@article {peralta_sniploid:_2013,
	title = {SNiPloid: A Utility to Exploit High-Throughput SNP Data Derived from RNA-Seq in Allopolyploid Species},
	journal = {International Journal of Plant Genomics},
	volume = {2013},
	year = {2013},
	abstract = {High-throughput sequencing is a common approach to discover {SNP} variants, especially in plant species. However, methods to analyze predicted {SNPs} are often optimized for diploid plant species whereas many crop species are allopolyploids and combine related but divergent subgenomes (homoeologous chromosome sets). We created a software tool, {SNiPloid}, that exploits and interprets putative {SNPs} in the context of allopolyploidy by comparing {SNPs} from an allopolyploid with those obtained in its modern-day diploid progenitors. {SNiPloid} can compare {SNPs} obtained from a sample to estimate the subgenome contribution to the transcriptome or {SNPs} obtained from two polyploid accessions to search for {SNP} divergence.},
	issn = {1687-5370},
	doi = {10.1155/2013/890123},
	url = {http://www.hindawi.com/journals/ijpg/2013/890123/abs/},
	author = {Peralta, Marine and Combes, Marie-Christine and Cenci, Albero and Lashermes, Philippe and Dereeper, Alexis}
}
