2023年版本
以ZNP-ISO32.0作为例子
1. 进入docker qiime容器操作qiime
docker start qiime
docker attach qiime
2.创建manifest表格。在excel中编辑好，直接整个文件粘贴到服务器的manifest文件。
sample-id | forward-absolute-filepath | reverse-absolute-filepath |
PAB | /data/16S/2022ZNEPVpatent/PAB-ISO32_LN2-220902-P1_P220707D-0123B_1.R1.fq.gz | /data/16S/2022ZNEPVpatent/PAB-ISO32_LN2-220902-P1_P220707D-0123B_1.R2.fq.gz |
PCD | /data/16S/2022ZNEPVpatent/PCD-ISO32_LN2-220902-P1_P220707D-0124B_1.R1.fq.gz | /data/16S/2022ZNEPVpatent/PCD-ISO32_LN2-220902-P1_P220707D-0124B_1.R2.fq.gz |
3. 数据导入
qiime tools import --type 'SampleData [PairedEndSequencesWithQuality]' --input-path manifest --output-path XXX.qza --input-format PairedEndFastqManifestPhred33V2
4.碱基质量可视化
qiime demux summarize --i-data XXX.qza --o-visualization XXX.qzv
将XXX.qzv拖入qiimeView
该操作的目的是确定剪切的位置，20分以上为合格质量分数
左右双端分别剪切到对应的最小值，剪切起始点设置为引物序列长度R1（19 na），R2（20 na）
nohup qiime dada2 denoise-paired \
--i-demultiplexed-seqs XXX.qza \
--p-trim-left-f 19 \
--p-trunc-len-f 248 \
--p-trim-left-r 20 \
--p-trunc-len-r 236 \
--o-representative-sequences rep-seqs-dada2.qza \
--o-table table-XXX.qza \
--o-denoising-stats stats-XXX.qza &
备注：XXX.qza为输入数据，已经经过了质量控制
rep-seqs-dada2.qza为代表序列
stats-XXX.qza降噪效果数据输出
table-XXX.qza为Feature表
6.Feature表的可视化
6.1 metadata创建
第一行是id,与manifest保持一致，其余都是样品的信息，随意，一定要注意不能只有一列数字！
sample-id | day | compound |
PAB | 10 | TCPP |
PCD | 10 | TCPP |
6.2 feature表可视化
qiime feature-table summarize --i-table table-XXX.qza --o-visualization table.qzv --m-sample-metadata-file metadata
17W作为rarefaction深度
7. 降噪效果可视化
qiime metadata tabulate --m-input-file stats-XXX.qza --o-visualization stats-XXX.qzv
8. Alpha Rarefaction and Selecting a RarefactionDepth
qiime diversity alpha-rarefaction \
--i-table table-XXX.qza \
--p-max-depth 170000 \
--m-metadata-file metadata \
--o-visualization alpha-rarefaction.qzv
结合“feature表可视化”判断，以13W作为定量深度。
9.Taxonomicclassification
9.1分类
nohup qiime feature-classifier classify-sklearn --i-reads rep-seqs-dada2.qza --i-classifier /data/16S/silva-138-99-515-806-nb-classifier.qza --o-classification ./taxonomy.qza &
9.2可视化（可以忽视）
qiime metadata tabulate --m-input-file ./taxonomy.qza --o-visualization taxonomy.qzv
10. 定量
nohup qiime feature-table filter-samples --i-table table-XXX.qza --p-min-frequency 170000 --o-filtered-table ./table_17W.qza &
可视化
qiime taxa barplot --i-table table_17W.qza --i-taxonomy taxonomy.qza --m-metadata-file metadata --o-visualization 1taxa_barplot17W.qzv
2025.10版本
教程：Gut-to-soil axis tutorial 💩🌱 - Microbiome marker gene analysis with QIIME 2
1.安装
下载：
docker pull quay.io/qiime2/amplicon:2025.10
安装
docker run --name=qiime2_202510 -it -v /ZYdata1/ys2022/qiime2:/home 4eb6b7a3b07d
运行
docker start qiime2_202510
docker attach qiime2_202510
2.导入数据
qiime tools import --type 'SampleData[PairedEndSequencesWithQuality]' --input-path fq-manifest.tsv --output-path demux.qza --input-format PairedEndFastqManifestPhred33V2
fq-manifest.tsv：
| sample-id | forward-absolute-filepath | reverse-absolute-filepath |
| GLU | /home/Xujr202508/raw_fq/*R1.fq.gz | /home/Xujr202508/raw_fq/*R2.fq.gz |
| LB | ||
| MSM |
3. 去引物515F/806R
qiime cutadapt trim-paired --i-demultiplexed-sequences demux.qza --p-front-f GTGYCAGCMGCCGCGGTAA --p-front-r GGACTACNVGGGTWTCTAAT --o-trimmed-sequences demux-trimmed.qza --verbose
输出：demux-trimmed.qza
4. Summarize demultiplexed sequences
qiime demux summarize \
--i-data demux-trimmed.qza \
--o-visualization demux.qzv
This allows you to determine how many sequences were obtained per sample, and also to get a summary of the distribution of sequence qualities at each position in your sequence data.
5.Sequence quality control and feature table construction
qiime dada2 denoise-paired \
--i-demultiplexed-seqs demux-trimmed.qza \
--p-trim-left-f 0 \
--p-trunc-len-f 210 \
--p-trim-left-r 0 \
--p-trunc-len-r 210 \
--o-representative-sequences asv-seqs.qza \
--o-table asv-table.qza \
--o-denoising-stats denoising-stats.qza \
--o-base-transition-stats base-transition-stats.qza
6. Feature table and feature data summaries
qiime feature-table summarize \
--i-table asv-table.qza \
--o-visualization table.qzv
确定测序深度为6w
#qiime feature-table tabulate-seqs \
# --i-data asv-seqs.qza \
# --m-metadata-file asv-frequencies.qza \
# --o-visualization asv-seqs.qzv
#7. Filtering features from a feature table
#qiime feature-table filter-features \
# --i-table asv-table.qza \
# --p-min-samples 2 \
# --o-filtered-table asv-table-ms2.qza
#qiime feature-table filter-seqs \
# --i-data asv-seqs.qza \
# --i-table asv-table-ms2.qza \
# --o-filtered-data asv-seqs-ms2.qza
8. Taxonomic annotation
qiime feature-classifier classify-sklearn \
--i-classifier SILVA138.2_SSURef_NR99_uniform_classifier_V4-515f-806r.qza \
--i-reads asv-seqs.qza \
--o-classification taxonomy.qza
9. Taxonomic analysis
qiime taxa barplot \
--i-table asv-table.qza \
--i-taxonomy taxonomy.qza \
--m-metadata-file sample-metadata.tsv \
--o-visualization taxa-bar-plots.qzv
