Evidence map›Paper›PMID 28320326›Full record

ArticleBMC bioinformatics2017

LW-FQZip 2: a parallelized reference-based compression of FASTQ files.

Zhi-An Huang, Zhenkun Wen, Qingjin Deng, Ying Chu, Yiwen Sun, Zexuan Zhu

Abstract read
In one paragraph

Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
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  7. Tackling the Challenges of FASTQ Referential Compression.Bioinformatics and biology insights · 2019
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zhi-An HuangCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China.
Zhenkun WenCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China.
Qingjin DengCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China.
Ying ChuCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China.
Yiwen SunSchool of Medicine, Shenzhen University, Shenzhen, 518060, China.
Zexuan ZhuCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China. zhuzx@szu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe rapid progress of high-throughput DNA sequencing techniques has dramatically reduced the costs of whole genome sequencing, which leads to revolutionary advances in gene industry. The explosively increasing volume of raw data outpaces the decreasing disk cost and the storage of huge sequencing data has become a bottleneck of downstream analyses. Data compression is considered as a solution to reduce the dependency on storage. Efficient sequencing data compression methods are highly demanded.

resultsIn this article, we present a lossless reference-based compression method namely LW-FQZip 2 targeted at FASTQ files. LW-FQZip 2 is improved from LW-FQZip 1 by introducing more efficient coding scheme and parallelism. Particularly, LW-FQZip 2 is equipped with a light-weight mapping model, bitwise prediction by partial matching model, arithmetic coding, and multi-threading parallelism. LW-FQZip 2 is evaluated on both short-read and long-read data generated from various sequencing platforms. The experimental results show that LW-FQZip 2 is able to obtain promising compression ratios at reasonable time and memory space costs.

conclusionsThe competence enables LW-FQZip 2 to serve as a candidate tool for archival or space-sensitive applications of high-throughput DNA sequencing data. LW-FQZip 2 is freely available at http://csse.szu.edu.cn/staff/zhuzx/LWFQZip2 and https://github.com/Zhuzxlab/LW-FQZip2 .

Indexed as

Data CompressionHigh-Throughput Nucleotide SequencingSequence AlignmentSequence Analysis, DNAHigh-throughput sequencingReference- based compressionSequence alignmentSequencing data compression

Identifiers

PMID28320326
PMCPMC5359991

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.