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Bambam: parallel comparative analysis of high-throughput sequencing data

  • US 9,646,134 B2
  • Filed: 11/18/2011
  • Issued: 05/09/2017
  • Est. Priority Date: 05/25/2010
  • Status: Active Grant
First Claim
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1. A processor-based method of deriving a differential genetic sequence object, the method comprising:

  • providing access to a genetic database storing (a) a first genetic sequence string representing a first tissue and (b) a second genetic sequence string representing a second tissue, wherein the first and second sequence strings have a plurality of corresponding sub-strings;

    providing access to a sequence analysis engine coupled with the genetic database;

    producing, using the sequence analysis engine, a local alignment using a known position of at least one of a plurality of corresponding sub-strings;

    determining base probabilities of possible locations of sequence reads in the first and second genetic sequence strings as a function of error rates of at least one sequencer;

    identifying a difference between the first set and the second set of genetic sequence strings by comparing genotypes from the first and the second sets that, overlapping at a particular genomic position, maximize a likelihood probability function identifying the genotypes as being different and that are located at the particular genomic position, where the likelihood probability function operates as a probability distribution of a likelihood that unmapped sequence reads of both the first set, representing the first tissue, and the second set, representing the second tissue, align to possible junction sequences, modeled over the base probabilities and associated sequence reads;

    using the local alignment and the identifying the difference to generate a local differential string between the first and second sequence strings within the local alignment; and

    using, by the sequence analysis engine, the local differential string to update a differential genetic sequence object in a differential sequence database with information according to the local differential string; and

    generating a patient specific clinical instruction based on the information of the differential genetic sequence object.

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