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  1. Article ; Online: Imaging Endophenotypes of Stroke as a Target for Genetic Studies.

    Jian, Xueqiu / Fornage, Myriam

    Stroke

    2018  Volume 49, Issue 6, Page(s) 1557–1562

    MeSH term(s) Brain/diagnostic imaging ; Endophenotypes ; Genetic Predisposition to Disease ; Genetic Testing ; Humans ; Stroke/diagnostic imaging ; Stroke/genetics
    Language English
    Publishing date 2018-05-14
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Review
    ZDB-ID 80381-9
    ISSN 1524-4628 ; 0039-2499 ; 0749-7954
    ISSN (online) 1524-4628
    ISSN 0039-2499 ; 0749-7954
    DOI 10.1161/STROKEAHA.117.017073
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  2. Article ; Online: In Silico Prediction of Deleteriousness for Nonsynonymous and Splice-Altering Single Nucleotide Variants in the Human Genome.

    Jian, Xueqiu / Liu, Xiaoming

    Methods in molecular biology (Clifton, N.J.)

    2017  Volume 1498, Page(s) 191–197

    Abstract: In silico prediction methods have increasingly been valuable and popular in molecular biology, especially in human genetics, for deleteriousness prediction to filter and prioritize huge amounts of DNA variation identified by sequencing human genomes. ... ...

    Abstract In silico prediction methods have increasingly been valuable and popular in molecular biology, especially in human genetics, for deleteriousness prediction to filter and prioritize huge amounts of DNA variation identified by sequencing human genomes. There is a rich collection of available methods developed upon different levels/aspects of knowledge about how DNA variations affect gene expression. Given the fact that their predictions are not always consistent or even opposite of what was expected, using consensus prediction or majority vote among these methods is preferred to trusting any single one. Because querying different databases for different methods is both tedious and time-consuming for such big data sets, one database integrating predictions from multiple databases can facilitate the process. In this chapter, we describe the general steps of obtaining comprehensive predictions and annotations for large numbers of variants from dbNSFP, the first and probably the most widely used database of its kind.
    Language English
    Publishing date 2017
    Publishing country United States
    Document type Journal Article
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-4939-6472-7_13
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  3. Article ; Online: In silico prediction of splice-altering single nucleotide variants in the human genome.

    Jian, Xueqiu / Boerwinkle, Eric / Liu, Xiaoming

    Nucleic acids research

    2014  Volume 42, Issue 22, Page(s) 13534–13544

    Abstract: In silico tools have been developed to predict variants that may have an impact on pre-mRNA splicing. The major limitation of the application of these tools to basic research and clinical practice is the difficulty in interpreting the output. Most tools ... ...

    Abstract In silico tools have been developed to predict variants that may have an impact on pre-mRNA splicing. The major limitation of the application of these tools to basic research and clinical practice is the difficulty in interpreting the output. Most tools only predict potential splice sites given a DNA sequence without measuring splicing signal changes caused by a variant. Another limitation is the lack of large-scale evaluation studies of these tools. We compared eight in silico tools on 2959 single nucleotide variants within splicing consensus regions (scSNVs) using receiver operating characteristic analysis. The Position Weight Matrix model and MaxEntScan outperformed other methods. Two ensemble learning methods, adaptive boosting and random forests, were used to construct models that take advantage of individual methods. Both models further improved prediction, with outputs of directly interpretable prediction scores. We applied our ensemble scores to scSNVs from the Catalogue of Somatic Mutations in Cancer database. Analysis showed that predicted splice-altering scSNVs are enriched in recurrent scSNVs and known cancer genes. We pre-computed our ensemble scores for all potential scSNVs across the human genome, providing a whole genome level resource for identifying splice-altering scSNVs discovered from large-scale sequencing studies.
    MeSH term(s) Alternative Splicing ; Artificial Intelligence ; Computer Simulation ; Genes, Neoplasm ; Genetic Variation ; Genome, Human ; Genomics/methods ; Humans ; Position-Specific Scoring Matrices ; RNA Splice Sites
    Chemical Substances RNA Splice Sites
    Language English
    Publishing date 2014-11-22
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Validation Study
    ZDB-ID 186809-3
    ISSN 1362-4962 ; 1362-4954 ; 0301-5610 ; 0305-1048
    ISSN (online) 1362-4962 ; 1362-4954
    ISSN 0301-5610 ; 0305-1048
    DOI 10.1093/nar/gku1206
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  4. Article ; Online: dbNSFP v2.0: a database of human non-synonymous SNVs and their functional predictions and annotations.

    Liu, Xiaoming / Jian, Xueqiu / Boerwinkle, Eric

    Human mutation

    2013  Volume 34, Issue 9, Page(s) E2393–402

    Abstract: dbNSFP is a database developed for functional prediction and annotation of all potential non-synonymous single-nucleotide variants (nsSNVs) in the human genome. This database significantly facilitates the process of querying predictions and annotations ... ...

    Abstract dbNSFP is a database developed for functional prediction and annotation of all potential non-synonymous single-nucleotide variants (nsSNVs) in the human genome. This database significantly facilitates the process of querying predictions and annotations from different databases/web-servers for large amounts of nsSNVs discovered in exome-sequencing studies. Here we report a recent major update of the database to version 2.0. We have rebuilt the SNV collection based on GENCODE 9 and currently the database includes 87,347,043 nsSNVs and 2,270,742 essential splice site SNVs (an 18% increase compared to dbNSFP v1.0). For each nsSNV dbNSFP v2.0 has added two prediction scores (MutationAssessor and FATHMM) and two conservation scores (GERP++ and SiPhy). The original five prediction and conservation scores in v1.0 (SIFT, Polyphen2, LRT, MutationTaster and PhyloP) have been updated. Rich functional annotations for SNVs and genes have also been added into the new version, including allele frequencies observed in the 1000 Genomes Project phase 1 data and the NHLBI Exome Sequencing Project, various gene IDs from different databases, functional descriptions of genes, gene expression and gene interaction information, among others. dbNSFP v2.0 is freely available for download at http://sites.google.com/site/jpopgen/dbNSFP.
    MeSH term(s) Computational Biology ; Databases, Nucleic Acid ; Exome ; Gene Frequency ; Genome, Human ; Humans ; Molecular Sequence Annotation ; Polymorphism, Single Nucleotide ; Software
    Language English
    Publishing date 2013-07-10
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 1126646-6
    ISSN 1098-1004 ; 1059-7794
    ISSN (online) 1098-1004
    ISSN 1059-7794
    DOI 10.1002/humu.22376
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  5. Article ; Online: In silico tools for splicing defect prediction: a survey from the viewpoint of end users.

    Jian, Xueqiu / Boerwinkle, Eric / Liu, Xiaoming

    Genetics in medicine : official journal of the American College of Medical Genetics

    2013  Volume 16, Issue 7, Page(s) 497–503

    Abstract: RNA splicing is the process during which introns are excised and exons are spliced. The precise recognition of splicing signals is critical to this process, and mutations affecting splicing comprise a considerable proportion of genetic disease etiology. ... ...

    Abstract RNA splicing is the process during which introns are excised and exons are spliced. The precise recognition of splicing signals is critical to this process, and mutations affecting splicing comprise a considerable proportion of genetic disease etiology. Analysis of RNA samples from the patient is the most straightforward and reliable method to detect splicing defects. However, currently, the technical limitation prohibits its use in routine clinical practice. In silico tools that predict potential consequences of splicing mutations may be useful in daily diagnostic activities. In this review, we provide medical geneticists with some basic insights into some of the most popular in silico tools for splicing defect prediction, from the viewpoint of end users. Bioinformaticians in relevant areas who are working on huge data sets may also benefit from this review. Specifically, we focus on those tools whose primary goal is to predict the impact of mutations within the 5' and 3' splicing consensus regions: the algorithms used by different tools as well as their major advantages and disadvantages are briefly introduced; the formats of their input and output are summarized; and the interpretation, evaluation, and prospection are also discussed.
    MeSH term(s) Computational Biology/methods ; Computer Simulation ; Genetic Variation/genetics ; Humans ; RNA Precursors/genetics ; RNA Splicing/genetics ; Software
    Chemical Substances RNA Precursors
    Language English
    Publishing date 2013-11-21
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Review
    ZDB-ID 1455352-1
    ISSN 1530-0366 ; 1098-3600
    ISSN (online) 1530-0366
    ISSN 1098-3600
    DOI 10.1038/gim.2013.176
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  6. Article ; Online: A prospective study of serum metabolites and risk of ischemic stroke.

    Sun, Daokun / Tiedt, Steffen / Yu, Bing / Jian, Xueqiu / Gottesman, Rebecca F / Mosley, Thomas H / Boerwinkle, Eric / Dichgans, Martin / Fornage, Myriam

    Neurology

    2019  Volume 92, Issue 16, Page(s) e1890–e1898

    Abstract: Objective: To identify promising blood-based biomarkers and novel etiologic pathways of disease risk, we applied an untargeted serum metabolomics profiling in a community-based prospective study of ischemic stroke (IS).: Methods: In 3,904 men and ... ...

    Abstract Objective: To identify promising blood-based biomarkers and novel etiologic pathways of disease risk, we applied an untargeted serum metabolomics profiling in a community-based prospective study of ischemic stroke (IS).
    Methods: In 3,904 men and women from the Atherosclerosis Risk In Communities study, Cox proportional hazard models were used to estimate the association of incident IS with the standardized level of 245 fasting serum metabolites individually, adjusting for age, sex, race, field center, batch, diabetes, hypertension, current smoking status, body mass index, and estimated glomerular filtration rate. Validation of results was carried out in an independent sample of 114 IS cases and 112 healthy controls.
    Results: Serum levels of 2 long-chain dicarboxylic acids, tetradecanedioate and hexadecanedioate, were strongly correlated (
    Conclusion: Two serum long-chain dicarboxylic acids, metabolic products of ω-oxidation of fatty acids, were associated with IS and CES independently of known risk factors. Pathways related to intracellular hexadecanedioate synthesis or those involved in its clearance from the circulation may mediate IS risk. These results highlight the potential of metabolomics to discover novel circulating biomarkers for stroke and to unravel novel pathways for IS and its subtypes.
    MeSH term(s) Biomarkers/blood ; Brain Ischemia/blood ; Brain Ischemia/epidemiology ; Brain Ischemia/genetics ; Female ; Follow-Up Studies ; Genetic Association Studies ; Humans ; Incidence ; Male ; Metabolome ; Metabolomics ; Middle Aged ; Polymorphism, Single Nucleotide ; Prospective Studies ; Risk Factors ; Stroke/blood ; Stroke/epidemiology ; Stroke/genetics
    Chemical Substances Biomarkers
    Language English
    Publishing date 2019-03-13
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 207147-2
    ISSN 1526-632X ; 0028-3878
    ISSN (online) 1526-632X
    ISSN 0028-3878
    DOI 10.1212/WNL.0000000000007279
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  7. Article ; Online: dbNSFP: a lightweight database of human nonsynonymous SNPs and their functional predictions.

    Liu, Xiaoming / Jian, Xueqiu / Boerwinkle, Eric

    Human mutation

    2011  Volume 32, Issue 8, Page(s) 894–899

    Abstract: With the advance of sequencing technologies, whole exome sequencing has increasingly been used to identify mutations that cause human diseases, especially rare Mendelian diseases. Among the analysis steps, functional prediction (of being deleterious) ... ...

    Abstract With the advance of sequencing technologies, whole exome sequencing has increasingly been used to identify mutations that cause human diseases, especially rare Mendelian diseases. Among the analysis steps, functional prediction (of being deleterious) plays an important role in filtering or prioritizing nonsynonymous SNP (NS) for further analysis. Unfortunately, different prediction algorithms use different information and each has its own strength and weakness. It has been suggested that investigators should use predictions from multiple algorithms instead of relying on a single one. However, querying predictions from different databases/Web-servers for different algorithms is both tedious and time consuming, especially when dealing with a huge number of NSs identified by exome sequencing. To facilitate the process, we developed dbNSFP (database for nonsynonymous SNPs' functional predictions). It compiles prediction scores from four new and popular algorithms (SIFT, Polyphen2, LRT, and MutationTaster), along with a conservation score (PhyloP) and other related information, for every potential NS in the human genome (a total of 75,931,005). It is the first integrated database of functional predictions from multiple algorithms for the comprehensive collection of human NSs. dbNSFP is freely available for download at http://sites.google.com/site/jpopgen/dbNSFP.
    MeSH term(s) Algorithms ; Computational Biology ; Databases, Nucleic Acid ; Genetic Association Studies ; Humans ; Internet ; Polymorphism, Single Nucleotide/genetics ; Software
    Language English
    Publishing date 2011-06-07
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 1126646-6
    ISSN 1098-1004 ; 1059-7794
    ISSN (online) 1098-1004
    ISSN 1059-7794
    DOI 10.1002/humu.21517
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  8. Article ; Online: Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies.

    Dong, Chengliang / Wei, Peng / Jian, Xueqiu / Gibbs, Richard / Boerwinkle, Eric / Wang, Kai / Liu, Xiaoming

    Human molecular genetics

    2015  Volume 24, Issue 8, Page(s) 2125–2137

    Abstract: Accurate deleteriousness prediction for nonsynonymous variants is crucial for distinguishing pathogenic mutations from background polymorphisms in whole exome sequencing (WES) studies. Although many deleteriousness prediction methods have been developed, ...

    Abstract Accurate deleteriousness prediction for nonsynonymous variants is crucial for distinguishing pathogenic mutations from background polymorphisms in whole exome sequencing (WES) studies. Although many deleteriousness prediction methods have been developed, their prediction results are sometimes inconsistent with each other and their relative merits are still unclear in practical applications. To address these issues, we comprehensively evaluated the predictive performance of 18 current deleteriousness-scoring methods, including 11 function prediction scores (PolyPhen-2, SIFT, MutationTaster, Mutation Assessor, FATHMM, LRT, PANTHER, PhD-SNP, SNAP, SNPs&GO and MutPred), 3 conservation scores (GERP++, SiPhy and PhyloP) and 4 ensemble scores (CADD, PON-P, KGGSeq and CONDEL). We found that FATHMM and KGGSeq had the highest discriminative power among independent scores and ensemble scores, respectively. Moreover, to ensure unbiased performance evaluation of these prediction scores, we manually collected three distinct testing datasets, on which no current prediction scores were tuned. In addition, we developed two new ensemble scores that integrate nine independent scores and allele frequency. Our scores achieved the highest discriminative power compared with all the deleteriousness prediction scores tested and showed low false-positive prediction rate for benign yet rare nonsynonymous variants, which demonstrated the value of combining information from multiple orthologous approaches. Finally, to facilitate variant prioritization in WES studies, we have pre-computed our ensemble scores for 87 347 044 possible variants in the whole-exome and made them publicly available through the ANNOVAR software and the dbNSFP database.
    MeSH term(s) Computational Biology/instrumentation ; Computational Biology/methods ; Exome ; Genome, Human ; Humans ; Polymorphism, Single Nucleotide ; Software
    Language English
    Publishing date 2015-04-15
    Publishing country England
    Document type Comparative Study ; Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 1108742-0
    ISSN 1460-2083 ; 0964-6906
    ISSN (online) 1460-2083
    ISSN 0964-6906
    DOI 10.1093/hmg/ddu733
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  9. Article ; Online: Apolipoprotein E genotypes among diverse middle-aged and older Latinos: Study of Latinos-Investigation of Neurocognitive Aging results (HCHS/SOL).

    González, Hector M / Tarraf, Wassim / Jian, Xueqiu / Vásquez, Priscilla M / Kaplan, Robert / Thyagarajan, Bharat / Daviglus, Martha / Lamar, Melissa / Gallo, Linda C / Zeng, Donglin / Fornage, Myriam

    Scientific reports

    2018  Volume 8, Issue 1, Page(s) 17578

    Abstract: The apoE4 isoform is associated with increased cholesterol, cardiovascular risk, and Alzheimer's Disease risk, however, its distribution is not well-understood among US Latinos. Latinos living in the US are highly Amerindian, European and African admixed, ...

    Abstract The apoE4 isoform is associated with increased cholesterol, cardiovascular risk, and Alzheimer's Disease risk, however, its distribution is not well-understood among US Latinos. Latinos living in the US are highly Amerindian, European and African admixed, which varies by region and country of origin. However, Latino genetic diversity is understudied and consequently poorly understood, which has significant implications for understanding disease risk in nearly one-fifth of the US population. In this report we describe apoE distributions in a large and representative sample of diverse, genetically determined US Latinos.
    MeSH term(s) Adult ; Aged ; Alzheimer Disease/blood ; Alzheimer Disease/genetics ; Apolipoproteins E/blood ; Apolipoproteins E/genetics ; Cardiovascular Diseases/blood ; Cardiovascular Diseases/genetics ; Cholesterol/blood ; Cholesterol/genetics ; Female ; Genetic Variation ; Genotype ; Hispanic Americans/genetics ; Humans ; Male ; Middle Aged ; Risk Factors ; United States
    Chemical Substances ApoE protein, human ; Apolipoproteins E ; Cholesterol (97C5T2UQ7J)
    Language English
    Publishing date 2018-12-13
    Publishing country England
    Document type Clinical Trial ; Journal Article ; Multicenter Study ; Research Support, N.I.H., Extramural
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-018-35573-3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Functional annotation of genomic variants in studies of late-onset Alzheimer's disease.

    Butkiewicz, Mariusz / Blue, Elizabeth E / Leung, Yuk Yee / Jian, Xueqiu / Marcora, Edoardo / Renton, Alan E / Kuzma, Amanda / Wang, Li-San / Koboldt, Daniel C / Haines, Jonathan L / Bush, William S

    Bioinformatics (Oxford, England)

    2018  Volume 34, Issue 16, Page(s) 2724–2731

    Abstract: Motivation: Annotation of genomic variants is an increasingly important and complex part of the analysis of sequence-based genomic analyses. Computational predictions of variant function are routinely incorporated into gene-based analyses of rare- ... ...

    Abstract Motivation: Annotation of genomic variants is an increasingly important and complex part of the analysis of sequence-based genomic analyses. Computational predictions of variant function are routinely incorporated into gene-based analyses of rare-variants, though to date most studies use limited information for assessing variant function that is often agnostic of the disease being studied.
    Results: In this work, we outline an annotation process motivated by the Alzheimer's Disease Sequencing Project, illustrate the impact of including tissue-specific transcript sets and sources of gene regulatory information and assess the potential impact of changing genomic builds on the annotation process. While these factors only impact a small proportion of total variant annotations (∼5%), they influence the potential analysis of a large fraction of genes (∼25%).
    Availability and implementation: Individual variant annotations are available via the NIAGADS GenomicsDB, at https://www.niagads.org/genomics/ tools-and-software/databases/genomics-database. Annotations are also available for bulk download at https://www.niagads.org/datasets. Annotation processing software is available at http://www.icompbio.net/resources/software-and-downloads/.
    Supplementary information: Supplementary data are available at Bioinformatics online.
    MeSH term(s) Alzheimer Disease/genetics ; Databases, Genetic ; Genetic Predisposition to Disease ; Genome ; Genomics ; Humans ; Molecular Sequence Annotation/methods ; Polymorphism, Single Nucleotide ; Sequence Analysis, DNA/methods ; Software
    Language English
    Publishing date 2018-04-04
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 1422668-6
    ISSN 1367-4811 ; 1367-4803
    ISSN (online) 1367-4811
    ISSN 1367-4803
    DOI 10.1093/bioinformatics/bty177
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