GAVIN: Gene-Aware Variant INterpretation for medical sequencing
暂无分享,去创建一个
Birgit Sikkema-Raddatz | Kristin M. Abbott | Alain Knopperts | Rolf H. Sijmons | Richard J. Sinke | Morris A. Swertz | Cisca Wijmenga | K. Joeri van der Velde | Eddy N. de Boer | Cleo C. van Diemen | Tom J. de Koning | Lude Franke | Joeri van der Velde | C. Wijmenga | M. Swertz | R. Sinke | L. Franke | K. J. van der Velde | K. Abbott | C. V. Diemen | R. Sijmons | C. V. van Diemen | T. Koning | B. Sikkema-Raddatz | T. D. de Koning | E. N. Boer | A. Knopperts | E. N. de Boer | B. Sikkema‐Raddatz
[1] Michael Krawczak,et al. Where genotype is not predictive of phenotype: towards an understanding of the molecular basis of reduced penetrance in human inherited disease , 2013, Human Genetics.
[2] Mauno Vihinen,et al. VariBench: A Benchmark Database for Variations , 2013, Human mutation.
[3] J. Shendure,et al. A general framework for estimating the relative pathogenicity of human genetic variants , 2014, Nature Genetics.
[4] Anh-Dao Nguyen,et al. Clinical Genomic Database , 2013, Proceedings of the National Academy of Sciences.
[5] W. Miller,et al. PhenCode: connecting ENCODE data with mutations and phenotype , 2007, Human mutation.
[6] P. Bork,et al. A method and server for predicting damaging missense mutations , 2010, Nature Methods.
[7] Xiaohui Xie,et al. DANN: a deep learning approach for annotating the pathogenicity of genetic variants , 2015, Bioinform..
[8] Ludovico Minati,et al. Slow Breathing and Hypoxic Challenge: Cardiorespiratory Consequences and Their Central Neural Substrates , 2015, PloS one.
[9] Lluis Quintana-Murci,et al. The mutation significance cutoff: gene-level thresholds for variant predictions , 2016, Nature Methods.
[10] J. Lupski,et al. Non-coding genetic variants in human disease. , 2015, Human molecular genetics.
[11] Jaroslav Bendl,et al. PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions , 2016, PLoS Comput. Biol..
[12] Sheena M. Scroggins,et al. CADD score has limited clinical validity for the identification of pathogenic variants in non-coding regions in a hereditary cancer panel , 2016, Genetics in Medicine.
[13] Jana Marie Schwarz,et al. MutationTaster2: mutation prediction for the deep-sequencing age , 2014, Nature Methods.
[14] James Y. Zou. Analysis of protein-coding genetic variation in 60,706 humans , 2015, Nature.
[15] C. Wijmenga,et al. Evaluation of CADD Scores in Curated Mismatch Repair Gene Variants Yields a Model for Clinical Validation and Prioritization , 2015, Human mutation.
[16] M. Vihinen,et al. Immunodeficiency mutation databases (IDbases). , 1998, Human mutation.
[17] Jean-Michel Claverie,et al. The human gene damage index as a gene-level approach to prioritizing exome variants , 2015, Proceedings of the National Academy of Sciences.
[18] J. Shendure,et al. Needles in stacks of needles: finding disease-causal variants in a wealth of genomic data , 2011, Nature Reviews Genetics.
[19] E. Nestler,et al. Chronic cocaine-regulated epigenomic changes in mouse nucleus accumbens , 2014, Genome Biology.
[20] S. Henikoff,et al. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm , 2009, Nature Protocols.
[21] Pieter B. T. Neerincx,et al. Supplementary Information Whole-genome sequence variation , population structure and demographic history of the Dutch population , 2022 .
[22] P. Stenson,et al. The Human Gene Mutation Database: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine , 2013, Human Genetics.
[23] A. Gonzalez-Perez,et al. Improving the assessment of the outcome of nonsynonymous SNVs with a consensus deleteriousness score, Condel. , 2011, American journal of human genetics.
[24] Colin Campbell,et al. An integrative approach to predicting the functional effects of non-coding and coding sequence variation , 2015, Bioinform..
[25] Muin J Khoury,et al. Deploying whole genome sequencing in clinical practice and public health: Meeting the challenge one bin at a time , 2011, Genetics in Medicine.
[26] Kevin Y. Yip,et al. FunSeq2: a framework for prioritizing noncoding regulatory variants in cancer , 2014, Genome Biology.
[27] Bale,et al. Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology , 2015, Genetics in Medicine.
[28] O. Troyanskaya,et al. Predicting effects of noncoding variants with deep learning–based sequence model , 2015, Nature Methods.
[29] M. Vihinen,et al. PON-P2: Prediction Method for Fast and Reliable Identification of Harmful Variants , 2015, PloS one.
[30] J. Miller,et al. Predicting the Functional Effect of Amino Acid Substitutions and Indels , 2012, PloS one.
[31] Peng Cui,et al. Dynamic regulation of genome-wide pre-mRNA splicing and stress tolerance by the Sm-like protein LSm5 in Arabidopsis , 2014, Genome Biology.
[32] Pablo Cingolani,et al. © 2012 Landes Bioscience. Do not distribute. , 2022 .
[33] Ricardo Villamarín-Salomón,et al. ClinVar: public archive of interpretations of clinically relevant variants , 2015, Nucleic Acids Res..
[34] J. Buxbaum,et al. A SPECTRAL APPROACH INTEGRATING FUNCTIONAL GENOMIC ANNOTATIONS FOR CODING AND NONCODING VARIANTS , 2015, Nature Genetics.
[35] S. Letovsky,et al. Exploring the landscape of pathogenic genetic variation in the ExAC population database: insights of relevance to variant classification , 2015, Genetics in Medicine.
[36] Gabor T. Marth,et al. A global reference for human genetic variation , 2015, Nature.
[37] Morris A. Swertz,et al. The MOLGENIS toolkit: rapid prototyping of biosoftware at the push of a button , 2010, BMC Bioinformatics.