MiDRMpol

MiDRMpol is an automated pipeline to detect drug resistance mutations (DRMs) in minor viral populations using high-throughput sequencing (HTS) data. The tool addresses the lack of sophisticated computational infrastructure and expertise required for analyzing HTS data in most diagnostic laboratories.

Key features of MiDRMpol:

1. Accessibility: The pipeline is designed to be user-friendly, making it accessible to researchers and clinicians without extensive computational expertise.

2. Automation: MiDRMpol automates the process of detecting DRMs in minor viral populations, streamlining the analysis workflow.

3. Input data: The pipeline accepts raw HTS data as input, eliminating the need for prior data processing by the user.

4. Comprehensive analysis: MiDRMpol performs quality control, read mapping, variant calling, and DRM identification, providing a complete analysis of the input data.

5. Reporting: The tool generates comprehensive reports on the detected DRMs, their frequencies, and their potential clinical significance.

Topic

Sequencing;Genetic variation;Microbiology

Detail

  • Operation: Sequence trimming;Genotyping

  • Software interface: Command-line interface

  • Language: Perl,Python

  • License: Not stated

  • Cost: Free of charge

  • Version name: -

  • Credit: Swedish Research Council, Karolinska Institutet, European Union, Stockholm County Council.

  • Input: -

  • Output: -

  • Contact: Shambhu G. Aralaguppe shambhu.aralaguppe@gmail.com

  • Collection: -

  • Maturity: -

Publications

  • MiDRMpol: A High-Throughput Multiplexed Amplicon Sequencing Workflow to Quantify HIV-1 Drug Resistance Mutations against Protease, Reverse Transcriptase, and Integrase Inhibitors.
  • Aralaguppe SG, et al. MiDRMpol: A High-Throughput Multiplexed Amplicon Sequencing Workflow to Quantify HIV-1 Drug Resistance Mutations against Protease, Reverse Transcriptase, and Integrase Inhibitors. MiDRMpol: A High-Throughput Multiplexed Amplicon Sequencing Workflow to Quantify HIV-1 Drug Resistance Mutations against Protease, Reverse Transcriptase, and Integrase Inhibitors. 2019; 11:(unknown pages). doi: 10.3390/v11090806
  • https://doi.org/10.3390/V11090806
  • PMID: 31480341
  • PMC: PMC6784143

Download and documentation

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