KmerKeys: a web resource for searching indexed genome assemblies and variants.
KmerKeys: a web resource for searching indexed genome assemblies and variants.
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DOI：
10.1093/nar/gkac266
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发表时间：
2022-07-05
影响因子：
14.9
通讯作者：
Ji, Hanlee P.
中科院分区：
文献类型：
--
作者：
Pavlichin, Dmitri S.;Lee, HoJoon;Greer, Stephanie U.;Grimes, Susan M.;Weissman, Tsachy;Ji, Hanlee P.
K - 聚体是用于基因组序列分析的短DNA序列。使用K - 聚体的应用包括基因组组装和比对。然而，这些短序列在更广泛的生物信息学应用中面临着与基因组序列数据的大规模相关的挑战。单个人类基因组组装包含数十亿个K - 聚体。因此，分析K - 聚体信息的计算需求是巨大的，特别是在涉及完整的基因组组装时。为了解决这些问题，我们开发了一种基于哈希表的新型索引数据结构，该哈希表针对短序列键的查找进行了优化。这个网络应用程序，称为KmerKeys，为基因组组装的云计算提供了高效、快速的查询速度。我们能够对组装进行模糊以及精确的序列搜索。为了实现稳健和快速的性能，该网站实现了对缓存友好的哈希表、内存映射和大规模并行处理。我们的方法采用了一种可扩展且高效的数据结构，可用于联合索引和搜索大量的人类基因组组装信息。人们可以包括变异数据库及其相关的元数据，例如gnomAD群体变异目录。这一特性使得未来的基因组信息能够融入测序分析中。KmerKeys可在https://kmerkeys.dgi - stanford.org免费访问。
K-mers are short DNA sequences that are used for genome sequence analysis. Applications that use k-mers include genome assembly and alignment. However, the wider bioinformatic use of these short sequences has challenges related to the massive scale of genomic sequence data. A single human genome assembly has billions of k-mers. As a result, the computational requirements for analyzing k-mer information is enormous, particularly when involving complete genome assemblies. To address these issues, we developed a new indexing data structure based on a hash table tuned for the lookup of short sequence keys. This web application, referred to as KmerKeys, provides performant, rapid query speeds for cloud computation on genome assemblies. We enable fuzzy as well as exact sequence searches of assemblies. To enable robust and speedy performance, the website implements cache-friendly hash tables, memory mapping and massive parallel processing. Our method employs a scalable and efficient data structure that can be used to jointly index and search a large collection of human genome assembly information. One can include variant databases and their associated metadata such as the gnomAD population variant catalogue. This feature enables the incorporation of future genomic information into sequencing analysis. KmerKeys is freely accessible at https://kmerkeys.dgi-stanford.org.
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影响因子：
30.8
作者：
Sherman RM;Forman J;Antonescu V;Puiu D;Daya M;Rafaels N;Boorgula MP;Chavan S;Vergara C;Ortega VE;Levin AM;Eng C;Yazdanbakhsh M;Wilson JG;Marrugo J;Lange LA;Williams LK;Watson H;Ware LB;Olopade CO;Olopade O;Oliveira RR;Ober C;Nicolae DL;Meyers DA;Mayorga A;Knight-Madden J;Hartert T;Hansel NN;Foreman MG;Ford JG;Faruque MU;Dunston GM;Caraballo L;Burchard EG;Bleecker ER;Araujo MI;Herrera-Paz EF;Campbell M;Foster C;Taub MA;Beaty TH;Ruczinski I;Mathias RA;Barnes KC;Salzberg SL
通讯作者：
Salzberg SL
影响因子：
5.8
作者：
Deorowicz, Sebastian;Gudys, Adam;Danek, Agnieszka
通讯作者：
Danek, Agnieszka
影响因子：
7
作者：
Schneider, Valerie A.;Graves-Lindsay, Tina;Church, Deanna M.
通讯作者：
Church, Deanna M.
影响因子：
5.8
作者：
Kokot, Marek;Dlugosz, Maciej;Deorowicz, Sebastian
通讯作者：
Deorowicz, Sebastian
影响因子：
64.8
作者：
Karczewski, Konrad J;Francioli, Laurent C;MacArthur, Daniel G
通讯作者：
MacArthur, Daniel G