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Fig. 6 | BMC Bioinformatics

Fig. 6

From: VISPA2: a scalable pipeline for high-throughput identification and annotation of vector integration sites

Fig. 6

Web Interface, workflow. A web version of VISPA2 is freely available at http://openserver.itb.cnr.it/vispa, it is open to all users and no login required, although there is a 50 MB limit in the size of input data (for larger analysis, please download the pipeline on your server or contact the authors). The figure shows a flowchart of the application. a At the first page the user can specify to run the single-end version or the paired-end version of the pipeline. In a second screen the user must upload the input sequences (demo examples are also provided) and set the VISPA2 parameters. Clicking for the next page, data are uploaded to the backend server. Then, a submission page is presented to the user that must confirm all the information provided. Clicking for the next page, the computation starts. At this point, a results page is presented, which shows the pipeline advancement while the computation is running. The user can wait for the end of the computation or bookmark this address and return later. Once the pipeline is finished, the same page presents the results achieved by the VISPA2 pipeline. bf In the results page, different statistics are reported (the output is the same for the single-end and the paired-end version): (b) a histogram of the IS distribution in the genome is shown, while in the bottom part some tab panels are present, showing different detailed statistics. The first tab contains a table showing the specific chromosome locus and strand of each IS, also reporting the nearest gene. The second tab (c) presents a circos plot of the IS density in the genome, while (d) a tag cloud of the genes more targeted by insertions is plotted in the third tab. We also implemented a Gene Ontology (GO) enrichment analysis of the target genes (e), considering the three branches of GO (Molecular Function, Biological Process, and Cellular Components), which is shown in the fourth tab. Beside the p-values achieved in this analysis, a diagram is reported of the most representative GO terms, bi-clustered according to their semantic similarity. The last tab (f) represents the statistics concerning the dataset computed by samstats [38]

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