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Consensus generation and variant detection by Celera Assembler.

Gennady Denisov1, Brian Walenz, Aaron L Halpern

  • 1J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850, USA. gdenisov@jcvi.org

Bioinformatics (Oxford, England)
|March 7, 2008
PubMed
Summary
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A new algorithm identifies allelic variation in Whole Genome Shotgun (WGS) assemblies, producing multiple haploid consensus sequences. This method generated the first diploid human genome sequence and improves accuracy in diploid locus representation.

Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Existing Whole Genome Shotgun (WGS) assemblers generate a single consensus sequence, which may not accurately represent underlying haploid alleles or aligned reads.
  • This can lead to inconsistencies in representing diploid genetic information.

Purpose of the Study:

  • To develop and present an algorithm for identifying allelic variation in WGS assemblies of haploid sequences.
  • To generate a set of haploid consensus sequences instead of a single consensus sequence.
  • To enable the accurate sequencing of diploid genomes.

Main Methods:

  • The algorithm employs a dynamic windowing approach to detect alleles.
  • It simultaneously processes aligned reads spanning sequence variation regions.
  • Reads are assigned to respective alleles, adjacent variant alleles are phased, and consensus sequences are generated for each confirmed allele.

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Main Results:

  • Applied to a human genome assembly, the algorithm detected two confirmed alleles and reported two consensus sequences in 98.98% of detected variation regions.
  • It corrected errors in mosaic haploid representations of diploid loci produced by previous algorithms.
  • The method identified 438,814 new heterozygous SNPs with a 12% false positive rate when calibrated against known SNPs.

Conclusions:

  • The new algorithm successfully generates accurate haploid consensus sequences from WGS data, enabling diploid genome sequencing.
  • It offers improved accuracy and error correction compared to existing WGS assembly methods.
  • The approach is applicable to assemblies of multiple diploid individuals and hybrid assemblies of haploid organisms.