IGD: high-performance search for large-scale genomic interval datasets
Author(s) -
Jianglin Feng,
Nathan C. Sheffield
Publication year - 2020
Publication title -
bioinformatics
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btaa1062
Subject(s) - immunoglobulin d , scale (ratio) , interval (graph theory) , computer science , computational biology , biology , genetics , mathematics , antibody , combinatorics , cartography , geography , b cell
Databases of large-scale genome projects now contain thousands of genomic interval datasets. These data are a critical resource for understanding the function of DNA. However, our ability to examine and integrate interval data of this scale is limited. Here, we introduce the integrated genome database (IGD), a method and tool for searching genome interval datasets more than three orders of magnitude faster than existing approaches, while using only one hundredth of the memory. IGD uses a novel linear binning method that allows us to scale analysis to billions of genomic regions.
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