From FastQ Data to High‐Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline

Auwera, Géraldine A. Van der; Carneiro, Mauricio O.; Hartl, Christopher; Poplin, Ryan; Angel, Guillermo del; Levy‐Moonshine, Ami; Jordan, Tadeusz; Shakir, Khalid; Roazen, David; Thibault, Joel; Banks, Eric; Garimella, Kiran; Altshuler, David; Gabriel, Stacey; DePristo, Mark A.

doi:10.1002/0471250953.bi1110s43

Cited by 5,119 publications

(2,973 citation statements)

References 13 publications

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“…(2017), single nucleotide polymorphisms (SNPs) were identified in the nuclear genome using three different variant callers: SAMTOOLS 1.1 (Li, 2011), FREEBAYES 0.9.15 (Garrison & Marth, 2012), and GATK 3.1 (DePristo et al., 2011; McKenna et al., 2010; Van der Auwera et al., 2013). A SNP set referred to as “consensus SNPs” hereafter was obtained from the overlap between callers, removing SNPs with a quality score below 50 and SNPs with mapping quality below 30.…”

Section: Methodsmentioning

confidence: 99%

Population genomics of the eastern cottonwood (Populus deltoides)

Fahrenkrog

Neves

Resende

et al. 2017

Ecology and Evolution

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Despite its economic importance as a bioenergy crop and key role in riparian ecosystems, little is known about genetic diversity and adaptation of the eastern cottonwood (Populus deltoides). Here, we report the first population genomics study for this species, conducted on a sample of 425 unrelated individuals collected in 13 states of the southeastern United States. The trees were genotyped by targeted resequencing of 18,153 genes and 23,835 intergenic regions, followed by the identification of single nucleotide polymorphisms (SNPs). This natural P. deltoides population showed low levels of subpopulation differentiation (F ST = 0.022–0.106), high genetic diversity (θW = 0.00100, π = 0.00170), a large effective population size (N e ≈ 32,900), and low to moderate levels of linkage disequilibrium. Additionally, genomewide scans for selection (Tajima's D), subpopulation differentiation (XTX), and environmental association analyses with eleven climate variables carried out with two different methods (LFMM and BAYENV2) identified genes putatively involved in local adaptation. Interestingly, many of these genes were also identified as adaptation candidates in another poplar species, Populus trichocarpa, indicating possible convergent evolution. This study constitutes the first assessment of genetic diversity and local adaptation in P. deltoides throughout the southern part of its range, information we expect to be of use to guide management and breeding strategies for this species in future, especially in the face of climate change.

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Section: Methodsmentioning

confidence: 99%

Population genomics of the eastern cottonwood (Populus deltoides)

Fahrenkrog

Neves

Resende

et al. 2017

Ecology and Evolution

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“…Due to the long reads, high error rates and continuously evolving error profile of the MinION basecalls at this early stage of technology roll out, variant callers such as the Genome Analysis Toolkit’s UnifiedGenotyper or HaplotypeCaller 13 were unable to identify variants or haplotypes in the MinION sequence data during our trials. Variant and haplotype level information, however, was readily accessible based on coverage of aligned reads, which we extracted using SAMTools via the Pysam wrapper ( http://github.com/pysam-developers/pysam) 14 .…”

Section: Methodsmentioning

confidence: 99%

Long read nanopore sequencing for detection of HLA and CYP2D6 variants and haplotypes

Ammar¹,

Paton²,

Torti³

et al. 2015

F1000Res

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Haplotypes are often critical for the interpretation of genetic laboratory observations into medically actionable findings. Current massively parallel DNA sequencing technologies produce short sequence reads that are often unable to resolve haplotype information. Phasing short read data typically requires supplemental statistical phasing based on known haplotype structure in the population or parental genotypic data. Here we demonstrate that the MinION nanopore sequencer is capable of producing very long reads to resolve both variants and haplotypes of HLA-A, HLA-B and CYP2D6 genes important in determining patient drug response in sample NA12878 of CEPH/UTAH pedigree 1463, without the need for statistical phasing. Long read data from a single 24-hour nanopore sequencing run was used to reconstruct haplotypes, which were confirmed by HapMap data and statistically phased Complete Genomics and Sequenom genotypes. Our results demonstrate that nanopore sequencing is an emerging standalone technology with potential utility in a clinical environment to aid in medical decision-making.

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“…This choice will determine the appropriate type of assembly program to use (e.g., GATK: McKenna et al., 2010; dePristo et al., 2011; Van der Auwera et al., 2013 with a reference genome; Stacks: Catchen, Amores, Hohenlohe, Cresko, & Postlethwait, 2011; Catchen, Hohenlohe, Bassham, Amores, & Cresko, 2013; Paris, Stevens, & Catchen, 2017; or dDocent: Puritz, Hollenbeck, & Gold, 2014 for a de novo assembly). Using a high‐quality and well‐annotated reference genome facilitates the identification of candidate genes and gene regions and allows for a truly genomic approach (e.g., considering physical linkage between regions with adaptive variation; Manel et al., 2016).…”

Section: Design and Implement: Assessmentmentioning

confidence: 99%

“…A major decision that will determine which loci are included in the dataset is choosing the parameters determining how closely the sequences must match (either match the reference sequence or match other sequences in de novo approaches; Catchen et al., 2011; McKenna et al., 2010; dePristo et al., 2011; Van der Auwera et al., 2013) and how often the sequences occur in individuals (i.e., coverage). If the sensitivity of these parameters is too low, sequences will be combined that are not from the same genomic region (i.e., paralogs; McKinney, Waples, Seeb, & Seeb, 2017).…”

Section: Design and Implement: Assessmentmentioning

confidence: 99%

“…Genotype‐calling software programs use either maximum‐likelihood (e.g., Stacks; Catchen et al., 2011) or Bayesian models (e.g., GATK; McKenna et al., 2010; dePristo et al., 2011; Van der Auwera et al., 2013) to assign individuals with genotypes. These models often incorporate some element of sequencing error, but the primary determinant of whether individuals are accurately genotyped as heterozygous or homozygous is the number of reads assigned to each individual.…”

Section: Design and Implement: Assessmentmentioning

confidence: 99%

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Guidelines for planning genomic assessment and monitoring of locally adaptive variation to inform species conservation

Flanagan

Forester

Latch

et al. 2017

Evolutionary Applications

209

189

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Identifying and monitoring locally adaptive genetic variation can have direct utility for conserving species at risk, especially when management may include actions such as translocations for restoration, genetic rescue, or assisted gene flow. However, genomic studies of local adaptation require careful planning to be successful, and in some cases may not be a worthwhile use of resources. Here, we offer an adaptive management framework to help conservation biologists and managers decide when genomics is likely to be effective in detecting local adaptation, and how to plan assessment and monitoring of adaptive variation to address conservation objectives. Studies of adaptive variation using genomic tools will inform conservation actions in many cases, including applications such as assisted gene flow and identifying conservation units. In others, assessing genetic diversity, inbreeding, and demographics using selectively neutral genetic markers may be most useful. And in some cases, local adaptation may be assessed more efficiently using alternative approaches such as common garden experiments. Here, we identify key considerations of genomics studies of locally adaptive variation, provide a road map for successful collaborations with genomics experts including key issues for study design and data analysis, and offer guidelines for interpreting and using results from genomic assessments to inform monitoring programs and conservation actions.

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From FastQ Data to High‐Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline

Cited by 5,119 publications

References 13 publications

Population genomics of the eastern cottonwood (Populus deltoides)

Population genomics of the eastern cottonwood (Populus deltoides)

Long read nanopore sequencing for detection of HLA and CYP2D6 variants and haplotypes

Guidelines for planning genomic assessment and monitoring of locally adaptive variation to inform species conservation

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