Improved representation of sequence bloom trees.

ABSTRACT:

Motivation

Algorithmic solutions to index and search biological databases are a fundamental part of bioinformatics, providing underlying components to many end-user tools. Inexpensive next generation sequencing has filled publicly available databases such as the Sequence Read Archive beyond the capacity of traditional indexing methods. Recently, the Sequence Bloom Tree (SBT) and its derivatives were proposed as a way to efficiently index such data for queries about transcript presence.

Results

We build on the SBT framework to construct the HowDe-SBT data structure, which uses a novel partitioning of information to reduce the construction and query time as well as the size of the index. Compared to previous SBT methods, on real RNA-seq data, HowDe-SBT can construct the index

SUBMITTER: Harris RS 

PROVIDER: S-EPMC8215923 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature