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Tranform files to the microtable object in microeco package

License: GNU General Public License v3.0

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how can i add phylogenetic tree to the microtable object when I use the file from QIIME2

Phyloseq object to microtable

Hi,
I was trying to convert a phyloseq object to your microtable class, but I run into this error:

> library(microeco)
> meco = phyloseq2meco(phytted)
Error in tax_table_trans %<>% tidy_taxonomy : 
  lazy-load database '/home/rob/R/x86_64-pc-linux-gnu-library/4.0/microeco/R/microeco.rdb' is corrupt
In addition: Warning messages:
1: In tax_table_trans %<>% tidy_taxonomy :
  restarting interrupted promise evaluation
2: In tax_table_trans %<>% tidy_taxonomy :
  internal error -3 in R_decompress1

I tried to reinstall the package microeco package but it did not help. I should add that I had no problem converting the same phyloseq object prior to the latest updates (so when the function phyloseq2meco was still in the main package).

> sessionInfo()
R version 4.0.2 (2020-06-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: elementary OS 5.1.7 Hera

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so

locale:
 [1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C               LC_TIME=de_IT.UTF-8       
 [4] LC_COLLATE=en_GB.UTF-8     LC_MONETARY=de_IT.UTF-8    LC_MESSAGES=en_GB.UTF-8   
 [7] LC_PAPER=de_IT.UTF-8       LC_NAME=C                  LC_ADDRESS=C              
[10] LC_TELEPHONE=C             LC_MEASUREMENT=de_IT.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] file2meco_0.1.1             microeco_0.4.1              MicrobiotaProcess_1.2.2    
 [4] doParallel_1.0.16           iterators_1.0.13            foreach_1.5.1              
 [7] nord_1.0.0                  DECIPHER_2.18.1             RSQLite_2.2.7              
[10] Biostrings_2.58.0           XVector_0.30.0              phangorn_2.7.0             
[13] here_1.0.1                  SRS_0.2.2                   shinybusy_0.2.2            
[16] shinycssloaders_1.0.0       DT_0.18                     shiny_1.6.0                
[19] hrbrthemes_0.8.0            patchwork_1.1.1             ggpubr_0.4.0               
[22] DESeq2_1.30.1               SummarizedExperiment_1.20.0 Biobase_2.50.0             
[25] MatrixGenerics_1.2.1        matrixStats_0.59.0          GenomicRanges_1.42.0       
[28] GenomeInfoDb_1.26.7         IRanges_2.24.1              S4Vectors_0.28.1           
[31] BiocGenerics_0.36.1         microbiome_1.12.0           ape_5.5                    
[34] vegan_2.5-7                 lattice_0.20-44             permute_0.9-5              
[37] phyloseq_1.34.0             forcats_0.5.1               stringr_1.4.0              
[40] dplyr_1.0.7                 purrr_0.3.4                 readr_1.4.0                
[43] tidyr_1.1.3                 tibble_3.1.2                ggplot2_3.3.5              
[46] tidyverse_1.3.1             decontam_1.10.0             qiime2R_0.99.35            
[49] devtools_2.4.2              usethis_2.0.1               BiocManager_1.30.16        
[52] pacman_0.5.1               

loaded via a namespace (and not attached):
  [1] bit64_4.0.5            knitr_1.33             multcomp_1.4-17        DelayedArray_0.16.3   
  [5] data.table_1.14.0      rpart_4.1-15           RCurl_1.98-1.3         generics_0.1.0        
  [9] TH.data_1.0-10         callr_3.7.0            cowplot_1.1.1          bit_4.0.4             
 [13] xml2_1.3.2             lubridate_1.7.10       httpuv_1.6.1           ggsci_2.9             
 [17] assertthat_0.2.1       xfun_0.24              hms_1.1.0              evaluate_0.14         
 [21] promises_1.2.0.1       fansi_0.5.0            Rmisc_1.5              dbplyr_2.1.1          
 [25] readxl_1.3.1           igraph_1.2.6           DBI_1.1.1              geneplotter_1.68.0    
 [29] htmlwidgets_1.5.3      reshape_0.8.8          ellipsis_0.3.2         backports_1.2.1       
 [33] annotate_1.68.0        libcoin_1.0-8          vctrs_0.3.8            remotes_2.4.0         
 [37] abind_1.4-5            cachem_1.0.5           withr_2.4.2            checkmate_2.0.0       
 [41] treeio_1.17.0          prettyunits_1.1.1      cluster_2.1.2          lazyeval_0.2.2        
 [45] crayon_1.4.1           genefilter_1.72.1      labeling_0.4.2         pkgconfig_2.0.3       
 [49] zCompositions_1.3.4    nlme_3.1-152           pkgload_1.2.1          nnet_7.3-16           
 [53] rlang_0.4.11           lifecycle_1.0.0        sandwich_3.0-1         extrafontdb_1.0       
 [57] modelr_0.1.8           cellranger_1.1.0       rprojroot_2.0.2        aplot_0.0.6           
 [61] Matrix_1.3-4           carData_3.0-4          Rhdf5lib_1.12.1        zoo_1.8-9             
 [65] reprex_2.0.0           base64enc_0.1-3        processx_3.5.2         png_0.1-7             
 [69] bitops_1.0-7           rhdf5filters_1.2.1     blob_1.2.1             coin_1.4-1            
 [73] jpeg_0.1-8.1           rstatix_0.7.0          ggsignif_0.6.2         scales_1.1.1          
 [77] memoise_2.0.0          magrittr_2.0.1         plyr_1.8.6             zlibbioc_1.36.0       
 [81] compiler_4.0.2         tinytex_0.32           RColorBrewer_1.1-2     ggstar_1.0.2          
 [85] cli_2.5.0              ade4_1.7-17            ps_1.6.0               htmlTable_2.2.1       
 [89] Formula_1.2-4          MASS_7.3-54            mgcv_1.8-36            tidyselect_1.1.1      
 [93] stringi_1.6.2          yaml_2.2.1             locfit_1.5-9.4         ggrepel_0.9.1         
 [97] latticeExtra_0.6-29    grid_4.0.2             fastmatch_1.1-0        tools_4.0.2           
[101] rio_0.5.27             rstudioapi_0.13        foreign_0.8-81         gridExtra_2.3         
[105] farver_2.1.0           Rtsne_0.15             rvcheck_0.1.8          digest_0.6.27         
[109] quadprog_1.5-8         Rcpp_1.0.6             car_3.0-10             broom_0.7.7           
[113] later_1.2.0            httr_1.4.2             gdtools_0.2.3          AnnotationDbi_1.52.0  
[117] colorspace_2.0-2       rvest_1.0.0            XML_3.99-0.6           fs_1.5.0              
[121] truncnorm_1.0-8        splines_4.0.2          tidytree_0.3.4         multtest_2.46.0       
[125] sessioninfo_1.1.1      systemfonts_1.0.2      xtable_1.8-4           ggtree_3.1.0          
[129] jsonlite_1.7.2         modeltools_0.2-23      testthat_3.0.3         R6_2.5.0              
[133] Hmisc_4.5-0            NADA_1.6-1.1           pillar_1.6.1           htmltools_0.5.1.1     
[137] mime_0.10              glue_1.4.2             fastmap_1.1.0          BiocParallel_1.24.1   
[141] codetools_0.2-18       pkgbuild_1.2.0         mvtnorm_1.1-2          utf8_1.2.1            
[145] curl_4.3.1             gtools_3.9.2           zip_2.2.0              openxlsx_4.2.4        
[149] Rttf2pt1_1.3.8         survival_3.2-11        rmarkdown_2.9          desc_1.3.0            
[153] biomformat_1.18.0      munsell_0.5.0          rhdf5_2.34.0           GenomeInfoDbData_1.2.4
[157] haven_2.4.1            reshape2_1.4.4         gtable_0.3.0           extrafont_0.17

after transferring QIIME2 files to microtable, how can I make the file as the dataset, which is used in the downstream analyse?

phyloseq2meco

Hi,

I got this error:
Error in tax_table_trans %<>% tidy_taxonomy :
lazy-load database '/Library/Frameworks/R.framework/Versions/4.0/Resources/library/microeco/R/microeco.rdb' is corrupt
In addition: Warning messages:
1: In tax_table_trans %<>% tidy_taxonomy :
restarting interrupted promise evaluation
2: In tax_table_trans %<>% tidy_taxonomy :
internal error -3 in R_decompress1

Why is it happening?:(

import ASV sequences rep_fasta using phyloseq2meco

Dear @ChiLiubio,

Thanks for this game changing R package.
I am trying to import a phyloseq object using file2meco::phyloseq2meco.

My initial phyloseq object contains ASV sequences refseq() but it is missing from the microtable-class object generated using microtable-class object file2meco::phyloseq2meco.

physeq
phyloseq-class experiment-level object
otu_table()   OTU Table:         [ 64 taxa and 116 samples ]
sample_data() Sample Data:       [ 116 samples by 26 sample variables ]
tax_table()   Taxonomy Table:    [ 64 taxa by 7 taxonomic ranks ]
phy_tree()    Phylogenetic Tree: [ 64 tips and 63 internal nodes ]
refseq()      DNAStringSet:      [ 64 reference sequences ]

 physeq %>%
    file2meco::phyloseq2meco(.) -> data

data
microtable-class object:
sample_table have 116 rows and 26 columns
otu_table have 64 rows and 116 columns
tax_table have 64 rows and 7 columns
phylo_tree have 64 tips

Is it expected? How ot fix this?

Thanks

#Error in read_qza(feature_table) : Path to artifact (.qza) not provided.

recently, I met a new problem with loading the QIIME2 data. My working directory is

setwd("~/24h_sampler_squencing/time_period_R/24h_1h/microeco")

Dataset is set as:

dataset <- qiime2meco(ASV_data = "/24h_sampler_squencing/time_period_R/24h_1h/microeco/dada2_table.qza",
sample_data = "/24h_sampler_squencing/time_period_R/24h_1h/microeco/sample-metadata.tsv",
taxonomy_data = "/24h_sampler_squencing/time_period_R/24h_1h/microeco/taxonomy.qza",
phylo_tree = "/24h_sampler_squencing/time_period_R/24h_1h/microeco/tree.qza")
dataset

when I ran these codes in R, it showed:
Error in read_qza(feature_table) : Path to artifact (.qza) not provided.

I think it is the whole pathway, I don't know how to solve this problem. I even tried the code and data which I worked a long time ago, but it didn't work this time.
I feel very confused.
Hope you can help me solve this problem.
Thank you

deseq2 to microtable

Hi,
Is it possible to convert deseq2 output to microecotable format for analysis in microeco?

Error in file.exists(file) : object 'data2_table.qza' not found

setwd("~/squencing_analyze/R_microeco_package")
qiime2meco(ASV_data = data2_table.qza, sample_data = sample-metadata.tvs, taxonomy_data = taxonomy.qza, phylo_tree = tree.qza)
Error in file.exists(file) : object 'data2_table.qza' not found.

I feel confused about how to transfer my QIIME2 data to microtable? Under my working directory, it shows the error above.

trans_beta error

we first create an object and select PCoA for ordination

t1 <- trans_beta$new(dataset = dataset, group = "Watermass", measure = "bray", ordination = "PCoA")

t1$res_ordination is the ordination result list

class(t1$res_ordination)

showing error like this 
Error in initialize(...) : unused argument (ordination = "PCoA")

Support for (Tree)SummarizedExperiment?

(Tree)SummarizedExperiment (Huang et al. 2021) is becoming increasingly common in microbiome data science in R/Bioconductor. Would it be possible to add support for this, like treese2meco or se2meco function?

Conversion between microtable and phyloseq

Hi,

I made a full microtable, but after the conversion the phyloseq object have lost one sample and representative sequences (all slot is lost).
What might be the problem?

Where does MetaCyc_pathway_map come from?

Dear Liu,
Thank you for making such a good R package. I was using PICRUST2's Metacyc to predict 16S functionality and found that your example file has Metacyc's metacyc hierarchy MetaCyc_pathway_map. I would like to ask where is the source of this hierarchy file? Does it include all metabolic pathways on the MetACYC https://biocyc.org/ECOLI/class-tree?object=Pathways As far as I know, there may be a metabolic pathway on the website that belongs to a different category in the same hierarchy on the website, and your sample files seem to correspond one to one.
Also, can all results of PicRust Metacyc be classified to different level using the MetaCyc_pathway_map file?

# MetaCyc pathway output
tmp_file_path <- system.file("extdata", "example_PICRUSt2_MetaCyc_path_abun_unstrat.tsv", package="file2meco")
pathway_table <- read.delim(tmp_file_path, row.names = 1)
data("MetaCyc_pathway_map")
tmp <- microtable$new(otu_table = pathway_table, tax_table = MetaCyc_pathway_map)
tmp$tidy_dataset()
tmp

trans_env class error

Hello I received this error when working with the trans_env class when running this command:
t1 <- trans_env$new(dataset = dataset, add_data = env_data_16S[, 4:11])

Error in initialize(...) : No sample names of sample_table found in env_data! Please chech the names of env_data!

At first I got it with my own data set but then went back to the example data provided (https://chiliubio.github.io/microeco/#trans_env_class) and received the same error with the data provided.

Can you give an explination on how the sample_table works?

QIIME2 files to microtable?

I tried to run the example that was provided and the output was:

abund_file_path <- system.file("extdata", "dada2_table.qza", package="file2meco")
sample_file_path <- system.file("extdata", "sample-metadata.tsv", package="file2meco")
taxonomy_file_path <- system.file("extdata", "taxonomy.qza", package="file2meco")
rep_fasta_path <- system.file("extdata", "dada2_rep_set.qza", package="file2meco")
phylo_file_path <- system.file("extdata", "tree.qza", package="file2meco")
qiime2meco(ASV_data = abund_file_path)
Error in initialize(...) : unused argument (rep_fasta = NULL)
qiime2meco(ASV_data = abund_file_path, sample_data = sample_file_path, taxonomy_data = taxonomy_file_path)
Error in initialize(...) : unused argument (rep_fasta = NULL)
qiime2meco(ASV_data = abund_file_path, sample_data = sample_file_path, taxonomy_data = taxonomy_file_path, phylo_tree = phylo_file_path, rep_fasta = rep_fasta_path)
Error in FUN(X[[i]], ...) :
numbers of left and right parentheses in Newick string not equal

I then tried to run it on my own files and got two different errors:

Error in initialize(...) : unused argument (rep_fasta = NULL)
Error in initialize(...) :
unused argument (rep_fasta = list(c("t", "a", "c", "g", "g", "a", "g", "g", "a", "t", "c", "c", "g", "a", "g", "c", "g", "t", "t", "a", "t", "c", "c", "g", "g", "a", "t", "t", "t", "a", "t", "t", "g", "g", "g", "t", "t", "t", "a", "a", "a", "g", "g", "g", "a", "g", "c", "g", "t", "a", "g", "g", "t", "g", "g", "a", "c", "a", "g", "t", "t", "a", "a", "g", "t", "c", "a", "g", "t", "t", "g", "t", "g", "a", "a", "a", "g", "t", "t", "t", "g", "c", "g", "g", "c", "t", "c", "a", "a", "c", "c", "g", "t", "a", "a",
"a", "a", "t", "t", "g", "c", "a", "g", "t", "t", "g", "a", "t", "a", "c", "t", "g", "g", "c", "t", "g", "t", "c", "t", "t", "g", "a", "g", "t", "a", "c", "a", "g", "t", "a", "g", "a", "g", "g", "t", "g", "g", "g", "c", "g", "g", "a", "a", "t", "t", "c", "g", "t", "g", "g"), c("t", "a", "c", "g", "g", "a", "g", "g", "a", "t", "c", "c", "g", "a", "g", "c", "g", "t", "t", "a", "t", "c", "c", "g", "g", "a", "t", "t", "t", "a", "t", "t", "g", "g", "g", "t", "t", "t", "a", "a",

Am I doing something wrong? I am a student and new to programming.

chiliubio / file2meco Goto Github PK

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file2meco's Issues

we first create an object and select PCoA for ordination

t1$res_ordination is the ordination result list

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