real Time Monitoring To monitor your pipeline remotely without connecting to the server via ssh use Nextflow Tower. Genome Research, 19, — Feeds Stay connected to the college world around you. Default "results" -w, -work name of working directory. Full run and extra annotation Scenario:. TransPi looks for a directory named onlyAnn. A combination of different model organisms, k-mer sets, read lengths and read quantities was used for assessing the tool. Close printable page. One of the main advantages of this approach is its flexibility in working on data from both "model" and "non-model" organisms and various levels of user expertise. Default ". Multiple profiles can be specified comma separated. Pricing We had just made the first standard prices for such a ride-sharing service in your market!