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                <text>Coronavirus</text>
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                <text>Dominio científico: Coronavirus</text>
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          <name>Title</name>
          <description>A name given to the resource</description>
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              <text>A secure SNP panel scheme using homomorphically encrypted K-mers without SNP calling on the user side</text>
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          <name>Creator</name>
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            <elementText elementTextId="14664">
              <text>Sung-Joon PARK, Minsu Kim, Seok-Jun Seo, Seung Wan Hong, Kyoohyung Han, Keewoo Lee, Jung Hee Cheon, Sun Kim</text>
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          <name>Description</name>
          <description>An account of the resource</description>
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              <text>Abstract Background Single Nucleotide Polymorphism (SNP) in the genome has become crucial information for clinical use. For example, the targeted cancer therapy is primarily based on the information which clinically important SNPs are detectable from the tumor. Many hospitals have developed their own panels that include clinically important SNPs. The genome information exchange between the patient and the hospital has become more popular. However, the genome sequence information is innate and irreversible and thus its leakage has serious consequences. Therefore, protecting one’s genome information is critical. On the other side, hospitals may need to protect their own panels. There is no known secure SNP panel scheme to protect both. Results In this paper, we propose a secure SNP panel scheme using homomorphically encrypted K-mers without requiring SNP calling on the user side and without revealing the panel information to the user. Use of the powerful homomorphic encryption technique is desirable, but there is no known algorithm to efficiently align two homomorphically encrypted sequences. Thus, we designed and implemented a novel secure SNP panel scheme utilizing the computationally feasible equality test on two homomorphically encrypted K-mers. To make the scheme work correctly, in addition to SNPs in the panel, sequence variations at the population level should be addressed. We designed a concept of Point Deviation Tolerance (PDT) level to address the false positives and false negatives. Using the TCGA BRCA dataset, we demonstrated that our scheme works at the level of over a hundred thousand somatic mutations. In addition, we provide a computational guideline for the panel design, including the size of K-mer and the number of SNPs. Conclusions The proposed method is the first of its kind to protect both the user’s sequence and the hospital’s panel information using the powerful homomorphic encryption scheme. We demonstrated that the scheme works with a simulated dataset and the TCGA BRCA dataset. In this study, we have shown only the feasibility of the proposed scheme and much more efforts should be done to make the scheme usable for clinical use.</text>
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          <name>Date</name>
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              <text>2019</text>
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        <element elementId="49">
          <name>Subject</name>
          <description>The topic of the resource</description>
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              <text>SNP panel, Homomorphic encryption, k-mer, Genomic security, Genomic privacy</text>
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          <name>Identifier</name>
          <description>An unambiguous reference to the resource within a given context</description>
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            <elementText elementTextId="14668">
              <text>DOI: 10.1186/s12864-019-5473-z</text>
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        <element elementId="48">
          <name>Source</name>
          <description>A related resource from which the described resource is derived</description>
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            <elementText elementTextId="14669">
              <text>BMC Genomics</text>
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          <name>Publisher</name>
          <description>An entity responsible for making the resource available</description>
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            <elementText elementTextId="14670">
              <text>BMC</text>
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          <name>Coverage</name>
          <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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            <elementText elementTextId="14671">
              <text>Genetics, Biotechnology</text>
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          <name>Language</name>
          <description>A language of the resource</description>
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              <text>EN</text>
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