SeqOthello: querying RNA-seq experiments at scale

We present SeqOthello, an ultra-fast and memory-efficient indexing structure to support arbitrary sequence query against large collections of RNA-seq experiments. It takes SeqOthello only 5 min and 19.1 GB memory to conduct a global survey of 11,658 fusion events against 10,113 TCGA Pan-Cancer RNA-s...

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Bibliographic Details
Published in:Genome Biology 2018-10, Vol.19 (1), p.167-167, Article 167
Main Authors: Yu, Ye, Liu, Jinpeng, Liu, Xinan, Zhang, Yi, Magner, Eamonn, Lehnert, Erik, Qian, Chen, Liu, Jinze
Format: Article
Language:English
Subjects:
Algorithms
Base Sequence
Bioinformatics
Cancer
Collections
Compression
Data analysis
Data collection
Data compression
Datasets
Experiments
Fusion protein
Gene Fusion
Genes
genetic databases
genome
Genomes
Genomics
Humans
Memory
Method
Neoplasms - genetics
Nucleotide sequence
Pan-cancer
Query
Ribonucleic acid
RNA
RNA-seq
Search Engine
sequence analysis
Sequence Analysis, RNA - methods
Software
surveys
TCGA
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Summary:We present SeqOthello, an ultra-fast and memory-efficient indexing structure to support arbitrary sequence query against large collections of RNA-seq experiments. It takes SeqOthello only 5 min and 19.1 GB memory to conduct a global survey of 11,658 fusion events against 10,113 TCGA Pan-Cancer RNA-seq datasets. The query recovers 92.7% of tier-1 fusions curated by TCGA Fusion Gene Database and reveals 270 novel occurrences, all of which are present as tumor-specific. By providing a reference-free, alignment-free, and parameter-free sequence search system, SeqOthello will enable large-scale integrative studies using sequence-level data, an undertaking not previously practicable for many individual labs.
ISSN:1474-760X
1474-7596
1474-760X
DOI:10.1186/s13059-018-1535-9