<![CDATA[基于qiime2的扩增子数据分析]]>一，导入数据
我们当前交付的illumina的数据都是双端且拆分过的 枚举值默认选择双端类型
暴露参数：
input-path:数据文件夹
type:类别 枚举型 默认值SampleData[PairedEndSequencesWithQuality]
input-format:格式 枚举型 默认值 CasavaOneEightSingleLanePerSampleDirFmt

参考：
https://igor.sbgenomics.com/public/apps/admin/sbg-public-data/qiime2-16s-rrna-metagenomic-profiling
ef864964-38b5-4ba4-8025-a58d24935dc3-image.png

qiime tools import \
  --type 'SampleData[PairedEndSequencesWithQuality]' \
  --input-path casava-18-paired-end-demultiplexed \
  --input-format CasavaOneEightSingleLanePerSampleDirFmt \
  --output-path demux-paired-end.qza

2.拆分（当前先不支持）
导入数据时 虽然大部分情况都已经拆分 如果没有拆分的数据 我们需要在文件上传的过程中增加一个拆分功能 让用户上传文件 并且附上 一个表格 表格里面包括样本编号和barcode列表 和qiime2类似

qiime demux emp-single \
  --i-seqs emp-single-end-sequences.qza \
  --m-barcodes-file sample-metadata.tsv \
  --m-barcodes-column barcode-sequence \
  --o-per-sample-sequences demux.qza \
  --o-error-correction-details demux-details.qza

拆分的软件对于illumina的数据 可以使用bcl2fastq 需要原始数据和samplesheet
https://support.illumina.com/content/dam/illumina-support/documents/documentation/software_documentation/bcl2fastq/bcl2fastq2-v2-20-software-guide-15051736-03.pdf

]]>http://an.forum.genostack.com/topic/743/基于qiime2的扩增子数据分析RSS for NodeSat, 13 Jun 2026 12:37:20 GMTWed, 03 Aug 2022 10:07:59 GMT60<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Fri, 14 Apr 2023 06:10:22 GMT]]>https://drive5.com/usearch/manual/amplification_bias.html
Abundance and amplification bias in amplicon sequencing
序列的丰度和物种的实际丰度 可能偏差比较大

]]>http://an.forum.genostack.com/post/2036http://an.forum.genostack.com/post/2036Fri, 14 Apr 2023 06:10:22 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Wed, 12 Apr 2023 08:48:12 GMT]]>https://www.jandonline.org/article/S2212-2672(20)30438-X/pdf
Associations between Diet, the Gut Microbiome,
and Short-Chain Fatty Acid Production among
Older Caribbean Latino Adults
饮食和微生物多样性的研究 主要用了关联性分析

]]>http://an.forum.genostack.com/post/2030http://an.forum.genostack.com/post/2030Wed, 12 Apr 2023 08:48:12 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Thu, 06 Apr 2023 12:16:03 GMT]]>https://hackmd.io/@MAE-MBL/HylpoaOF5#Part-II-In-depth-analysis

这个文章写的不错

]]>http://an.forum.genostack.com/post/2026http://an.forum.genostack.com/post/2026Thu, 06 Apr 2023 12:16:03 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Tue, 04 Apr 2023 12:15:03 GMT]]>假如data2的代码保存在 /root/data2
cd /root
R CMD build dada2
会生成dada2.so

]]>http://an.forum.genostack.com/post/2023http://an.forum.genostack.com/post/2023Tue, 04 Apr 2023 12:15:03 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Tue, 11 Apr 2023 07:02:21 GMT]]>https://forum.qiime2.org/t/difference-between-sub-sampling-and-rarefing/18219

sub-sampling and rarefing的对比:
5688a244-9fd7-4071-a031-d2e8a6629c73-image.png 25b2f752-278b-41d6-aa58-cfcc0f403be6-image.png

c96b2b7f-7c63-456b-9890-72071f25e5b4-image.png

sub-sampling可以从sample或者feature的角度 对数据进行过滤 得到的是整个数据的子集。
rarefy是对所有feature的结果进行归一化。

]]>http://an.forum.genostack.com/post/2020http://an.forum.genostack.com/post/2020Tue, 11 Apr 2023 07:02:21 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Sat, 01 Apr 2023 06:17:09 GMT]]>dada2的执行过程:
filterAndTrim 过滤，截取
derepFastq (可选步骤 dada内部会判断 如果没有经过去重 会自己调用这个函数)
learnErrors 这个函数也会调用dada 以 self-consist mode 模式运行
dada 核心步骤 但是 self-consist mode = FALSE

]]>http://an.forum.genostack.com/post/2017http://an.forum.genostack.com/post/2017Sat, 01 Apr 2023 06:17:09 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Thu, 30 Mar 2023 08:31:47 GMT]]>https://btep.ccr.cancer.gov/docs/qiime2/index.html
Microbiome Analysis with QIIME2 教程

]]>http://an.forum.genostack.com/post/2015http://an.forum.genostack.com/post/2015Thu, 30 Mar 2023 08:31:47 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Fri, 30 Sep 2022 09:04:30 GMT]]>dyn.load("./src/dada2.so")
Error in dyn.load("./src/dada2.so") :
unable to load shared object '/home/jynlix/Downloads/src/dada2/dada2/./src/dada2.so':
/home/jynlix/Downloads/src/dada2/dada2/./src/dada2.so: undefined symbol: _ZTIN3tbb4taskE

使用gdb 调试dada2时报错 dada2依赖 Rcpp 做多线程 Rcpp 依赖 tbb 需要提前把这个包加载

dyn.load("/home/jynlix/R/x86_64-pc-linux-gnu-library/4.1/RcppParallel/lib/libtbb.so.2", local = FALSE)

]]>http://an.forum.genostack.com/post/1866http://an.forum.genostack.com/post/1866Fri, 30 Sep 2022 09:04:30 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Thu, 29 Sep 2022 06:27:07 GMT]]>https://github.com/benjjneb/dada2/issues/1095
dereplication (derepFastq) required?
dada2在处理的时候 可以去重 只是为了降低内存消耗？在最后统计丰度的时候 会把重复再计算回来？

]]>http://an.forum.genostack.com/post/1863http://an.forum.genostack.com/post/1863Thu, 29 Sep 2022 06:27:07 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Wed, 28 Sep 2022 01:40:53 GMT]]>DADA2的限制
33724111-06e2-45c5-aa3e-2cbc189b42fb-image.png
DADA2对于单体序列 无法识别

]]>http://an.forum.genostack.com/post/1861http://an.forum.genostack.com/post/1861Wed, 28 Sep 2022 01:40:53 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Tue, 13 Sep 2022 08:18:42 GMT]]>https://www.drive5.com/usearch/manual/qiime_classic.html
OTU 表中的数字代表reads数

]]>http://an.forum.genostack.com/post/1835http://an.forum.genostack.com/post/1835Tue, 13 Sep 2022 08:18:42 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Mon, 05 Sep 2022 11:25:57 GMT]]>对于__的问题：
qiime的图上会有__;__这种注释
4a67e350-a9b9-4b3c-840a-1da8075f37ae-image.png

经过查询：
850ca6bc-9ad2-479c-a188-fe5693299d7a-image.png
数据里面是
k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Burkholderiales 这种级别不够的注释
对于级别不够的情况 qiime view 会用__补齐

但是注意，s__ p__这种情况数据也是有的 如果需要过滤 可以用
qiime taxa filter-table --p-exclude "s__"过滤

]]>http://an.forum.genostack.com/post/1832http://an.forum.genostack.com/post/1832Mon, 05 Sep 2022 11:25:57 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Fri, 02 Sep 2022 12:06:27 GMT]]>https://colab.research.google.com/github/Gibbons-Lab/isb_course_2020/blob/master/16S.ipynb#scrollTo=h3NALJ7u6mBP

使用Colab来运行Qiime2
ca7766ac-8224-4e29-a739-484290c0e7a1-image.png

4166d0cf-56e2-4ab9-bcba-a8011754855f-image.png

5f4a99a7-e403-44b1-afb4-6de5d7509358-image.png

]]>http://an.forum.genostack.com/post/1831http://an.forum.genostack.com/post/1831Fri, 02 Sep 2022 12:06:27 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Fri, 02 Sep 2022 11:53:15 GMT]]>https://www.biorxiv.org/content/10.1101/2021.09.15.460495v2.full.pdf
Tourmaline: a containerized workflow for rapid and
iterable amplicon sequence analysis using QIIME 2
and Snakemake
使用snakemake对qiime2做了自动化

]]>http://an.forum.genostack.com/post/1830http://an.forum.genostack.com/post/1830Fri, 02 Sep 2022 11:53:15 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Thu, 01 Sep 2022 11:26:51 GMT]]>https://bioinformaticsworkbook.org/dataAnalysis/Metagenomics/Qiime2.html#gsc.tab=0

]]>http://an.forum.genostack.com/post/1829http://an.forum.genostack.com/post/1829Thu, 01 Sep 2022 11:26:51 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Thu, 01 Sep 2022 07:16:39 GMT]]>https://forum.qiime2.org/t/whats-the-difference-between-and-g-in-greengene-database/17615

S__ 和__的区别

]]>http://an.forum.genostack.com/post/1826http://an.forum.genostack.com/post/1826Thu, 01 Sep 2022 07:16:39 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Fri, 26 Aug 2022 12:58:01 GMT]]>https://www.youtube.com/watch?v=g5BdGP4V5YA
关于rarefy的解释

]]>http://an.forum.genostack.com/post/1814http://an.forum.genostack.com/post/1814Fri, 26 Aug 2022 12:58:01 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Fri, 26 Aug 2022 11:43:09 GMT]]>https://hackmd.io/@MAE-MBL/HylpoaOF5 qiime2的一个帖子 讲的比较好

]]>http://an.forum.genostack.com/post/1813http://an.forum.genostack.com/post/1813Fri, 26 Aug 2022 11:43:09 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Fri, 26 Aug 2022 09:40:59 GMT]]>python -m pdb /home/jynlix/miniconda3/envs/qiime2-2022.2/bin/qiime diversity alpha-group-significance --i-alpha-diversity ace.qza --m-metadata-file metadata2.tsv --o-visualization alpha.ace.qzv --verbose

qiime2代码调试
1.要使用全路径
2.要加上--verbose 否则pdb的打印也会被重定向
3.然后可以使用“文件名:行号”打断点
b /home/jynlix/miniconda3/envs/qiime2-2022.2/lib/python3.8/site-packages/q2_diversity/_alpha/_visualizer.py:35

]]>http://an.forum.genostack.com/post/1812http://an.forum.genostack.com/post/1812Fri, 26 Aug 2022 09:40:59 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Fri, 05 Aug 2022 10:51:25 GMT]]>https://edu.omicslogic.com/blog/16s-rna-amplicon-data-analysis-dada2-on-t-bioinfoserver?utm_campaign=T-Bio Info Server&utm_content=212683594&utm_medium=social&utm_source=linkedin&hss_channel=lcp-27253342
3c0844f9-8f04-4943-a2b8-532b3f73e4f3-image.png

]]>http://an.forum.genostack.com/post/1780http://an.forum.genostack.com/post/1780Fri, 05 Aug 2022 10:51:25 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Fri, 05 Aug 2022 03:33:04 GMT]]>NIHMS782534-supplement-1.pdf
f58dd7ce-2d0a-4c3b-95c8-976abdb2b8f0-image.png
为了排除测序误差 OTU采用聚类的方式(97%相似度) 但是也会把真正的突变给排除掉
DADA2 R package implements the full amplicon workflow: filtering, dereplication, chimera identification, and merging paired-end reads.
DADA2 本身是个流程 做了很多事情 其中有一个就是把R1、R2做了合并。

]]>http://an.forum.genostack.com/post/1777http://an.forum.genostack.com/post/1777Fri, 05 Aug 2022 03:33:04 GMT<![CDATA[Reply to 基于qiime2的扩增子数据分析 on Thu, 04 Aug 2022 11:32:20 GMT]]>https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03591-6
DADA2 Deblur CD-HIT-OTU-Miseq的对比：
Deblur 只能支持单端 必须进行R1、R2的合并
DADA2 内部本身就会合并

https://github.com/ydkondratenko/cdsnake
http://weizhong-lab.ucsd.edu/cd-hit-otu/

https://www.biorxiv.org/content/10.1101/153783v1.full
CD-HIT-OTU-MiSeq, an Improved Approach for Clustering and Analyzing Paired End MiSeq 16S rRNA Sequences
70036dd0-6a9f-40ef-b20d-27483f736fc4-image.png

]]>http://an.forum.genostack.com/post/1776http://an.forum.genostack.com/post/1776Thu, 04 Aug 2022 11:32:20 GMT