ECOGEMS: efficient compression and retrieve of SNP data of 2058 rice accessions with integer sparse matrices

Wen Yao; Fangfang Huang; Xuehai Zhang; Jihua Tang

doi:10.1093/bioinformatics/btz186

ECOGEMS: efficient compression and retrieve of SNP data of 2058 rice accessions with integer sparse matrices

Bioinformatics. 2019 Oct 15;35(20):4181-4183. doi: 10.1093/bioinformatics/btz186.

Authors

Wen Yao^{1

2}, Fangfang Huang^{1

2}, Xuehai Zhang^{2

3

4}, Jihua Tang^{2

3

4}

Affiliations

¹ College of Life Sciences, Henan Agricultural University, Zhengzhou, China.
² National Key Laboratory of Wheat and Maize Crop Science, Henan Agricultural University, Zhengzhou, China.
³ College of Agronomy, Henan Agricultural University, Zhengzhou, China.
⁴ Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou, China.

PMID: 30873546
DOI: 10.1093/bioinformatics/btz186

Abstract

Summary: We proposed to store large-scale genotype data as integer sparse matrices, which consumed much fewer computing resources for storage and analysis than traditional approaches. In addition, the raw genotype data could be readily recovered from integer sparse matrices. Utilizing this approach, we stored the genotype data of 1612 Asian cultivated rice accessions and 446 Asian wild rice accessions across 8 584 244 SNP sites in the ECOGEMS database with 310 MB of disk usage. Graphical interface for visualization, analysis and download of SNP data were implemented in ECOGEMS, which made it a valuable resource for rice functional genomic studies.

Availability and implementation: The code and data of ECOGEMS are freely available at https://github.com/venyao/ECOGEMS. ECOGEMS is deployed at http://ecogems.ncpgr.cn and http://150.109.59.144: 3838/ECOGEMS/ for online use.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Data Compression*
Genotype
Oryza*
Polymorphism, Single Nucleotide
Software