TIminer

TIminer performs integrative analysis of next-generation sequencing (NGS) data to characterize tumor–immune interactions for cancer immunology and immunotherapy research.


Key Features:

  • Integrative immunogenomic analyses: Combines multiple immunogenomic analyses from NGS data to assess tumor–immune system relationships.
  • Human Leukocyte Antigen (HLA) typing: Identifies HLA types from NGS data for patient-specific immune profiling.
  • Neoantigen prediction: Predicts candidate neoantigen peptides derived from tumor variants for immunogenicity assessment.
  • Characterization of immune infiltrates: Quantifies composition and abundance of immune cell populations within the tumor microenvironment.
  • Quantification of tumor immunogenicity: Assesses tumor immunogenic potential to inform likelihood of eliciting immune responses.
  • Automated multi-step pipeline: Integrates and automates multi-step NGS analyses to produce reproducible outputs with reduced manual intervention.

Scientific Applications:

  • Personalized medicine approaches: Enables HLA typing and neoantigen prediction to support development of tailored immunotherapies.
  • Research into tumor microenvironments: Provides immune infiltrate profiles to study interactions between immune cells and tumors.
  • Evaluating immunotherapy efficacy: Supplies tumor immunogenicity metrics to predict and assess responses to immunotherapeutic interventions.

Methodology:

TIminer automates the integration and analysis of NGS data through a streamlined multi-step pipeline that minimizes manual intervention.

Topics

Details

Tool Type:
command-line tool
Operating Systems:
Linux, Mac
Programming Languages:
Python
Added:
6/12/2018
Last Updated:
11/25/2024

Operations

Publications

Tappeiner E, Finotello F, Charoentong P, Mayer C, Rieder D, Trajanoski Z. TIminer: NGS data mining pipeline for cancer immunology and immunotherapy. Bioinformatics. 2017;33(19):3140-3141. doi:10.1093/bioinformatics/btx377. PMID:28633385. PMCID:PMC5870678.

PMID: 28633385
PMCID: PMC5870678
Funding: - Austrian Science Fund: W1101-B18 - Austrian National Bank: 16534

Documentation