Bioinformatics Workflow Management With The Wobidisco Ecosystem

Mondet, Sebastien; Ba, Aksoy; Rozenberg, L; Hodes, Isaac; Hammerbacher, Jeff

doi:10.1101/213884

Cited by 4 publications

(3 citation statements)

References 26 publications

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“…Most of the tools can predict neoepitopes from SNVs, some also incorporate INDELs (pVACseq ( 211 ), MuPeXI ( 207 ), TSNAD ( 212 ), CloudNeo ( 213 ), Epidisco ( 214 ), pTuneos ( 215 ), antigen.garnish ( 195 ), NeoPredPipe ( 216 ), NeoEpiScope ( 217 ), OpenVax ( 218 )). A few focus solely on INDELs (ScanNeo ( 219 )) or gene fusions (NeoFuse ( 220 ), INTEGRATE-neo ( 221 )), while others allow users to input the variants as peptides (EDGE ( 97 ), DeepHLApan ( 103 )).…”

Section: Integrated Software For Neoantigen Detection and Prioritizationmentioning

confidence: 99%

Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy

Bulashevska,

Nacsa,

Lang

et al. 2024

Front. Immunol.

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Cancer immunotherapy has witnessed rapid advancement in recent years, with a particular focus on neoantigens as promising targets for personalized treatments. The convergence of immunogenomics, bioinformatics, and artificial intelligence (AI) has propelled the development of innovative neoantigen discovery tools and pipelines. These tools have revolutionized our ability to identify tumor-specific antigens, providing the foundation for precision cancer immunotherapy. AI-driven algorithms can process extensive amounts of data, identify patterns, and make predictions that were once challenging to achieve. However, the integration of AI comes with its own set of challenges, leaving space for further research. With particular focus on the computational approaches, in this article we have explored the current landscape of neoantigen prediction, the fundamental concepts behind, the challenges and their potential solutions providing a comprehensive overview of this rapidly evolving field.

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Section: Integrated Software For Neoantigen Detection and Prioritizationmentioning

confidence: 99%

Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy

Bulashevska,

Nacsa,

Lang

et al. 2024

Front. Immunol.

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“…Epidisco ( 55 ) takes as input wild type DNA, tumor DNA and tumor RNA sequencing data. The tool maps the normal and tumor DNA samples to the human GRCh37 reference genome.…”

Section: Neoantigen Predictionmentioning

confidence: 99%

T Cell Epitope Prediction and Its Application to Immunotherapy

et al. 2021

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T cells play a crucial role in controlling and driving the immune response with their ability to discriminate peptides derived from healthy as well as pathogenic proteins. In this review, we focus on the currently available computational tools for epitope prediction, with a particular focus on tools aimed at identifying neoepitopes, i.e. cancer-specific peptides and their potential for use in immunotherapy for cancer treatment. This review will cover how these tools work, what kind of data they use, as well as pros and cons in their respective applications.

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“…The workflow management tool that orchestrates the execution of the PGV pipeline is called Epidisco ( 41 ). Epidisco is used to set up a local or cluster compute environment, install all relevant bioinformatics tools (external software such as GATK, as well as our own tools including Isovar and Vaxrank), and coordinate the execution of these different tools on the input data.…”

Section: Epidisco: Parallel Implementation Of the Pgv Pipelinementioning

confidence: 99%

Computational Pipeline for the PGV-001 Neoantigen Vaccine Trial

et al. 2018

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This paper describes the sequencing protocol and computational pipeline for the PGV-001 personalized vaccine trial. PGV-001 is a therapeutic peptide vaccine targeting neoantigens identified from patient tumor samples. Peptides are selected by a computational pipeline that identifies mutations from tumor/normal exome sequencing and ranks mutant sequences by a combination of predicted Class I MHC affinity and abundance estimated from tumor RNA. The personalized genomic vaccine (PGV) pipeline is modular and consists of independently usable tools and software libraries. We hope that the functionality of these tools may extend beyond the specifics of the PGV-001 trial and enable other research groups in their own neoantigen investigations.

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Bioinformatics Workflow Management With The Wobidisco Ecosystem

Cited by 4 publications

References 26 publications

Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy

Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy

T Cell Epitope Prediction and Its Application to Immunotherapy

Computational Pipeline for the PGV-001 Neoantigen Vaccine Trial

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