kGEM

kGEM reconstructs haplotypes from single-amplicon sequencing data using an expectation maximization (EM) algorithm to distinguish true genetic variants from sequencing errors within viral quasispecies.

Key Features:

• Haplotype Identification: Reconstructs haplotypes from single-amplicon sequencing data to resolve genetic variants in viral populations.
• Error Correction: Applies an expectation maximization (EM) algorithm to differentiate sequencing errors from true variants during reconstruction.
• Input Format and Conversion: Requires aligned reads in a proprietary internal format and provides the auxiliary program ERIF (ERIF Read Converter) to convert reads from FASTA (unaligned) or SAM (pairwise alignment) into that format.

Scientific Applications:

• Virology Research: Enables analysis of genetic diversity in viral populations from single-amplicon sequencing data.
• Viral Evolution: Supports inference of viral evolution by resolving haplotype structures within quasispecies.
• Drug Resistance Mechanisms: Facilitates detection and characterization of variants relevant to drug resistance mechanisms.
• Pathogenicity Studies: Aids investigation of variants that may influence viral pathogenicity.

Methodology:

Uses an expectation maximization (EM) algorithm for haplotype reconstruction and error correction; requires aligned reads in a proprietary internal format and uses ERIF to convert FASTA or SAM reads into that format.