Stacks: Building and Genotyping Loci De Novo From Short-Read Sequences

By Julian Catchen, A. Amores, Paul A Hohenlohe, W. Cresko, J. Postlethwait. G3: Genes, Genomes, Genetics, 2011

1,963 citations recorded by the source corpus.

Advances in sequencing technology provide special opportunities for genotyping individuals with speed and thrift, but the lack of software to automate the calling of tens of thousands of genotypes over hundreds of individuals has hindered progress. Stacks is a software system that uses short-read sequence data to identify and genotype loci in a set of individuals either de novo or by comparison to a reference genome. From reduced representation Illumina sequence data, such as RAD-tags, Stacks can recover thousands of single nucleotide polymorphism (SNP) markers useful for the genetic analysis of crosses or populations. Stacks can generate markers for ultra-dense genetic linkage maps, facilitate the examination of population phylogeography, and help in reference genome assembly. We report here the algorithms implemented in Stacks and demonstrate their efficacy by constructing loci from simulated RAD-tags taken from the stickleback reference genome and by recapitulating and improving a genetic map of the zebrafish, Danio rerio.

Subfields: Genetics, Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/98ecd711900e8f1be039bbb02bea928512ca5562

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Citations in the corpus

Stacks: an analysis tool set for population genomics (2013, methodology): “Furthermore, paired-end sequencing of sheared RAD tags with sufﬁcient depth allows one to produce longer haplotypes from the randomly sequenced paired ends (Catchen et al. 2011; Etter et al. 2011a), allowing for the possibility of long (500 bp) haplotypes being inferred.”
Species Delimitation using Genome-Wide SNP Data (2013, methodology): “We processed the filtered data using STACKS (Catchen et al. 2011), a group of programs and scripts that perform additional filtering based on sequence quality and identifies putative loci and haplotypes for each individual, and organizes them into a MySQL database.”
High-throughput linkage mapping of Australian white cypress pine (Callitris glaucophylla) and map transferability to related species (2015, methodology): “The ref_map.pl pipeline in Stacks 1.08 was used to build RAD loci, and the SNP genotype for each individual was exported with a minimum read depth of 8, using the " populations " program (Catchen et al. 2011).”
Restriction site‐associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference (2015, methodology): “…assembly and genotyping tools for RADseq data have recently been released, such as RaPiD (Willing et al. 2011), RADtools (Baxter et al. 2011), graph-based distance clustering approaches (Peterson et al. 2012), Stacks (Catchen et al. 2011, 2013), Rain-bow (Chong et al. 2012) and pyRAD (Eaton 2014).”
High-Throughput SNP Genotyping to Accelerate Crop Improvement (2014, methodology): “For example, the Stacks software package was developed to analyze and call SNPs from sequenced RAD-tags, whether de novo or by comparison to a reference genome (Catchen et al. 2011).”
The genome of the pear (Pyrus bretschneideri Rehd.) (2013, methodology): “The SNP calling algorithm was done using a Stacks package (Catchen et al. 2011) with default parameters.”
Special features of RAD Sequencing data: implications for genotyping (2012, methodology): “…2011; Chutimanitsakun et al. 2011; Baxter et al. 2011), phylogenetics and phylogeography (Rubin et al. 2012; Nadeau et al. 2012, Emerson et al. 2010), genome scaffolding (Catchen et al. 2011; He-liconius Genome Consortium 2012) and population genetics (Andersen et al. 2012; Hohenlohe et al. 2012).”
PyRAD: assembly of de novo RADseq loci for phylogenetic analyses (2013, methodology): “Few software are currently available to assemble RADseq data (Chong et al. , 2012; Pe-terson et al. , 2012), the most commonly used of which is Stacks (Catchen et al. , 2011, 2013).”
Lost in parameter space: a road map for stacks (2017, methodology): “The first stage in the assembly of loci de novo (Catchen et al. 2011) is to collapse identical raw reads into STACKS and consider them putative alleles.”
Genomic approaches to understanding population divergence and speciation in birds (2015, background): “Special care must be taken to collect and store samples in a way that preserves RNA (see Cheviron et al. 2011), a procedure that is not routine in most field or avian-museumcollection protocols (but see Balakrishnan et al. 2014).”
Double Digest RADseq: An Inexpensive Method for De Novo SNP Discovery and Genotyping in Model and Non-Model Species (2012, positive): “While the Stacks package is a complete and robust solution tailored to de novo analysis of random shearing RADseq data, we were motivated to develop our own implementation for four principle reasons.”
Stacks 2: Analytical Methods for Paired-end Sequencing Improve RADseq-based Population Genomics (2019, methodology): “The de novo approach found fewer SNPs, particularly in the forward read region, probably because low‐coverage alleles may be classified as errors and missed during locus clustering (see Catchen et al., 2011 for de‐ tails).”