Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB.
Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB.
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DOI：
10.1093/nar/gky1084
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发表时间：
2019-01-08
影响因子：
14.9
通讯作者：
Reecy JM
中科院分区：
文献类型：
--
作者：
Hu ZL;Park CA;Reecy JM
生物数据库的成功开发需要适应来自高通量基因组学管道的大量数据。随着Animal QTLdb（https：//www.animalgenome.org/QTLdb）中的策展数据量呈指数级增长，必须通过快速的基础设施开发来应对由此产生的挑战，以有效地适应丰富的数据策展并使元数据分析更加强大。动物QTLdb和CorrDB在过去15年的发展为研究人员利用丰富的表型/基因型数据来研究家畜性状的遗传结构提供了有价值的工具。我们专注于数据策展，提高数据质量维护，新工具开发和数据库联合开发，为用户提供方便的数据查询和分析平台。该数据库目前有158 499个QTL/协会，10 482个相关和1977个遗传力数据，平均每年增加32%的数据。此外，自上次报告以来，我们已经进行了超过14项功能改进或新工具的实施。我们数据库开发的最终目标是为数据收集，管理和注释提供基础设施，更重要的是，支持创新的数据结构，用于新类型的数据挖掘，数据再分析和网络遗传分析，从而产生新知识。
Successful development of biological databases requires accommodation of the burgeoning amounts of data from high-throughput genomics pipelines. As the volume of curated data in Animal QTLdb (https://www.animalgenome.org/QTLdb) increases exponentially, the resulting challenges must be met with rapid infrastructure development to effectively accommodate abundant data curation and make metadata analysis more powerful. The development of Animal QTLdb and CorrDB for the past 15 years has provided valuable tools for researchers to utilize a wealth of phenotype/genotype data to study the genetic architecture of livestock traits. We have focused our efforts on data curation, improved data quality maintenance, new tool developments, and database co-developments, in order to provide convenient platforms for users to query and analyze data. The database currently has 158 499 QTL/associations, 10 482 correlations and 1977 heritability data as a result of an average 32% data increase per year. In addition, we have made >14 functional improvements or new tool implementations since our last report. Our ultimate goals of database development are to provide infrastructure for data collection, curation, and annotation, and more importantly, to support innovated data structure for new types of data mining, data reanalysis, and networked genetic analysis that lead to the generation of new knowledge.
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影响因子：
12.3
作者：
Andersson L;Archibald AL;Bottema CD;Brauning R;Burgess SC;Burt DW;Casas E;Cheng HH;Clarke L;Couldrey C;Dalrymple BP;Elsik CG;Foissac S;Giuffra E;Groenen MA;Hayes BJ;Huang LS;Khatib H;Kijas JW;Kim H;Lunney JK;McCarthy FM;McEwan JC;Moore S;Nanduri B;Notredame C;Palti Y;Plastow GS;Reecy JM;Rohrer GA;Sarropoulou E;Schmidt CJ;Silverstein J;Tellam RL;Tixier-Boichard M;Tosser-Klopp G;Tuggle CK;Vilkki J;White SN;Zhao S;Zhou H;FAANG Consortium
通讯作者：
FAANG Consortium
影响因子：
16.6
作者：
Berthelot, Camille;Brunet, Frederic;Chalopin, Domitille;Juanchich, Amelie;Bernard, Maria;Noel, Benjamin;Bento, Pascal;Da Silva, Corinne;Labadie, Karine;Alberti, Adriana;Aury, Jean-Marc;Louis, Alexandra;Dehais, Patrice;Bardou, Philippe;Montfort, Jerome;Klopp, Christophe;Cabau, Cedric;Gaspin, Christine;Thorgaard, Gary H.;Boussaha, Mekki;Quillet, Edwige;Guyomard, Rene;Galiana, Delphine;Bobe, Julien;Volff, Jean-Nicolas;Genet, Carine;Wincker, Patrick;Jaillon, Olivier;Roest Crollius, Hugues;Guiguen, Yann
通讯作者：
Guiguen, Yann
DOI：
10.1126/science.1252806
发表时间：
2014-06-06
期刊：
Science (New York, N.Y.)
影响因子：
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作者：
Jiang Y;Xie M;Chen W;Talbot R;Maddox JF;Faraut T;Wu C;Muzny DM;Li Y;Zhang W;Stanton JA;Brauning R;Barris WC;Hourlier T;Aken BL;Searle SMJ;Adelson DL;Bian C;Cam GR;Chen Y;Cheng S;DeSilva U;Dixen K;Dong Y;Fan G;Franklin IR;Fu S;Guan R;Highland MA;Holder ME;Huang G;Ingham AB;Jhangiani SN;Kalra D;Kovar CL;Lee SL;Liu W;Liu X;Lu C;Lv T;Mathew T;McWilliam S;Menzies M;Pan S;Robelin D;Servin B;Townley D;Wang W;Wei B;White SN;Yang X;Ye C;Yue Y;Zeng P;Zhou Q;Hansen JB;Kristensen K;Gibbs RA;Flicek P;Warkup CC;Jones HE;Oddy VH;Nicholas FW;McEwan JC;Kijas J;Wang J;Worley KC;Archibald AL;Cockett N;Xu X;Wang W;Dalrymple BP
通讯作者：
Dalrymple BP
影响因子：
64.8
作者：
通讯作者：
--
DOI：
10.5713/ajas.14.0715
发表时间：
2015-10
期刊：
Asian-Australasian journal of animal sciences
影响因子：
--
作者：
Sharma A;Lee JS;Dang CG;Sudrajad P;Kim HC;Yeon SH;Kang HS;Lee SH
通讯作者：
Lee SH