{"corpus_id":251368982,"paper_sha":"7bb9645c6dd66da44d1f128b80b0c4f3f48e6657","doi":"10.1093/jhered/esac039","arxiv_id":null,"pmid":35932284,"pmcid":null,"mag_id":null,"dblp_id":null,"acl_id":null,"title":"MLNe: Simulating and Estimating Effective Size and Migration Rate from Temporal Changes in Allele Frequencies.","year":2022,"publication_date":"2022-08-06","venue":"Journal of Heredity","journal":{"name":"The Journal of heredity","pages":null,"volume":null},"journal_issn":null,"journal_title":null,"publication_types":["JournalArticle"],"pubmed_pub_types":["Journal Article"],"s2_fields_of_study":["Biology","Medicine"],"reference_count":0,"citation_count":5,"influential_citation_count":1,"is_open_access":true,"arxiv_categories":null,"arxiv_license":null,"arxiv_journal_ref":null,"mesh_headings":[{"d":"Humans","mj":false,"ui":"D006801"},{"d":"Genetic Markers","mj":false,"ui":"D005819"},{"d":"Population Density","mj":false,"ui":"D011156"},{"d":"Bayes Theorem","mj":false,"ui":"D001499"},{"d":"Gene Frequency","mj":false,"ui":"D005787"},{"d":"Software","mj":true,"ui":"D012984"}],"chemicals":[{"n":"Genetic Markers","ui":"D005819","reg":"0"}],"comments_corrections":null,"source_flags":5,"s2_open_access_pdf_url":"https://discovery.ucl.ac.uk/10155470/2/Wang_MLNe.pdf","s2_open_access_landing_url":"https://www.semanticscholar.org/paper/7bb9645c6dd66da44d1f128b80b0c4f3f48e6657","s2_open_access_license":"other-oa","s2_open_access_status":"GREEN","pmc_open_access_pdf_url":null,"pmc_open_access_landing_url":null,"pmc_open_access_license":null,"pmc_open_access_status":null,"unpaywall_open_access_pdf_url":null,"unpaywall_open_access_landing_url":null,"unpaywall_open_access_license":null,"unpaywall_open_access_status":null,"abstract":"In studies of molecular ecology, conservation biology and evolutionary biology, the current or recent effective size (Ne) of a population is frequently estimated from the marker genotype data of two or more temporally spaced samples of individuals taken from the population. Despite the developments of numerous Bayesian, likelihood and moment estimators, only a couple of them can use both temporally and spatially spaced samples of individuals to estimate jointly the effective size (Ne) of and the migration rate (m) into a population. In this note I describe new implementations of these joint estimators of Ne and m in software MLNe which runs on multiple platforms (Windows, Mac, Linux) with or without a graphical user interface (GUI), has an integrated simulation module to simulate genotype data for investigating the impacts of various factors (such as sample size and sampling interval) on estimation precision and accuracy, exploits both Message Passing Interface (MPI) and openMP for parallel computations using multiple cores and nodes to speed up analysis. The program does not require data pre-processing and accepts multiple formats of a file of original genotype data and a file of parameters as input. The GUI facilitates data and parameter inputs and produces publication-quality output graphs, while the non-GUI version of software is convenient for batch analysis of multiple datasets as in simulations. MLNe will help advance the analysis of temporal genetic marker data for estimating Ne of and m between populations, which are important parameters that will help biologists for the conservation management of natural and managed populations. MLNe can be downloaded free from the website http://www.zsl.org/science/research/software/.","claims":[{"public_id":"cl_62e31dbd176b0700f6849688cf12e08b","status":"active","text":"A non-GUI version supports batch analysis of multiple datasets, especially for simulation workflows.","confidence":0.9,"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/claims/cl_62e31dbd176b0700f6849688cf12e08b"},{"public_id":"cl_3d15e3bd4d9e36e8484aaef73d32e9b6","status":"active","text":"MLNe implements joint estimators for effective population size and migration rate from temporally and spatially spaced genetic samples.","confidence":0.98,"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous 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