xiangpin
commented
3 years ago The MPSE object was introduced in the newest version, it has not been released. And I will update the vignettes as soon as possible. But you can refer to the example and the manual of the corresponding functions (start with mp_).
- I also tried to convert phloseq object to MPSE object with MicrobiotaProcess funtion 'as.MPSE'. But I believed I did not do it properly. Because I can not found Taxonomy Information after convert.
Please provide a reproducible example. This is an example of converting phyloseq to MPSE object.
> library(MicrobiotaProcess)
Attaching package: ‘MicrobiotaProcess’
The following object is masked from ‘package:stats’:
filter
> data(test_otu_data)
> test_otu_data
phyloseq-class experiment-level object
otu_table() OTU Table: [ 99 taxa and 12 samples ]
sample_data() Sample Data: [ 12 samples by 2 sample variables ]
tax_table() Taxonomy Table: [ 99 taxa by 7 taxonomic ranks ]
> mpse <- test_otu_data %>% as.MPSE
> mpse
# A MPSE-tibble (MPSE object) abstraction: 1,188 × 12
# OTU=99 | Samples=12 | Assays=Abundance | Taxanomy=Kingdom, Phylum, Class, Order, Family, Genus, Species
OTU Sample Abundance sample group Kingdom Phylum Class Order Family Genus
<chr> <chr> <int> <fct> <fct> <chr> <chr> <chr> <chr> <chr> <chr>
1 OTU_1 B11 3995 B11 B k__Bact… p__Fi… c__B… o__L… f__La… g__L…
2 OTU_10 B11 605 B11 B k__Bact… p__Fi… c__B… o__L… f__La… g__L…
3 OTU_1… B11 57 B11 B k__Bact… p__Fi… c__C… o__C… f__Ru… g__R…
4 OTU_1… B11 0 B11 B k__Bact… p__Fi… c__C… o__C… f__Ru… g__I…
5 OTU_1… B11 5 B11 B k__Bact… p__Fi… c__E… o__E… f__Er… g__E…
6 OTU_1… B11 1 B11 B k__Bact… p__Fi… c__C… o__C… f__Ru… g__R…
7 OTU_1… B11 0 B11 B k__Bact… p__Ba… c__B… o__B… f__Pr… g__P…
8 OTU_1… B11 0 B11 B k__Bact… p__Fi… c__C… o__C… f__Ru… g__C…
9 OTU_1… B11 0 B11 B k__Bact… p__Ba… c__B… o__S… f__Sp… g__S…
10 OTU_1… B11 34 B11 B k__Bact… p__Fi… c__C… o__C… f__Ru… g__R…
# … with 1,178 more rows, and 1 more variable: Species <chr>
>- I wonder if we can use the phylogenetic tree information from the phyloseq object to draw the tree directly?
Yes, The newest version has supported it, you can reinstall it by remotes::install_github("YuLab-SMU/MicrobiotaProcess")
and perform mp_diff_analysis with parameter action="add", then use mp_extract_tree(type="otutree") to get the phylogenetic tree, mp_extract_tree(type="taxatree") to get the taxonomy tree. You can refer to the following example.
> library(MicrobiotaProcess)
Attaching package: ‘MicrobiotaProcess’
The following object is masked from ‘package:stats’:
filter
> mpse <- mp_import_qiime2(otuqza="./table.qza", taxaqza="./taxonomy.qza", mapfilename="./sample-metadata.tsv", refseqqza="./refseq.qza", treeqza="./tree.qza")
Warning messages:
1: The treeqza is a tree file, it is parsing by read.tree function.
* It is better to parse it with the function of treeio
* then the treedata or phylo result all can be supported.
2: The number of samples in otu table is not equal the number of samples in sample data.
* The same samples will be extract automatically !
> mpse
# A MPSE-tibble (MPSE object) abstraction: 26,180 × 19
# OTU=770 | Samples=34 | Assays=Abundance | Taxanomy=Kingdom, Phylum, Class, Order, Family, Genus, Speies
OTU Sample Abundance barcode.sequence body.site year month day subject
<chr> <chr> <dbl> <chr> <chr> <chr> <chr> <chr> <chr>
1 4b5eeb… L1S8 2599 AGCTGACTAGTC gut 2008 10 28 subjec…
2 fe30ff… L1S8 0 AGCTGACTAGTC gut 2008 10 28 subjec…
3 d29fe3… L1S8 0 AGCTGACTAGTC gut 2008 10 28 subjec…
4 868528… L1S8 0 AGCTGACTAGTC gut 2008 10 28 subjec…
5 154709… L1S8 1623 AGCTGACTAGTC gut 2008 10 28 subjec…
6 1d2e5f… L1S8 5 AGCTGACTAGTC gut 2008 10 28 subjec…
7 0305a4… L1S8 243 AGCTGACTAGTC gut 2008 10 28 subjec…
8 cb2fe0… L1S8 0 AGCTGACTAGTC gut 2008 10 28 subjec…
9 997056… L1S8 3 AGCTGACTAGTC gut 2008 10 28 subjec…
10 3c9c43… L1S8 0 AGCTGACTAGTC gut 2008 10 28 subjec…
# … with 26,170 more rows, and 10 more variables: reported.antibiotic.usage <chr>,
# days.since.experiment.start <chr>, Confidence <dbl>, Kingdom <chr>,
# Phylum <chr>, Class <chr>, Order <chr>, Family <chr>, Genus <chr>,
# Speies <chr>
> mpse %<>% mp_rrarefy()
> mpse
# A MPSE-tibble (MPSE object) abstraction: 26,180 × 20
# OTU=770 | Samples=34 | Assays=Abundance, RareAbundance | Taxanomy=Kingdom, Phylum, Class, Order, Family, Genus, Speies
OTU Sample Abundance RareAbundance barcode.sequence body.site year month
<chr> <chr> <dbl> <dbl> <chr> <chr> <chr> <chr>
1 4b5eeb… L1S8 2599 348 AGCTGACTAGTC gut 2008 10
2 fe30ff… L1S8 0 0 AGCTGACTAGTC gut 2008 10
3 d29fe3… L1S8 0 0 AGCTGACTAGTC gut 2008 10
4 868528… L1S8 0 0 AGCTGACTAGTC gut 2008 10
5 154709… L1S8 1623 202 AGCTGACTAGTC gut 2008 10
6 1d2e5f… L1S8 5 1 AGCTGACTAGTC gut 2008 10
7 0305a4… L1S8 243 38 AGCTGACTAGTC gut 2008 10
8 cb2fe0… L1S8 0 0 AGCTGACTAGTC gut 2008 10
9 997056… L1S8 3 0 AGCTGACTAGTC gut 2008 10
10 3c9c43… L1S8 0 0 AGCTGACTAGTC gut 2008 10
# … with 26,170 more rows, and 12 more variables: day <chr>, subject <chr>,
# reported.antibiotic.usage <chr>, days.since.experiment.start <chr>,
# Confidence <dbl>, Kingdom <chr>, Phylum <chr>, Class <chr>, Order <chr>,
# Family <chr>, Genus <chr>, Speies <chr>
> mpse %<>% mp_diff_analysis(.abundance=RareAbundance, .group=body.site, first.test.alpha=0.01)
> mpse
# A MPSE-tibble (MPSE object) abstraction: 26,180 × 27
# OTU=770 | Samples=34 | Assays=Abundance, RareAbundance, RelRareAbundanceBySample | Taxanomy=Kingdom, Phylum, Class, Order, Family, Genus, Speies
OTU Sample Abundance RareAbundance RelRareAbundance… barcode.sequence
<chr> <chr> <dbl> <dbl> <dbl> <chr>
1 4b5eeb3003… L1S8 2599 348 38.8 AGCTGACTAGTC
2 fe30ff0f71… L1S8 0 0 0 AGCTGACTAGTC
3 d29fe3c705… L1S8 0 0 0 AGCTGACTAGTC
4 868528ca94… L1S8 0 0 0 AGCTGACTAGTC
5 154709e160… L1S8 1623 202 22.5 AGCTGACTAGTC
6 1d2e5f3444… L1S8 5 1 0.111 AGCTGACTAGTC
7 0305a4993e… L1S8 243 38 4.23 AGCTGACTAGTC
8 cb2fe0146e… L1S8 0 0 0 AGCTGACTAGTC
9 997056ba80… L1S8 3 0 0 AGCTGACTAGTC
10 3c9c437f27… L1S8 0 0 0 AGCTGACTAGTC
# … with 26,170 more rows, and 21 more variables: body.site <chr>, year <chr>, month <chr>,
# day <chr>, subject <chr>, reported.antibiotic.usage <chr>,
# days.since.experiment.start <chr>, Confidence <dbl>, Kingdom <chr>,
# Phylum <chr>, Class <chr>, Order <chr>, Family <chr>, Genus <chr>,
# Speies <chr>, LDAupper <dbl>, LDAmean <dbl>, LDAlower <dbl>,
# Sign_body.site <chr>, pvalue <dbl>, fdr <dbl>
> otutree <- mpse %>% mp_extract_tree(type="otutree")
> otutree
'treedata' S4 object'.
...@ phylo:
Phylogenetic tree with 770 tips and 768 internal nodes.
Tip labels:
35bfc371d940cffdc527b7b4dc954456, a95851baf426c85eae4419617db902a7, 08bd73939f7bfd85daf2eaee7e9c9bf8, a9e0ac523112f40942da575caf1f386e, 033511c7ff4fe93866075cfb9129aa3b, fc5b641a0b0408d99ddfb2a5ba64da59, ...
Node labels:
root, 1.000, 0.621, , 0.894, 0.627, ...
Rooted; includes branch lengths.
with the following features available:
'', 'RareAbundanceBySample', 'LDAupper', 'LDAmean', 'LDAlower',
'Sign_body.site', 'pvalue', 'fdr'.
# The associated data tibble abstraction: 1,538 × 10
# The 'node', 'label' and 'isTip' are from the phylo tree.
node label isTip RareAbundanceBy… LDAupper LDAmean LDAlower Sign_body.site
<int> <chr> <lgl> <list> <dbl> <dbl> <dbl> <chr>
1 1 35bfc3… TRUE <tibble [34 × 1… NA NA NA NA
2 2 a95851… TRUE <tibble [34 × 1… NA NA NA NA
3 3 08bd73… TRUE <tibble [34 × 1… NA NA NA NA
4 4 a9e0ac… TRUE <tibble [34 × 1… NA NA NA NA
5 5 033511… TRUE <tibble [34 × 1… NA NA NA NA
6 6 fc5b64… TRUE <tibble [34 × 1… NA NA NA NA
7 7 4980b8… TRUE <tibble [34 × 1… NA NA NA NA
8 8 e04721… TRUE <tibble [34 × 1… NA NA NA NA
9 9 3b74a9… TRUE <tibble [34 × 1… NA NA NA NA
10 10 96a7db… TRUE <tibble [34 × 1… NA NA NA NA
# … with 1,528 more rows, and 2 more variables: pvalue <dbl>, fdr <dbl>
> library(ggtree)
ggtree v3.1.3.992 For help: https://yulab-smu.top/treedata-book/
If you use ggtree in published research, please cite the most appropriate paper(s):
1. Guangchuang Yu. Using ggtree to visualize data on tree-like structures. Current Protocols in Bioinformatics, 2020, 69:e96. doi:10.1002/cpbi.96
2. Guangchuang Yu, Tommy Tsan-Yuk Lam, Huachen Zhu, Yi Guan. Two methods for mapping and visualizing associated data on phylogeny using ggtree. Molecular Biology and Evolution 2018, 35(12):3041-3043. doi:10.1093/molbev/msy194
3. Guangchuang Yu, David Smith, Huachen Zhu, Yi Guan, Tommy Tsan-Yuk Lam. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods in Ecology and Evolution 2017, 8(1):28-36. doi:10.1111/2041-210X.12628
> otutree %>% ggtree(layout="circular")
padingdun833
I have the question like above,I can't build mpse object using those files in the pictures!
cmetadea
Hi dear developer,
I read your "ggtreeExtra的开发及其在宏基因组上的应用" from YuLabSMU wechat channel. It is a very nice and helpful tutorial. But I am confused about the MPSE object which you use for downstream analysis. I can not find much useful information about MPSE from google.
I also tried to convert phloseq object to MPSE object with MicrobiotaProcess funtion 'as.MPSE'. But I believed I did not do it properly. Because I can not found Taxonomy Information after convert. On the other hand, I wonder if we can use the phylogenetic tree information from the phloseq object to draw the tree directly?
Thanks, Yuhao