Fast search of thousands of short-read sequencing experiments.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 26854477.
- Also identified by DOI 10.1038/nbt.3442 and PMC identifier 4804353.
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Abstract
The amount of sequence information in public repositories is growing at a rapid rate. Although these data are likely to contain clinically important information that has not yet been uncovered, our ability to effectively mine these repositories is limited. Here we introduce Sequence Bloom Trees (SBTs), a method for querying thousands of short-read sequencing experiments by sequence, 162 times faster than existing approaches. The approach searches large data archives for all experiments that involve a given sequence. We use SBTs to search 2,652 human blood, breast and brain RNA-seq experiments for all 214,293 known transcripts in under 4 days using less than 239 MB of RAM and a single CPU. Searching sequence archives at this scale and in this time frame is currently not possible using existing tools.
Medical subject headings
- Data Mining
- High-Throughput Nucleotide Sequencing
- RNA
- Sequence Analysis, RNA