Evidence map›Paper›PMID 37811144›Full record

ArticleFrontiers in genetics2023

Efficient sequencing data compression and FPGA acceleration based on a two-step framework.

Shifu Chen, Yaru Chen, Zhouyang Wang, Wenjian Qin, Jing Zhang, Heera Nand, Jishuai Zhang, Jun Li, Xiaoni Zhang, Xiaoming Liang and 1 more

Abstract read
In one paragraph

Article in Frontiers in genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. 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

11 authors.

Shifu Chen *HaploX Biotechnology, Shenzhen, Guangdong, China.
Yaru Chen *HaploX Biotechnology, Shenzhen, Guangdong, China.
Zhouyang WangHaploX Biotechnology, Shenzhen, Guangdong, China.
Wenjian QinShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.
Jing ZhangHaploX Biotechnology, Shenzhen, Guangdong, China.
Heera NandXilinx Inc., San Jose, CA, United States.
Jishuai ZhangXilinx Inc., San Jose, CA, United States.
Jun LiHaploX Biotechnology, Shenzhen, Guangdong, China.
Xiaoni ZhangHaploX Biotechnology, Shenzhen, Guangdong, China.
Xiaoming LiangXilinx Inc., San Jose, CA, United States.
Mingyan XuHaploX Biotechnology, Shenzhen, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the increasing throughput of modern sequencing instruments, the cost of storing and transmitting sequencing data has also increased dramatically. Although many tools have been developed to compress sequencing data, there is still a need to develop a compressor with a higher compression ratio. We present a two-step framework for compressing sequencing data in this paper. The first step is to repack original data into a binary stream, while the second step is to compress the stream with a LZMA encoder. We develop a new strategy to encode the original file into a LZMA highly compressed stream. In addition an FPGA-accelerated of LZMA was implemented to speedup the second step. As a demonstration, we present repaq as a lossless non-reference compressor of FASTQ format files. We introduced a multifile redundancy elimination method, which is very useful for compressing paired-end sequencing data. According to our test results, the compression ratio of repaq is much higher than other FASTQ compressors. For some deep sequencing data, the compression ratio of repaq can be higher than 25, almost four times of Gzip. The framework presented in this paper can also be applied to develop new tools for compressing other sequencing data. The open-source code of repaq is available at: https://github.com/OpenGene/repaq.

Indexed as

compressionfastqFPGA accelerationLZMArepaqsequencing

Identifiers

PMID37811144
PMCPMC10552150

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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.