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MaxSpliZer: a Tool to Predict Effects of Splice Variants Based on the Maximum Entropy Model
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  • Seyedmohammad Saadatagah,
  • Reza Shahnazar,
  • Alborz Sherafati,
  • Lubna Alhalabi,
  • Alexandra A. Miller,
  • Marwan Hamed,
  • Iftikhar Kullo
Seyedmohammad Saadatagah
Mayo Clinic Department of Cardiovascular Medicine

Corresponding Author:[email protected]

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Reza Shahnazar
Tehran University of Medical Sciences
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Alborz Sherafati
Mayo Clinic Department of Cardiovascular Medicine
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Lubna Alhalabi
Mayo Clinic Department of Cardiovascular Medicine
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Alexandra A. Miller
Mayo Clinic Department of Cardiovascular Medicine
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Marwan Hamed
Mayo Clinic Department of Cardiovascular Medicine
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Iftikhar Kullo
Mayo Clinic Department of Cardiovascular Medicine
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Abstract

The Clinical Genome Resource Consortium (ClinGen) recommends MaxEntScan (MES) model to predict effects of LDLR splice variants. We developed “MaxSpliZer”, a software tool to automate implementation of MES and validated it using ClinVar and UK-Biobank (UKBB) data. We tested concordance of MaxSpliZer predictions with ClinVar classifications of pathogenicity of variants in LDLR and FBN1 with potential effect on splicing. We also annotated LDLR splice variants in 200,618 UKBB participants, categorizing them using MaxSpliZer as deleterious (n=90) and non-deleterious (n=7,404). Low-density lipoprotein cholesterol (LDL-C) levels were compared in these two groups after adjustment for lipid lowering medication use. MaxSpliZer prediction was concordant with the ClinVar classification in 96% of LDLR variants and 98% of FBN1 variants. In the UKBB, splice variants predicted as deleterious by MaxSpliZer had higher LDL-C than non-deleterious splice variants (158.7±47.4 vs. 146.0±34.8mg/dL, p-value = 0.014). Compared to manual curation time of 12±7 min per variant, MaxSpliZer took 0.52±0.11 min for single entries and 1.5 s per variant for biobank-scale data. MaxSpliZer, a software tool that implements MES based on the ClinGen guideline, can accurately classify splice variants in a rapid automated fashion.