Analysis of cross sequence similarities for multiple DNA sequences compression

IEEE/ACM Trans. Comput. Biol. and Bioinf.

et al. 2015

Self Cite

Traditionally, intra-sequence similarity is exploited for compressing a single DNA sequence. Recently, remarkable compression performance of individual DNA sequence from the same population is achieved by encoding its difference with a nearly identical reference sequence. Nevertheless, there is lack of general algorithms that also allow less similar reference sequences. In this work, we extend the intra-sequence to the inter-sequence similarity in that approximate matches of subsequences are found between the DNA sequence and a set of reference sequences. Hence, a set of nearly identical DNA sequences from the same population or a set of partially similar DNA sequences like chromosome sequences and DNA sequences of related species can be compressed together. For practical compressors, the compressed size is usually influenced by the compression order of sequences. Fast search algorithms for the optimal compression order are thus developed for multiple sequences compression. Experimental results on artificial and real datasets demonstrate that our proposed multiple sequences compression methods with fast compression order search are able to achieve good compression performance under different levels of similarity in the multiple DNA sequences.

Section: Dna Similarities For Compressionmentioning

confidence: 99%

Section: Dna Similarities For Compressionmentioning

confidence: 99%

Section: Dna Similarities For Compressionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Compression of Multiple DNA Sequences Using Intra-Sequence and Inter-Sequence Similarities

Cheng

IEEE/ACM Trans. Comput. Biol. and Bioinf.

et al. 2015

Self Cite

“…The similar subsequences can be exact repeats with the same bases or with reverse complementary bases [9,10]. Consider the sequence S 1 as, The sequence S 1 contains both repeat and reverse complementary repeat.…”

Section: Base T T a G C G T T A G C G C G C T A Amentioning

confidence: 99%

A Survey of Techniques for Sequence Similarities Matching in Compression

Cheng

2014

Adv Robot Autom

DNA Sequence Compression can be achieved through exploiting the intra-sequence and inter-sequence similarities. In order to have a good compression gain, effective methods have to be used to search for all the similar subsequences within the DNA sequences so that these similar subsequences can be encoded together. Different pattern recognition methods have been used to search for these similar subsequences. They are suffix-based approach, dynamic programming approach, seed extension approach, rule-based approach and parsing approach. A survey of their main ideas and application domains has been given in this paper.

Application of signal processing for DNA sequence compression

2019

IET signal process.

Due to the advancement of high-throughput sequencing technologies, it is now feasible for sequencing individual genomes in a fast and affordable manner. With the significant increase in the number of individual genomes, compression methods are needed to reduce pressure on data storage as well as enable effective data distribution and management. The compression methods can generally be divided into two classes, namely reference-free methods and reference-based methods. In reference-free methods, redundancies within the target DNA sequence to be compressed are explored. In reference-based methods, redundancies between the target DNA sequence and other reference sequences are identified to achieve compression. This type of method is applicable to population sequences which are highly similar to each other and have a small number of mismatches. Some of the methods can also be applied to partially similar sequences such as chromosome sequences or sequences having evolutionary relationship. The authors highlight recent developments in these methods. In the comparative study, the authors' simulation results reveal that the selection of a reference sequence is a crucial factor affecting the compression performance. Use of multiple number of reference sequences and enhancement strategies such as reference rewriting are important to achieve a large compression gain. (a) Short segment of the chromosome 19 of the human Homo sapiens genome, (b) Its lossless encoded representation with 'A' represented as '00', 'T' as '11', 'C' as '01' and 'G' as '10', (c) Resultant segment after the first referencing instruction is applied