SmMIP-tools

SmMIP-tools processes and analyzes single-molecule molecular inversion probe (smMIP) sequencing data to enable high-multiplex targeted next-generation sequencing (NGS) experiments and sensitive detection of genetic variants.


Key Features:

  • Integrated analytic pipeline: Consolidates quality control, read–smMIP linkage generation, molecular tag retrieval, and variant calling into a single computational pipeline.
  • Read processing tool: Performs quality control, establishes linkages between sequencing reads and smMIPs, and retrieves molecular tags.
  • Error-aware variant caller: Detects single nucleotide variants (SNVs) and short insertions and deletions (indels) while accounting for sequencing errors to improve accuracy.
  • Benchmarking and validation: Validated on a cell-line DNA dilution series and a cohort of blood cancer patients with results concordant with clinical sequencing reports.

Scientific Applications:

  • High-multiplex targeted NGS studies: Enables smMIP-based high-multiplex targeted NGS experiments for genetic research.
  • Personalized medicine: Supports sensitive detection of genetic variants in contexts relevant to personalized medicine.
  • Clinical research in hematologic malignancies: Applied to analysis of blood cancer patient cohorts with demonstrated concordance to clinical sequencing reports.
  • Assay development and validation: Used for analytical validation workflows such as cell-line DNA dilution series.

Methodology:

Performs quality control, generates read–smMIP linkages, retrieves molecular tags, and applies an error-aware variant caller to detect SNVs and short indels.

Topics

Details

License:
MIT
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Mac, Linux, Windows
Programming Languages:
R, Shell
Added:
10/15/2021
Last Updated:
10/15/2021

Operations

Publications

Medeiros JJF, Capo-Chichi J, Shlush LI, Dick JE, Arruda A, Minden MD, Abelson S. SmMIP-tools: a computational toolset for processing and analysis of single-molecule molecular inversion probes derived data. Unknown Journal. 2021. doi:10.1101/2021.06.03.446993.

Documentation