Variation in genome-wide mutation rates within and between human families

By D. Conrad, Jonathan E. M. Keebler, Mark A. DePristo, S. Lindsay, Yujun Zhang, F. Casals, Youssef Idaghdour, C. Hartl, C. Torroja, K. Garimella and 7 more. Nature Genetics, 2011

604 citations recorded by the source corpus.

Subfields: Cancer Research, Genetics

View Paper: https://www.semanticscholar.org/paper/532811803b5067cf9a50db019a774fec9e23131f

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Citations in the corpus

Whole Genome Sequencing in Autism Identifies Hotspots for De Novo Germline Mutation (2012, positive): “MI was highly correlated with mutation rate variation in a genome-wide data set from two trios (Conrad et al., 2011) (Figure 4B) and exome data sets from four independent trio-based studies of autism (Iossifov et al.”
Toward better understanding of artifacts in variant calling from high-coverage samples (2014, background): “Because we expect to see only tens to hundreds of somatic mutations or Mendelian errors per Li genome (Conrad et al., 2011), most other inconsistencies are very likely to be errors.”
lobSTR: A short tandem repeat profiler for personal genomes (2012, background): “…any other type of known genetic variation and can reach 1/500 mutations per locus per generation (Walsh 2001; Ballantyne et al. 2010), 200-fold higher than the rate of spontaneous copy number variations (CNV) (Lupski 2007) and 200,000-fold higher than the rate of de novo SNPs (Conrad et al. 2011).”
A reference data set of 5.4 million phased human variants validated by genetic inheritance from sequencing a three-generation 17-member pedigree (2016, neutral): “For indels, Strelka and GATK3 have very similar recall and precision, whereas Platypus has the highest precision values at a cost of lower recall.”
Genome-Wide Detection of Single Nucleotide and Copy Number Variations of a Single Human Cell (2012, result): “The mutation rate of this cancer cell line is about 10 fold higher than the mutation rate estimated based on germ line studies (29-31).”
The Next-Generation Sequencing Revolution and Its Impact on Genomics (2013, neutral): “Familybased WGS studies have shown that each individual's genome harbors 74 germline de novo mutations (DNMs) (Conrad et al., 2011).”
Integrating mapping-, assembly- and haplotype-based approaches for calling variants in clinical sequencing applications (2014, methodology): “To assess Platypus’s sensitivity, we again analyzed data from the NA12878 trio obtained from immortalized cell lines and made use of a study by Conrad et al. that identified 49 germline and 952 cell line de novo mutations using an exhaustive calling strategy followed by comprehensive validation 35 .”
A framework for variation discovery and genotyping using next-generation DNA sequencing data (2011, background): “…searches for standing variation in common disease; mutations underlying linkages in Mendelian disease 3 ; as well as spontaneously arising variation for which no gene-mapping shortcuts are available (e.g., somatic mutations in cancer 4–6 and de novo mutations 7,8 in autism and schizophrenia).”
A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data (2011, background): “The biallele assumption does not have a big impact to the modeling of SNPs, though it may have a bigger impact to the modeling of INDELs at microsatellites.”