Laiyi Fu, Yanxin Xie, Shunkang Ling, Ying Wang, Binzhong Wang, Hejun Du, Qinke Peng, Hequan Sun
{"title":"findGSEP: estimating genome size of polyploid species using k-mer frequencies.","authors":"Laiyi Fu, Yanxin Xie, Shunkang Ling, Ying Wang, Binzhong Wang, Hejun Du, Qinke Peng, Hequan Sun","doi":"10.1093/bioinformatics/btae647","DOIUrl":null,"url":null,"abstract":"<p><strong>Summary: </strong>Estimating genome size using k-mer frequencies, which plays a fundamental role in designing genome sequencing and analysis projects, has remained challenging for polyploid species, i.e., ploidy p > 2. To address this, we introduce \"findGSEP,\" which is designed based on iterative curve fitting of k-mer frequencies. Precisely, it first disentangles up to p normal distributions by analyzing k-mer frequencies in whole genome sequencing of the focal species. Second, it computes the sizes of genomic regions related to 1∼p (homologous) chromosome(s) using each respective curve fitting, from which it infers the full polyploid and average haploid genome size. \"findGSEP\" can handle any level of ploidy p, and infer more accurate genome size than other well-known tools, as shown by tests using simulated and real genomic sequencing data of various species including octoploids.</p><p><strong>Availability and implementation: </strong>\"findGSEP\" was implemented as a web server, which is freely available at http://146.56.237.198:3838/findGSEP/. Also, \"findGSEP\" was implemented as an R package for parallel processing of multiple samples. Source code and tutorial on its installation and usage is available at https://github.com/sperfu/findGSEP.</p>","PeriodicalId":93899,"journal":{"name":"Bioinformatics (Oxford, England)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11552620/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics (Oxford, England)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioinformatics/btae647","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Summary: Estimating genome size using k-mer frequencies, which plays a fundamental role in designing genome sequencing and analysis projects, has remained challenging for polyploid species, i.e., ploidy p > 2. To address this, we introduce "findGSEP," which is designed based on iterative curve fitting of k-mer frequencies. Precisely, it first disentangles up to p normal distributions by analyzing k-mer frequencies in whole genome sequencing of the focal species. Second, it computes the sizes of genomic regions related to 1∼p (homologous) chromosome(s) using each respective curve fitting, from which it infers the full polyploid and average haploid genome size. "findGSEP" can handle any level of ploidy p, and infer more accurate genome size than other well-known tools, as shown by tests using simulated and real genomic sequencing data of various species including octoploids.
Availability and implementation: "findGSEP" was implemented as a web server, which is freely available at http://146.56.237.198:3838/findGSEP/. Also, "findGSEP" was implemented as an R package for parallel processing of multiple samples. Source code and tutorial on its installation and usage is available at https://github.com/sperfu/findGSEP.