Unipro UGENE: a unified bioinformatics toolkitUNLABELLED: Unipro UGENE is a multiplatform open-source software with the main goal of assisting molecular biologists without much expertise in bioinformatics to manage, analyze and visualize their data. UGENE integrates widely used bioinformatics tools within a common user interface. The toolkit supports multiple biological data formats and allows the retrieval of data from remote data sources. It provides visualization modules for biological objects such as annotated genome sequences, Next Generation Sequencing (NGS) assembly data, multiple sequence alignments, phylogenetic trees and 3D structures. Most of the integrated algorithms are tuned for maximum performance by the usage of multithreading and special processor instructions. UGENE includes a visual environment for creating reusable workflows that can be launched on local resources or in a High Performance Computing (HPC) environment. UGENE is written in C++ using the Qt framework. The built-in plugin system and structured UGENE API make it possible to extend the toolkit with new functionality. AVAILABILITY AND IMPLEMENTATION: UGENE binaries are freely available for MS Windows, Linux and Mac OS X at http://ugene.unipro.ru/download.html. UGENE code is licensed under the GPLv2; the information about the code licensing and copyright of integrated tools can be found in the LICENSE.3rd_party file provided with the source bundle.
Qualimap 2: advanced multi-sample quality control for high-throughput sequencing dataMOTIVATION: Detection of random errors and systematic biases is a crucial step of a robust pipeline for processing high-throughput sequencing (HTS) data. Bioinformatics software tools capable of performing this task are available, either for general analysis of HTS data or targeted to a specific sequencing technology. However, most of the existing QC instruments only allow processing of one sample at a time. RESULTS: Qualimap 2 represents a next step in the QC analysis of HTS data. Along with comprehensive single-sample analysis of alignment data, it includes new modes that allow simultaneous processing and comparison of multiple samples. As with the first version, the new features are available via both graphical and command line interface. Additionally, it includes a large number of improvements proposed by the user community. AVAILABILITY AND IMPLEMENTATION: The implementation of the software along with documentation is freely available at http://www.qualimap.org. CONTACT: meyer@mpiib-berlin.mpg.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Qualimap: evaluating next-generation sequencing alignment dataMOTIVATION: The sequence alignment/map (SAM) and the binary alignment/map (BAM) formats have become the standard method of representation of nucleotide sequence alignments for next-generation sequencing data. SAM/BAM files usually contain information from tens to hundreds of millions of reads. Often, the sequencing technology, protocol and/or the selected mapping algorithm introduce some unwanted biases in these data. The systematic detection of such biases is a non-trivial task that is crucial to drive appropriate downstream analyses. RESULTS: We have developed Qualimap, a Java application that supports user-friendly quality control of mapping data, by considering sequence features and their genomic properties. Qualimap takes sequence alignment data and provides graphical and statistical analyses for the evaluation of data. Such quality-control data are vital for highlighting problems in the sequencing and/or mapping processes, which must be addressed prior to further analyses. AVAILABILITY: Qualimap is freely available from http://www.qualimap.org.
DNA methylation-based classification and grading system for meningioma: a multicentre, retrospective analysisA mechanistic classification of clinical phenotypes in neuroblastomaNeuroblastoma is a pediatric tumor of the sympathetic nervous system. Its clinical course ranges from spontaneous tumor regression to fatal progression. To investigate the molecular features of the divergent tumor subtypes, we performed genome sequencing on 416 pretreatment neuroblastomas and assessed telomere maintenance mechanisms in 208 of these tumors. We found that patients whose tumors lacked telomere maintenance mechanisms had an excellent prognosis, whereas the prognosis of patients whose tumors harbored telomere maintenance mechanisms was substantially worse. Survival rates were lowest for neuroblastoma patients whose tumors harbored telomere maintenance mechanisms in combination with RAS and/or p53 pathway mutations. Spontaneous tumor regression occurred both in the presence and absence of these mutations in patients with telomere maintenance-negative tumors. On the basis of these data, we propose a mechanistic classification of neuroblastoma that may benefit the clinical management of patients.