Beran Pavel, Stehlíková Dagmar, Cohen Stephen P, Čurn Vladislav
Department of Genetics and Agricultural Biotechnology, Biotechnological Centre, University of South Bohemia, Faculty of Agriculture, 37005 České Budějovice, Czech Republic.
Department of Plant Pathology, The Ohio State University, Columbus, OH 43210, USA.
Bioinformatics. 2021 Oct 11;37(19):3349-3350. doi: 10.1093/bioinformatics/btab196.
Searching for amino acid or nucleic acid sequences unique to one organism may be challenging depending on size of the available datasets. K-mer elimination by cross-reference (KEC) allows users to quickly and easily find unique sequences by providing target and non-target sequences. Due to its speed, it can be used for datasets of genomic size and can be run on desktop or laptop computers with modest specifications.
KEC is freely available for non-commercial purposes. Source code and executable binary files compiled for Linux, Mac and Windows can be downloaded from https://github.com/berybox/KEC.
Supplementary data are available at Bioinformatics online.
根据可用数据集的大小，寻找某一生物体特有的氨基酸或核酸序列可能具有挑战性。通过交叉引用进行k-mer消除（KEC）允许用户通过提供目标序列和非目标序列来快速轻松地找到独特序列。由于其速度快，它可用于基因组大小的数据集，并且可以在规格适中的台式机或笔记本电脑上运行。
KEC可免费用于非商业目的。可从https://github.com/berybox/KEC下载为Linux、Mac和Windows编译的源代码和可执行二进制文件。
补充数据可在《生物信息学》在线获取。
