MsPAC

MsPAC integrates Pacific Biosciences long-read sequencing and 10x Genomics NGS barcoding to partition reads, assemble haplotypes, and produce haplotype-resolved structural variant (SV) predictions for diploid genome analysis.


Key Features:

  • Integration of sequencing technologies: Integrates Pacific Biosciences long-read sequencing with 10x Genomics NGS barcoding for combined analysis.
  • Read partitioning: Partitions reads to enable haplotype-specific assembly.
  • Haplotype assembly: Assembles haplotypes using existing software frameworks.
  • Phased structural variant prediction: Transforms haplotype assemblies into high-quality, phased structural variant predictions.
  • Long-read resolution: Leverages long reads to span large genomic regions and resolve complex variants.
  • NGS barcoding linkage: Utilizes 10x Genomics barcodes to provide high-throughput linkage information for phasing.
  • Haplotype-resolved SV calls: Produces haplotype-resolved SV calls suitable for diploid genome analyses.

Scientific Applications:

  • Haplotype-resolved SV detection: Enables detection and phasing of structural variants in diploid genomes.
  • Genomics research: Supports comprehensive structural variant analyses in genomics studies.
  • Personalized medicine: Facilitates identification of structural variants relevant to disease susceptibility and clinical research.
  • Evolutionary biology: Aids studies of genetic variation and phenotypic diversity in evolutionary analyses.

Methodology:

Combines Pacific Biosciences long reads with 10x Genomics barcodes, partitions reads, assembles haplotypes with existing software frameworks, and converts assemblies into phased structural variant predictions.

Topics

Details

License:
Unlicense
Maturity:
Mature
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Linux
Programming Languages:
Python
Added:
8/11/2019
Last Updated:
11/24/2024

Operations

Publications

Rodriguez OL, Ritz A, Sharp AJ, Bashir A. MsPAC: a tool for haplotype-phased structural variant detection. Bioinformatics. 2019;36(3):922-924. doi:10.1093/bioinformatics/btz618. PMID:31397844. PMCID:PMC7523683.

PMID: 31397844
PMCID: PMC7523683
Funding: - NIH: 1F31NS108797, NS105781, R21AI117407

Documentation

Links