qiime2R包整合qiime2和R可视化分析16s数据

背景:qiime artifact 是用于存储qiime2的输入输出以及相关的元数据,并提供结果是如何产生的信息,但是qiime2所产生的artifacts(如.qza,虽然其是一个压缩文件)不能直接作为R的直接输入文件,而是要经过一系列的转化成R可接受的文件,所以qiime2R这个包被用来简化从qiime2 artifacts到R中输入文件的步骤,并且尽可能的保留artifacts中的信息,主要通过read_qza函数实现。

原理: The artifact is unpacked in to a temporary directory and the raw data and associated metadata are read into a named list (see below). Data are typically returned as either a data.frame, phylo object (trees), or DNAStringSets (nucleic acid sequences).

2.qiime2R包的下载

github中下载

if (!requireNamespace("devtools", quietly = TRUE)){install.packages("devtools")}
devtools::install_github("jbisanz/qiime2R")

3.读取artifacts(.qza)

依靠read_qza函数实现read_qza(.qza), 例如

SVs<-read_qza("table.qza")
names(SVs)
[1] "uuid"       "type"       "format"     "contents"   "version"   
[6] "data"       "provenance"

SVs$data[1:5,1:5] #show first 5 samples and first 5 taxa
#                                 L1S105 L1S140 L1S208 L1S257 L1S281
#4b5eeb300368260019c1fbc7a3c718fc   2183      0      0      0      0
#fe30ff0f71a38a39cf1717ec2be3a2fc      5      0      0      0      0
#d29fe3c70564fc0f69f2c03e0d1e5561      0      0      0      0      0
#868528ca947bc57b69ffdf83e6b73bae      0   2249   2117   1191   1737
#154709e160e8cada6bfb21115acc80f5    802   1174    694    406    242

data: the raw data ex OTU table as matrix or tree in phylo format
uuid: the unique identifer of the artifact
type :the semantic type of the object (ex FeatureData[Sequence])
format: the format of the qiime artifact
provenance: information tracking how the object was created
contents: a table of all the files contained within the artifact and their file size
version: the reported version for the artifact, a warning error may be thrown if a new version is seen

4. 读取metadata

read_q2metadata()函数

metadata<-read_q2metadata("sample-metadata.tsv")
head(metadata) # show top lines of metadata
#  SampleID barcode-sequence body-site year month day   subject reported-antibiotic-usage days-since-experiment-start
#2     L1S8     AGCTGACTAGTC       gut 2008    10  28 subject-1                       Yes                           0
#3    L1S57     ACACACTATGGC       gut 2009     1  20 subject-1                        No                          84
#4    L1S76     ACTACGTGTGGT       gut 2009     2  17 subject-1                        No                         112
#5   L1S105     AGTGCGATGCGT       gut 2009     3  17 subject-1                        No                         140
#6   L2S155     ACGATGCGACCA left palm 2009     1  20 subject-1                        No                          84
#7   L2S175     AGCTATCCACGA left palm 2009     2  17 subject-1                        No                         112

5.读取taxonomy

当read_qza读入taxonomy时,返回的是feature id 和未拆分的物种注释以及置信分数,而后续分析需要拆分物种注释到具体的界门纲目科属种,parse_taxonomy()可以实现上述要求。

taxonomy<-read_qza("taxonomy.qza")
head(taxonomy$data)
#                        Feature.ID                                                                                                                            Taxon Confidence
#1 4b5eeb300368260019c1fbc7a3c718fc                          k__Bacteria; p__Bacteroidetes; c__Bacteroidia; o__Bacteroidales; f__Bacteroidaceae; g__Bacteroides; s__  0.9972511
#2 fe30ff0f71a38a39cf1717ec2be3a2fc                           k__Bacteria; p__Proteobacteria; c__Betaproteobacteria; o__Neisseriales; f__Neisseriaceae; g__Neisseria  0.9799427
#3 d29fe3c70564fc0f69f2c03e0d1e5561                                k__Bacteria; p__Firmicutes; c__Bacilli; o__Lactobacillales; f__Streptococcaceae; g__Streptococcus  1.0000000
#4 868528ca947bc57b69ffdf83e6b73bae                          k__Bacteria; p__Bacteroidetes; c__Bacteroidia; o__Bacteroidales; f__Bacteroidaceae; g__Bacteroides; s__  0.9955859
#5 154709e160e8cada6bfb21115acc80f5                               k__Bacteria; p__Bacteroidetes; c__Bacteroidia; o__Bacteroidales; f__Bacteroidaceae; g__Bacteroides  1.0000000
#6 1d2e5f3444ca750c85302ceee2473331 k__Bacteria; p__Proteobacteria; c__Gammaproteobacteria; o__Pasteurellales; f__Pasteurellaceae; g__Haemophilus; s__parainfluenzae  0.9455365
taxonomy<-parse_taxonomy(taxonomy$data)
head(taxonomy)
#                                  Kingdom         Phylum               Class           Order           Family         Genus        Species
#4b5eeb300368260019c1fbc7a3c718fc Bacteria  Bacteroidetes         Bacteroidia   Bacteroidales   Bacteroidaceae   Bacteroides           
#fe30ff0f71a38a39cf1717ec2be3a2fc Bacteria Proteobacteria  Betaproteobacteria    Neisseriales    Neisseriaceae     Neisseria           
#d29fe3c70564fc0f69f2c03e0d1e5561 Bacteria     Firmicutes             Bacilli Lactobacillales Streptococcaceae Streptococcus           
#868528ca947bc57b69ffdf83e6b73bae Bacteria  Bacteroidetes         Bacteroidia   Bacteroidales   Bacteroidaceae   Bacteroides           
#154709e160e8cada6bfb21115acc80f5 Bacteria  Bacteroidetes         Bacteroidia   Bacteroidales   Bacteroidaceae   Bacteroides           
#1d2e5f3444ca750c85302ceee2473331 Bacteria Proteobacteria Gammaproteobacteria  Pasteurellales  Pasteurellaceae   Haemophilus parainfluenzae

6.创建phyloseq对象

qza_to_phyloseq()函数可以连接多个read_qza()创建一个phyloseq对象用于后续分析

physeq<-qza_to_phyloseq(
    features="inst/artifacts/2020.2_moving-pictures/table.qza",
    tree="inst/artifacts/2020.2_moving-pictures/rooted-tree.qza",
    taxonomy="inst/artifacts/2020.2_moving-pictures/taxonomy.qza",
    metadata = "inst/artifacts/2020.2_moving-pictures/sample-metadata.tsv"
    )
physeq
## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 759 taxa and 34 samples ]
## sample_data() Sample Data:       [ 34 samples by 10 sample variables ]
## tax_table()   Taxonomy Table:    [ 759 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 759 tips and 757 internal nodes ]

7.其他函数

  • read_qza() - Function for reading artifacts (.qza).
  • qza_to_phyloseq() - Imports multiple artifacts to produce a phyloseq object.
  • read_q2metadata() - Reads qiime2 metadata file (containing q2-types definition line,metadata文件中第二行必须要定义哪些列是字符、那些列是数值)
  • write_q2manifest() - Writes a read manifest file to import data into qiime2
  • theme_q2r() - A ggplot2 theme for for clean figures.
  • print_provenance() - A function to display provenance information.展示数据产生的步骤
  • is_q2metadata() - A function to check if a file is a qiime2 metadata file.
  • parse_taxonomy() - A function to parse taxonomy strings and return a table where each column is a taxonomic class.
  • parse_ordination() - A function to parse the internal ordination format.
  • read_q2biom() - A function for reading QIIME2 biom files in format v2.1
  • make_clr() - Transform feature table using centered log2 ratio.
  • make_proportion() - Transform feature table to proportion (sum to 1).
  • make_percent() - Transform feature to percent (sum to 100).
  • interactive_table() - Create an interactive table in Rstudio viewer or rmarkdown html.
  • summarize_taxa()- Create a list of tables with abundances sumed to each taxonomic level.
  • taxa_barplot() - Create a stacked barplot using ggplot2.
  • taxa_heatmap() - Create a heatmap of taxonomic abundances using gplot2.
  • corner() - Show top corner of a large table-like obejct.
  • min_nonzero() - Find the smallest non-zero, non-NA in a numeric vector.
  • mean_sd() - Return mean and standard deviation for plotting.
  • subsample_table() - Subsample a table with or without replacement.
  • filter_features() - Remove low abundance features by number of counts and number of samples they appear in.

参考资料

qime2R

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