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In previous work, the authors developed a modular no-reference framework that compresses FASTA files by applying a predict-and-residue method, as used in video coding. We extended this framework with support for Context-Adaptive Binary Arithmetic Coding (CABAC), while at the same time preserving random access functionality and offering support for the full IUB/IUPAC nucleic acid codes alphabet.
In this paper, we show that the LZ77 factorization of a text T ε Σn can be computed in O(R log n) bits of working space and O(n log R) time, R being the number of runs in the Burrows-Wheeler transform of T (reversed). For (extremely) repetitive inputs, the working space can be as low as O(log n) bits: exponentially smaller than the text itself. Hence, our result finds important applications in the...
This paper provides the specification and an initial validation of an evaluation framework for the comparison of lossy compressors of genome sequencing quality values. The goal is to define reference data, test sets, tools and metrics that shall be used to evaluate the impact of lossy compression of quality values on human genome variant calling. The functionality of the framework is validated referring...
The number of genomic sequences is growing substantially. Besides discarding part of the data, the only efficient possibility for coping with this trend is data compression. We present an efficient compressor for genomic sequences, allowing both reference-free and referential compression. This compressor uses a mixture of context models of several orders, according to two model classes: reference...
Massive amounts of sequencing data are being generated thanks to advances in sequencing technology and a dramatic drop in the sequencing cost. Storing and sharing this large data has become a major bottleneck in the discovery and analysis of genetic variants that are used for medical inference. As such, lossless compression of this data has been proposed. Of the compressed data, more than 70% correspond...
In order to avoid the reference bias introduced by mapping reads to a reference genome, bioinformaticians are investigating reference-free methods for analyzing sequenced genomes. With large projects sequencing thousands of individuals, this raises the need for tools capable of handling terabases of sequence data. A key method is the Burrows-Wheeler transform (BWT), which is widely used for compressing...
Due to novel high-throughput next-generation sequencing technologies, the sequencing of huge amounts of genetic information has become affordable. On account of this flood of data, IT costs have become a major obstacle compared to sequencing costs. High-performance compression of genomic data is required to reduce the storage size and transmission costs. The high coverage inherent in next-generation...
Next generation sequencing technologies generate normous amount of short reads, which poses a significant computational challenge for short read alignment. Furthermore, because of sequence polymorphisms in a population, repetitive sequences, and sequencing errors, there still exist difficulties in correctly aligning all reads. We propose a space-efficient compressed suffix array-based method for short...
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