geck: trio-based comparative benchmarking of variant calls
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[1] J. Veltman,et al. De novo mutations in human genetic disease , 2012, Nature Reviews Genetics.
[2] Alexa B. R. McIntyre,et al. Extensive sequencing of seven human genomes to characterize benchmark reference materials , 2015, Scientific Data.
[3] Deniz Kural,et al. Comparing complex variants in family trios , 2018, bioRxiv.
[4] Jinliang Wang,et al. Sibship reconstruction from genetic data with typing errors. , 2004, Genetics.
[5] L. Jostins. Inferring genotyping error rates from genotyped trios , 2011, 1109.1462.
[6] H. Skaug,et al. Estimating genotyping error rates from parent–offspring dyads , 2013 .
[7] Michael Krawczak,et al. Family-Based Benchmarking of Copy Number Variation Detection Software , 2015, PloS one.
[8] Masao Nagasaki,et al. A statistical variant calling approach from pedigree information and local haplotyping with phase informative reads , 2013, Bioinform..
[9] G. McVean,et al. A reference data set of 5.4 million phased human variants validated by genetic inheritance from sequencing a three-generation 17-member pedigree , 2016, bioRxiv.
[10] Michael Boehnke,et al. Probability of detection of genotyping errors and mutations as inheritance inconsistencies in nuclear-family data. , 2002, American journal of human genetics.
[11] Dan Geiger,et al. Integration of SNP genotyping confidence scores in IBD inference , 2011, Bioinform..
[12] Brian L Browning,et al. Detecting identity by descent and estimating genotype error rates in sequence data. , 2013, American journal of human genetics.
[13] T. Spector,et al. Parametric model‐based statistics for possible genotyping errors and sample stratification in sibling‐pair SNP data , 2009, Genetic epidemiology.
[14] Ronald W. Davis,et al. Rare variant detection using family-based sequencing analysis , 2013, Proceedings of the National Academy of Sciences.
[15] M. DePristo,et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. , 2010, Genome research.
[16] Richard Durbin,et al. Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .
[17] Insuk Lee,et al. Systematic comparison of variant calling pipelines using gold standard personal exome variants , 2015, Scientific Reports.
[18] J. Zook,et al. Integrating human sequence data sets provides a resource of benchmark SNP and indel genotype calls , 2013, Nature Biotechnology.
[19] Cheng Li,et al. Estimation of genotype error rate using samples with pedigree information--an application on the GeneChip Mapping 10K array. , 2004, Genomics.
[20] Chittibabu Guda,et al. A Comparison of Variant Calling Pipelines Using Genome in a Bottle as a Reference , 2015, BioMed research international.
[21] Yun S. Song,et al. The Simons Genome Diversity Project: 300 genomes from 142 diverse populations , 2016, Nature.
[22] Jeanette C Papp,et al. Detection and integration of genotyping errors in statistical genetics. , 2002, American journal of human genetics.
[23] Sarah Sandmann,et al. Evaluating Variant Calling Tools for Non-Matched Next-Generation Sequencing Data , 2017, Scientific Reports.
[24] Li Fang,et al. Evaluation on Efficient Detection of Structural Variants at Low Coverage by Long-Read Sequencing , 2016 .
[25] Mauricio O. Carneiro,et al. From FastQ Data to High‐Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline , 2013, Current protocols in bioinformatics.
[26] Marc L. Salit,et al. Best practices for evaluating single nucleotide variant calling methods for microbial genomics , 2015, Front. Genet..
[27] J. Shendure,et al. Exome sequencing as a tool for Mendelian disease gene discovery , 2011, Nature Reviews Genetics.
[28] M. DePristo,et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data , 2011, Nature Genetics.
[29] F. Kronenberg,et al. American Journal of Epidemiology Practice of Epidemiology Estimating the Single Nucleotide Polymorphism Genotype Misclassification from Routine Double Measurements in a Large Epidemiologic Sample , 2022 .
[30] Andrea Califano,et al. Toward better benchmarking: challenge-based methods assessment in cancer genomics , 2014, Genome Biology.
[31] Heng Li,et al. Toward better understanding of artifacts in variant calling from high-coverage samples , 2014, Bioinform..
[32] Ryan L. Collins,et al. Multi-platform discovery of haplotype-resolved structural variation in human genomes , 2017, bioRxiv.
[33] Wei Chen,et al. Genotype calling and haplotyping in parent-offspring trios , 2013, Genome research.
[34] Andrew Carroll,et al. Inexpensive and Highly Reproducible Cloud-Based Variant Calling of 2,535 Human Genomes , 2015, PloS one.
[35] D. Haydon,et al. Maximum-Likelihood Estimation of Allelic Dropout and False Allele Error Rates From Microsatellite Genotypes in the Absence of Reference Data , 2007, Genetics.
[36] Wolfgang Losert,et al. svclassify: a method to establish benchmark structural variant calls , 2015, BMC Genomics.
[37] Tiago M. Fragoso,et al. Bayesian Model Averaging: A Systematic Review and Conceptual Classification , 2015, 1509.08864.
[38] G. N. Hannan,et al. Estimating genotyping error rates from Mendelian errors in SNP array genotypes and their impact on inference. , 2007, Genomics.
[39] Gabor T. Marth,et al. A global reference for human genetic variation , 2015, Nature.
[40] Yun S. Song,et al. SMaSH: a benchmarking toolkit for human genome variant calling , 2013, Bioinform..
[41] Heng Li,et al. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data , 2011, Bioinform..