Additional file 1: Table S1. of Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies

微生物组数据分析方法

16SrRNA基因扩增子基准测试

Overview of the datasets used in the study. Sampling and data characteristics of the seven datasets used in the study, A1â A4 for the false positive rate and spike-in retrieval tests and B1â B3 for

Figshare2017-04-22 更新70

Additional file 3 of Whole microbial community viability is not quantitatively reflected by propidium monoazide sequencing approach

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微生物组数据分析方法

Additional file 2. bioBakery workflows.

DataCite Commons2024-03-04 更新70

An Open-Source QIIME2 and R Pipeline for Multi-Amplicon 16S rRNA Profiling: Validation and Application in Pediatric Microbiome Studies

微生物组数据分析方法

儿童微生物组

This study presents a validated, open-source QIIME2- and R-based pipeline for 16S rRNA gene profiling using multi-amplicon sequencing. It aims to overcome the limitations of commercial, closed-source

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Additional file 14: Table S2. of Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies

资源简介：

Additional file 14: Table S2. of Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies

资源简介：

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