{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T15:30:26Z","timestamp":1781796626414,"version":"3.54.5"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,7,29]],"date-time":"2020-07-29T00:00:00Z","timestamp":1595980800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,7,29]],"date-time":"2020-07-29T00:00:00Z","timestamp":1595980800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2020,12]]},"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n \n Research on the molecular ecology of non-model organisms, while previously constrained, has now been greatly facilitated by the advent of reduced-representation sequencing protocols. However, tools that allow these large datasets to be efficiently parsed are often lacking, or if indeed available, then limited by the necessity of a comparable reference genome as an adjunct. This, of course, can be difficult when working with non-model organisms. Fortunately, pipelines are currently available that avoid this prerequisite, thus allowing data to be a priori parsed. An oft-used molecular ecology program (i.e., S\n tructure<\/jats:sc>\n ), for example, is facilitated by such pipelines, yet they are surprisingly absent for a second program that is similarly popular and computationally more efficient (i.e., A\n dmixture<\/jats:sc>\n ). The two programs differ in that A\n dmixture<\/jats:sc>\n employs a maximum-likelihood framework whereas S\n tructure<\/jats:sc>\n uses a Bayesian approach, yet both produce similar results. Given these issues, there is an overriding (and recognized) need among researchers in molecular ecology for bioinformatic software that will not only condense output from replicated A\n dmixture<\/jats:sc>\n runs, but also infer from these data the optimal number of population clusters (\n K<\/jats:italic>\n ).\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Here we provide such a program (i.e., A\n dmix<\/jats:sc>\n P\n ipe<\/jats:sc>\n ) that (a) filters SNPs to allow the delineation of population structure in A\n dmixture<\/jats:sc>\n , then (b) parses the output for summarization and graphical representation via C\n lumpak<\/jats:sc>\n . Our benchmarks effectively demonstrate how efficient the pipeline is for processing large, non-model datasets generated via double digest restriction-site associated DNA sequencing (ddRAD). Outputs not only parallel those from S\n tructure<\/jats:sc>\n , but also visualize the variation among individual A\n dmixture<\/jats:sc>\n runs, so as to facilitate selection of the most appropriate\n K<\/jats:italic>\n -value.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n \n A\n dmix<\/jats:sc>\n P\n ipe<\/jats:sc>\n successfully integrates A\n dmixture<\/jats:sc>\n analysis with popular variant call format (VCF) filtering software to yield file types readily analyzed by C\n lumpak<\/jats:sc>\n . Large population genomic datasets derived from non-model organisms are efficiently analyzed via the parallel-processing capabilities of A\n dmixture<\/jats:sc>\n . A\n dmix<\/jats:sc>\n P\n ipe<\/jats:sc>\n is distributed under the GNU Public License and freely available for Mac OSX and Linux platforms at:\n https:\/\/github.com\/stevemussmann\/admixturePipeline<\/jats:ext-link>\n .\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1186\/s12859-020-03701-4","type":"journal-article","created":{"date-parts":[[2020,7,29]],"date-time":"2020-07-29T13:02:53Z","timestamp":1596027773000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["AdmixPipe: population analyses in Admixture for non-model organisms"],"prefix":"10.1186","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5237-5088","authenticated-orcid":false,"given":"Steven M.","family":"Mussmann","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marlis R.","family":"Douglas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tyler K.","family":"Chafin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael E.","family":"Douglas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,7,29]]},"reference":[{"key":"3701_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0037135","volume":"7","author":"BK Peterson","year":"2012","unstructured":"Peterson BK, Weber JN, Kay EH, Fisher HS, Hoekstra HE. 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