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ASAP 2:一个用于自动和一致地分析标记基因扩增子测序数据的流水线和网络服务器。

ASAP 2: a pipeline and web server to analyze marker gene amplicon sequencing data automatically and consistently.

机构信息

Institute for Food Safety and Health, Illinois Institute of Technology, Bedford Park, IL, 60501, USA.

Department of Food Science and Nutrition, Illinois Institute of Technology, Bedford Park, IL, 60501, USA.

出版信息

BMC Bioinformatics. 2022 Jan 6;23(1):27. doi: 10.1186/s12859-021-04555-0.

Abstract

BACKGROUND

Amplicon sequencing of marker genes such as 16S rDNA have been widely used to survey and characterize microbial community. However, the complex data analyses have required many interfering manual steps often leading to inconsistencies in results.

RESULTS

Here, we have developed a pipeline, amplicon sequence analysis pipeline 2 (ASAP 2), to automate and glide through the processes without the usual manual inspections and user's interference, for instance, in the detection of barcode orientation, selection of high-quality region of reads, and determination of resampling depth and many more. The pipeline integrates all the analytical processes such as importing data, demultiplexing, summarizing read profiles, trimming quality, denoising, removing chimeric sequences and making the feature table among others. The pipeline accepts multiple file formats as input including multiplexed or demultiplexed, paired-end or single-end, barcode inside or outside and raw or intermediate data (e.g. feature table). The outputs include taxonomic classification, alpha/beta diversity, community composition, ordination analysis and statistical tests. ASAP 2 supports merging multiple sequencing runs which helps integrate and compare data from different sources (public databases and collaborators).

CONCLUSIONS

Our pipeline minimizes hands-on interference and runs amplicon sequence variant (ASV)-based amplicon sequencing analysis automatically and consistently. Our web server assists researchers that have no access to high performance computer (HPC) or have limited bioinformatics skills. The pipeline and web server can be accessed at https://github.com/tianrenmaogithub/asap2 and https://hts.iit.edu/asap2 , respectively.

摘要

背景

扩增子测序技术(如 16S rDNA)已广泛用于微生物群落的调查和特征分析。然而,复杂的数据分析需要许多干预性的手动步骤,这往往导致结果不一致。

结果

在这里,我们开发了一个流程,即扩增子序列分析流程 2(ASAP 2),该流程可以自动完成所有步骤,而无需通常的手动检查和用户干预,例如检测条形码方向、选择高质量的读段、确定重采样深度等。该流程集成了所有分析过程,如导入数据、多路分解、读取概况汇总、质量修剪、去噪、去除嵌合体序列以及制作特征表等。该流程接受多种文件格式作为输入,包括多路或多路分解、成对或单端、条形码在内部或外部以及原始或中间数据(例如特征表)。输出包括分类学分类、α/β多样性、群落组成、排序分析和统计检验。ASAP 2 支持合并多个测序运行,这有助于整合和比较来自不同来源的数据(公共数据库和合作者)。

结论

我们的流程最大限度地减少了手工干预,并自动一致地运行基于扩增子序列变异(ASV)的扩增子测序分析。我们的网络服务器可以帮助那些无法访问高性能计算机(HPC)或具有有限生物信息学技能的研究人员。该流程和网络服务器可以分别在 https://github.com/tianrenmaogithub/asap2https://hts.iit.edu/asap2 上访问。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92e1/8740450/8cbc37cefbfb/12859_2021_4555_Fig1_HTML.jpg

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