下一个流与简单的bash:从整个基因组序列数据中呼叫SNP并行化的不同方法
Marek Sztuka1, Krzysztof Kotlarz1,2, Magda Mielczarek1,2
1Wroclaw University of Environmental and Life Sciences, Department of Genetics, the Biostatistics Group Kozuchowska 7, Wroclaw PL-51631, Poland.
NAR genomics and bioinformatics
|April 30, 2024
概括
多进程Nextflow脚本为单核酸多态 (SNP) 调用工作流提供了15-27%的速度改进. 这种方法提高了基因组数据分析的计算效率.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 对大型基因组数据集的高效处理对于畜牧养殖和研究至关重要.
- 单核酸多态性 (SNP) 调用工作流在遗传分析中是基本的.
- 平行化策略显著影响生物信息学管道的性能.
研究的目的:
- 为了比较SNP调用工作流程的不同计算并行化方法的性能.
- 为了评估各种并行化方法的执行时间,RAM使用量和磁盘使用量.
- 为了确定SNP最有效的并行化策略,调用牛DNA测序数据.
主要方法:
- 三种并行化方法的比较:简单的Bash脚本,单进程Nextflow和多进程Nextflow.
- 通过标准生物信息管道 (QC,对齐,SNP调用) 处理了来自五头荷尔斯坦-弗里西亚牛的DNA测序数据.
- 评估性能指标,包括执行速度,随机存取内存 (RAM) 消耗,以及跨不同线程计数的磁盘空间利用.
主要成果:
- 与普通Bash方法相比,多进程Nextflow脚本的平均执行速度增加了15-27% ,特别是在10个线程的情况下.
- 在多进程Nextflow设置中的RAM使用量与线程数量相比,与其他方法不同.
- 由于生成中间和日志文件,多进程Nextflow的磁盘使用量最高.
结论:
- 多进程Nextflow为SNP调用工作流提供了显著的性能优势,提高了计算效率.
- 选择并行化策略会影响资源利用 (RAM,磁盘空间),需要对大规模基因组分析进行仔细考虑.
- 建议使用Nextflow的多过程方法来优化SNP,在牛基因组学研究中进行调用.
相关概念视频
03:00Next-generation Sequencing
88.7K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
88.7K
03:36Genome Annotation and Assembly
18.8K
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
18.8K
03:21RNA-seq
9.9K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
9.9K
02:26Comparing Copy Number Variations and SNPs
17.7K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
17.7K