{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T18:23:22Z","timestamp":1760984602042},"reference-count":6,"publisher":"Oxford University Press (OUP)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,2,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: The execution of a software application or pipeline using various combinations of parameters and inputs is a common task in bioinformatics. In the absence of a specialized tool to organize, streamline and formalize this process, scientists must write frequently complex scripts to perform these tasks. We present nestly, a Python package to facilitate running tools with nested combinations of parameters and inputs. nestly provides three components. First, a module to build nested directory structures corresponding to choices of parameters. Second, the nestrun script to run a given command using each set of parameter choices. Third, the nestagg script to aggregate results of the individual runs into a CSV file, as well as support for more complex aggregation. We also include a module for easily specifying nested dependencies for the SCons build tool, enabling incremental builds.<\/jats:p>\n               <jats:p>Availability: Source, documentation and tutorial examples are available at http:\/\/github.com\/fhcrc\/nestly. nestly can be installed from the Python Package Index via pip; it is open source (MIT license).<\/jats:p>\n               <jats:p>Contact: \u00a0cmccoy@fhcrc.org or matsen@fhcrc.org<\/jats:p>","DOI":"10.1093\/bioinformatics\/bts696","type":"journal-article","created":{"date-parts":[[2012,12,8]],"date-time":"2012-12-08T08:17:38Z","timestamp":1354954658000},"page":"387-388","source":"Crossref","is-referenced-by-count":6,"title":["nestly\u2014a framework for running software with nested parameter choices and aggregating results"],"prefix":"10.1093","volume":"29","author":[{"given":"Connor O.","family":"McCoy","sequence":"first","affiliation":[{"name":"1 Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA and 2Department of Laboratory Medicine, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aaron","family":"Gallagher","sequence":"additional","affiliation":[{"name":"1 Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA and 2Department of Laboratory Medicine, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Noah G.","family":"Hoffman","sequence":"additional","affiliation":[{"name":"1 Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA and 2Department of Laboratory Medicine, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Frederick A.","family":"Matsen","sequence":"additional","affiliation":[{"name":"1 Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA and 2Department of Laboratory Medicine, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2012,12,6]]},"reference":[{"key":"2023012810191425100_bts696-B1","doi-asserted-by":"crossref","first-page":"772","DOI":"10.1038\/nmeth.2109","article-title":"jModelTest 2: more models, new heuristics and parallel computing","volume":"9","author":"Darriba","year":"2012","journal-title":"Nat. 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