SUMMARY: MicroRNAs have been shown to be able to modulate the tumor microenvironment and the immune response and hence could be interesting biomarkers and therapeutic targets in immuno-oncology; however, dedicated analysis tools are missing. Here, we present a user-friendly web platform MIO and a Python toolkit miopy integrating various methods for visualization and analysis of provided or custom bulk microRNA and gene expression data. We include regularized regression and survival analysis and provide information of 40 microRNA target prediction tools as well as a collection of curated immune related gene and microRNA signatures and processed TCGA data including estimations of infiltrated immune cells and the immunophenoscore. The integration of several machine learning methods enables the selection of prognostic and predictive microRNAs and gene interaction network biomarkers. AVAILABILITY AND IMPLEMENTATION: https://mio.icbi.at, https://github.com/icbi-lab/mio and https://github.com/icbi-lab/miopy. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: Somatic mutations and gene fusions can produce immunogenic neoantigens mediating anticancer immune responses. However, their computational prediction from sequencing data requires complex computational workflows to identify tumor-specific aberrations, derive the resulting peptides, infer patients' Human Leukocyte Antigen types and predict neoepitopes binding to them, together with a set of features underlying their immunogenicity. Here, we present nextNEOpi (nextflow NEOantigen prediction pipeline) a comprehensive and fully automated bioinformatic pipeline to predict tumor neoantigens from raw DNA and RNA sequencing data. In addition, nextNEOpi quantifies neoepitope- and patient-specific features associated with tumor immunogenicity and response to immunotherapy. AVAILABILITY AND IMPLEMENTATION: nextNEOpi source code and documentation are available at https://github.com/icbi-lab/nextNEOpi. CONTACT: [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: Gene fusions can generate immunogenic neoantigens that mediate anticancer immune responses. However, their computational prediction from RNA sequencing (RNA-seq) data requires deep bioinformatics expertise to assembly a computational workflow covering the prediction of: fusion transcripts, their translated proteins and peptides, Human Leukocyte Antigen (HLA) types, and peptide-HLA binding affinity. Here, we present NeoFuse, a computational pipeline for the prediction of fusion neoantigens from tumor RNA-seq data. NeoFuse can be applied to cancer patients' RNA-seq data to identify fusion neoantigens that might expand the repertoire of suitable targets for immunotherapy. AVAILABILITY AND IMPLEMENTATION: NeoFuse source code and documentation are available under GPLv3 license at https://icbi.i-med.ac.at/NeoFuse/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: Advances in single-cell technologies have enabled the investigation of T-cell phenotypes and repertoires at unprecedented resolution and scale. Bioinformatic methods for the efficient analysis of these large-scale datasets are instrumental for advancing our understanding of adaptive immune responses. However, while well-established solutions are accessible for the processing of single-cell transcriptomes, no streamlined pipelines are available for the comprehensive characterization of T-cell receptors. Here, we propose single-cell immune repertoires in Python (Scirpy), a scalable Python toolkit that provides simplified access to the analysis and visualization of immune repertoires from single cells and seamless integration with transcriptomic data. AVAILABILITY AND IMPLEMENTATION: Scirpy source code and documentation are available at https://github.com/icbi-lab/scirpy. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUMMARY: Recently, a number of powerful computational tools for dissecting tumor-immune cell interactions from next-generation sequencing data have been developed. However, the assembly of analytical pipelines and execution of multi-step workflows are laborious and involve a large number of intermediate steps with many dependencies and parameter settings. Here we present TIminer, an easy-to-use computational pipeline for mining tumor-immune cell interactions from next-generation sequencing data. TIminer enables integrative immunogenomic analyses, including: human leukocyte antigens typing, neoantigen prediction, characterization of immune infiltrates and quantification of tumor immunogenicity. AVAILABILITY AND IMPLEMENTATION: TIminer is freely available at http://icbi.i-med.ac.at/software/timiner/timiner.shtml. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: The significance and function of posttranscriptional cytosine methylation in poly(A)RNA attracts great interest but is still poorly understood. High-throughput sequencing of RNA treated with bisulfite (RNA-BSseq) or subjected to enrichment techniques like Aza-IP or miCLIP enables transcriptome wide studies of this particular modification at single base pair resolution. However, to date, there are no specialized software tools available for the analysis of RNA-BSseq or Aza-IP data. Therefore, we developed meRanTK, the first publicly available tool kit which addresses the special demands of high-throughput RNA cytosine methylation data analysis. It provides fast and easy to use splice-aware bisulfite sequencing read mapping, comprehensive methylation calling and identification of differentially methylated cytosines by statistical analysis of single- and multi-replicate experiments. Application of meRanTK to RNA-BSseq or Aza-IP data produces accurate results in standard compliant formats. AVAILABILITY AND IMPLEMENTATION: meRanTK, source code and test data are released under the GNU GPLv3+ license and are available at http://icbi.at/software/meRanTK/ CONTACT: [email protected].

BACKGROUND: In recent years, the genome biology community has expended considerable effort to confront the challenges of managing heterogeneous data in a structured and organized way and developed laboratory information management systems (LIMS) for both raw and processed data. On the other hand, electronic notebooks were developed to record and manage scientific data, and facilitate data-sharing. Software which enables both, management of large datasets and digital recording of laboratory procedures would serve a real need in laboratories using medium and high-throughput techniques. RESULTS: We have developed iLAP (Laboratory data management, Analysis, and Protocol development), a workflow-driven information management system specifically designed to create and manage experimental protocols, and to analyze and share laboratory data. The system combines experimental protocol development, wizard-based data acquisition, and high-throughput data analysis into a single, integrated system. We demonstrate the power and the flexibility of the platform using a microscopy case study based on a combinatorial multiple fluorescence in situ hybridization (m-FISH) protocol and 3D-image reconstruction. iLAP is freely available under the open source license AGPL from http://genome.tugraz.at/iLAP/. CONCLUSION: iLAP is a flexible and versatile information management system, which has the potential to close the gap between electronic notebooks and LIMS and can therefore be of great value for a broad scientific community.

UNLABELLED: ClusterControl is a web interface to simplify distributing and monitoring bioinformatics applications on Linux cluster systems. We have developed a modular concept that enables integration of command line oriented program into the application framework of ClusterControl. The systems facilitate integration of different applications accessed through one interface and executed on a distributed cluster system. The package is based on freely available technologies like Apache as web server, PHP as server-side scripting language and OpenPBS as queuing system and is available free of charge for academic and non-profit institutions. AVAILABILITY: http://genome.tugraz.at/Software/ClusterControl