Illumina has been granted a patent for an analytics system that can identify duplicate DNA fragments and detect cancer presence in a test subject. The system uses methylation state vectors and a modified Hamming distance to determine if two fragments are duplicates. If they are, the system removes one of the fragments and applies a cancer prediction model to generate a prediction for the test subject. GlobalData’s report on Illumina gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Illumina, Microfluidics automation was a key innovation area identified from patents. Illumina's grant share as of September 2023 was 40%. Grant share is based on the ratio of number of grants to total number of patents.
Method for identifying duplicate dna fragments and predicting cancer
A recently granted patent (Publication Number: US11773450B2) describes a method for identifying duplicate DNA fragments and detecting the presence of cancer in a test subject. The method involves sequencing a physical sample obtained from the test subject, which contains multiple fragments including duplicate DNA fragments. The first step is to identify a pair of fragments that are derived from the same reference location.
Next, a methylation state vector is generated for each fragment, which represents the methylation state of each CpG site in the fragment. The methylation states can be methylated, unmethylated, variant, or ambiguous. Difference scores are computed for each CpG site by comparing the methylation states between the two fragments. These difference scores are used to calculate a modified Hamming distance.
If the modified Hamming distance does not exceed a threshold score, the second fragment is labeled as a duplicate of the first fragment. The duplicate fragment is then removed from the set of fragments, generating a reduced set. Finally, a cancer prediction model is applied to the reduced set of fragments to generate a cancer prediction for the test subject.
The patent also includes additional claims and variations of the method. For example, it describes how the difference scores can be computed based on the methylation states within pairs of sequence reads. It also discusses the identification of unique fragments with modified Hamming distances exceeding the threshold score, and the application of a cancer prediction model to these unique fragments.
The patent further mentions the use of p-value filtering to identify anomalous fragments and the application of the cancer prediction model to these anomalous fragments. It also describes the generation of a test feature vector based on the overlap of anomalous fragments with CpG sites in a reference genome, which is then used as input for the cancer prediction model.
Overall, this patent presents a method for identifying duplicate DNA fragments and predicting cancer presence based on methylation patterns. The method utilizes sequencing data and computational analysis to provide a potential tool for cancer detection and diagnosis.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
