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AFRESh: an adaptive framework for compression of reads and assembled sequences with random access functionality
Author(s) -
Tom Paridaens,
Glenn Van Wallendael,
Wesley De Neve,
Peter Lambert
Publication year - 2017
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btx001
Subject(s) - random access , computer science , data compression , coding (social sciences) , context adaptive binary arithmetic coding , binary number , set (abstract data type) , encoding (memory) , theoretical computer science , algorithm , arithmetic , artificial intelligence , programming language , mathematics , statistics
The past decade has seen the introduction of new technologies that lowered the cost of genomic sequencing increasingly. We can even observe that the cost of sequencing is dropping significantly faster than the cost of storage and transmission. The latter motivates a need for continuous improvements in the area of genomic data compression, not only at the level of effectiveness (compression rate), but also at the level of functionality (e.g. random access), configurability (effectiveness versus complexity, coding tool set …) and versatility (support for both sequenced reads and assembled sequences). In that regard, we can point out that current approaches mostly do not support random access, requiring full files to be transmitted, and that current approaches are restricted to either read or sequence compression.

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