Patents by Inventor Yun William Yu

Yun William Yu has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20240004838
    Abstract: This disclosure provides for a highly-efficient and scalable compression tool that compresses quality scores, preferably by capitalizing on sequence redundancy. In one embodiment, compression is achieved by smoothing a large fraction of quality score values based on k-mer neighborhood of their corresponding positions in read sequences. The approach exploits the intuition that any divergent base in a k-mer likely corresponds to either a single-nucleotide polymorphism (SNP) or sequencing error; thus, a preferred approach is to only preserve quality scores for probable variant locations and compress quality scores of concordant bases, preferably by resetting them to a default value. By viewing individual read datasets through the lens of k-mer frequencies in a corpus of reads, the approach herein ensures that compression “lossiness” does not affect accuracy in a deleterious way.
    Type: Application
    Filed: September 19, 2023
    Publication date: January 4, 2024
    Inventors: Bonnie Berger Leighton, Deniz Yorukoglu, Yun William Yu, Jian Peng
  • Patent number: 11762813
    Abstract: This disclosure provides for a highly-efficient and scalable compression tool that compresses quality scores, preferably by capitalizing on sequence redundancy. In one embodiment, compression is achieved by smoothing a large fraction of quality score values based on k-mer neighborhood of their corresponding positions in read sequences. The approach exploits the intuition that any divergent base in a k-mer likely corresponds to either a single-nucleotide polymorphism (SNP) or sequencing error; thus, a preferred approach is to only preserve quality scores for probable variant locations and compress quality scores of concordant bases, preferably by resetting them to a default value. By viewing individual read datasets through the lens of k-mer frequencies in a corpus of reads, the approach herein ensures that compression “lossiness” does not affect accuracy in a deleterious way.
    Type: Grant
    Filed: February 5, 2019
    Date of Patent: September 19, 2023
    Inventors: Bonnie Berger Leighton, Deniz Yorukoglu, Yun William Yu, Jian Peng
  • Publication number: 20190171625
    Abstract: This disclosure provides for a highly-efficient and scalable compression tool that compresses quality scores, preferably by capitalizing on sequence redundancy. In one embodiment, compression is achieved by smoothing a large fraction of quality score values based on k-mer neighborhood of their corresponding positions in read sequences. The approach exploits the intuition that any divergent base in a k-mer likely corresponds to either a single-nucleotide polymorphism (SNP) or sequencing error; thus, a preferred approach is to only preserve quality scores for probable variant locations and compress quality scores of concordant bases, preferably by resetting them to a default value. By viewing individual read datasets through the lens of k-mer frequencies in a corpus of reads, the approach herein ensures that compression “lossiness” does not affect accuracy in a deleterious way.
    Type: Application
    Filed: February 5, 2019
    Publication date: June 6, 2019
    Inventors: Bonnie Berger Leighton, Deniz Yorukoglu, Yun William Yu, Jian Peng
  • Patent number: 10198454
    Abstract: This disclosure provides for a highly-efficient and scalable compression tool that compresses quality scores, preferably by capitalizing on sequence redundancy. In one embodiment, compression is achieved by smoothing a large fraction of quality score values based on k-mer neighborhood of their corresponding positions in read sequences. The approach exploits the intuition that any divergent base in a k-mer likely corresponds to either a single-nucleotide polymorphism (SNP) or sequencing error; thus, a preferred approach is to only preserve quality scores for probable variant locations and compress quality scores of concordant bases, preferably by resetting them to a default value. By viewing individual read datasets through the lens of k-mer frequencies in a corpus of reads, the approach herein ensures that compression “lossiness” does not affect accuracy in a deleterious way.
    Type: Grant
    Filed: April 27, 2015
    Date of Patent: February 5, 2019
    Inventors: Bonnie Berger Leighton, Deniz Yorukoglu, Yun William Yu, Jian Peng