A FASTQ compressor based on integer-mapped k-mer indexing for biologist
Document Type
Article
Publication Date
3-15-2016
Abstract
Next generation sequencing (NGS) technologies have gained considerable popularity among biologists. For example, RNA-seq, which provides both genomic and functional information, has been widely used by recent functional and evolutionary studies, especially in non-model organisms. However, storing and transmitting these large data sets (primarily in FASTQ format) have become genuine challenges, especially for biologists with little informatics experience. Data compression is thus a necessity. KIC, a FASTQ compressor based on a new integer-mapped k-mer indexing method, was developed (available at http://www.ysunlab.org/kic.jsp). It offers high compression ratio on sequence data, outstanding user-friendliness with graphic user interfaces, and proven reliability. Evaluated on multiple large RNA-seq data sets from both human and plants, it was found that the compression ratio of KIC had exceeded all major generic compressors, and was comparable to those of the latest dedicated compressors. KIC enables researchers with minimal informatics training to take advantage of the latest sequence compression technologies, easily manage large FASTQ data sets, and reduce storage and transmission cost.
Publication Title
Gene
First Page Number
75
Last Page Number
81
DOI
10.1016/j.gene.2015.12.053
Recommended Citation
Zhang, Yeting; Patel, Khyati; Endrawis, Tony; Bowers, Autumn; and Sun, Yazhou, "A FASTQ compressor based on integer-mapped k-mer indexing for biologist" (2016). Kean Publications. 1746.
https://digitalcommons.kean.edu/keanpublications/1746