The strollur package stores the data associated with your
Amplicon Sequence Analysis. This tutorial will explain how to save,
load, copy, export, and import your strollur object. If you
haven’t reviewed the Getting
Started tuturial, we recommend you start there.
Let’s use the strollur::miseq_sop_example() function to
create a strollur object from the Miseq SOP Example.
miseq <- strollur::miseq_sop_example()
#> Added 2425 sequences.
#> Assigned 2425 sequence abundances.
#> Assigned 2425 sequence taxonomies.
#> Assigned 531 otu bins.
#> Assigned 2425 asv bins.
#> Assigned 63 phylotype bins.
#> Assigned 19 samples to treatments.
#> Assigned 171 samples distances.
#> Assigned 531 otu bin taxonomies.
#> Assigned 531 otu bin representative sequences.
#> Added a metadata report.
#> Added 2 resource references.
#> Added a contigs_report report.
miseq
#> miseq_sop:
#>
#> starts ends nbases ambigs polymers numns numseqs
#> Minimum: 1 375 249 0 3 0 1.00
#> 2.5%-tile: 1 375 252 0 4 0 2850.05
#> 25%-tile: 1 375 252 0 4 0 28491.50
#> Median: 1 375 253 0 4 0 56982.00
#> 75%-tile: 1 375 253 0 5 0 85472.50
#> 97.5%-tile: 1 375 254 0 6 0 111113.95
#> Maximum: 1 375 256 0 6 0 113963.00
#> Mean: 1 375 252 0 4 0 56982.00
#>
#> Number of unique seqs: 2425
#> Total number of seqs: 113963
#>
#> Total number of samples: 19
#> Total number of treatments: 2
#> Total number of otus: 531
#> Total number of otu bin classifications: 531
#> Total number of asvs: 2425
#> Total number of asv bin classifications: 2425
#> Total number of phylotypes: 63
#> Total number of phylotype bin classifications: 63
#> Total number of sequence classifications: 2425
#> Total number of resource references: 2
#> Total number of custom reports: 2Saving and Loading
The strollur package has a function to save a dataset object as an
.rds file, strollur::save_dataset(), and a
function to create a dataset from an .rds file,
strollur::load_dataset(). Let’s use the miseq data object
to learn how to do that.
file_name <- file.path(tempdir(), "miseq_sop.rds")
strollur::save_dataset(miseq, file = file_name)
#> [1] "/tmp/RtmpK1B4SS/miseq_sop.rds"
miseq_from_rds <- strollur::load_dataset(file = file_name)
miseq_from_rds
#> miseq_sop:
#>
#> starts ends nbases ambigs polymers numns numseqs
#> Minimum: 1 375 249 0 3 0 1.00
#> 2.5%-tile: 1 375 252 0 4 0 2850.05
#> 25%-tile: 1 375 252 0 4 0 28491.50
#> Median: 1 375 253 0 4 0 56982.00
#> 75%-tile: 1 375 253 0 5 0 85472.50
#> 97.5%-tile: 1 375 254 0 6 0 111113.95
#> Maximum: 1 375 256 0 6 0 113963.00
#> Mean: 1 375 252 0 4 0 56982.00
#>
#> Number of unique seqs: 2425
#> Total number of seqs: 113963
#>
#> Total number of samples: 19
#> Total number of treatments: 2
#> Total number of otus: 531
#> Total number of otu bin classifications: 531
#> Total number of asvs: 2425
#> Total number of asv bin classifications: 2425
#> Total number of phylotypes: 63
#> Total number of phylotype bin classifications: 63
#> Total number of sequence classifications: 2425
#> Total number of resource references: 2
#> Total number of custom reports: 2
unlink(file_name)We can see that the summaries of miseq and miseq_from_rds are identical. Let’s modify miseq_from_rds to verify they are not referring to the same object. We will add clusters created by mothur using vsearch’s distance-based greedy clustering (dgc) algorithm.
dgc_data <-
strollur::read_mothur_list(list = strollur_example("final.dgc.list.gz"))
strollur::assign(miseq_from_rds, table = dgc_data, bin_type = "dgc")
#> Assigned 361 dgc bins.
miseq_from_rds
#> miseq_sop:
#>
#> starts ends nbases ambigs polymers numns numseqs
#> Minimum: 1 375 249 0 3 0 1.00
#> 2.5%-tile: 1 375 252 0 4 0 2850.05
#> 25%-tile: 1 375 252 0 4 0 28491.50
#> Median: 1 375 253 0 4 0 56982.00
#> 75%-tile: 1 375 253 0 5 0 85472.50
#> 97.5%-tile: 1 375 254 0 6 0 111113.95
#> Maximum: 1 375 256 0 6 0 113963.00
#> Mean: 1 375 252 0 4 0 56982.00
#>
#> Number of unique seqs: 2425
#> Total number of seqs: 113963
#>
#> Total number of samples: 19
#> Total number of treatments: 2
#> Total number of otus: 531
#> Total number of otu bin classifications: 531
#> Total number of asvs: 2425
#> Total number of asv bin classifications: 2425
#> Total number of phylotypes: 63
#> Total number of phylotype bin classifications: 63
#> Total number of dgcs: 361
#> Total number of dgc bin classifications: 361
#> Total number of sequence classifications: 2425
#> Total number of resource references: 2
#> Total number of custom reports: 2
miseq
#> miseq_sop:
#>
#> starts ends nbases ambigs polymers numns numseqs
#> Minimum: 1 375 249 0 3 0 1.00
#> 2.5%-tile: 1 375 252 0 4 0 2850.05
#> 25%-tile: 1 375 252 0 4 0 28491.50
#> Median: 1 375 253 0 4 0 56982.00
#> 75%-tile: 1 375 253 0 5 0 85472.50
#> 97.5%-tile: 1 375 254 0 6 0 111113.95
#> Maximum: 1 375 256 0 6 0 113963.00
#> Mean: 1 375 252 0 4 0 56982.00
#>
#> Number of unique seqs: 2425
#> Total number of seqs: 113963
#>
#> Total number of samples: 19
#> Total number of treatments: 2
#> Total number of otus: 531
#> Total number of otu bin classifications: 531
#> Total number of asvs: 2425
#> Total number of asv bin classifications: 2425
#> Total number of phylotypes: 63
#> Total number of phylotype bin classifications: 63
#> Total number of sequence classifications: 2425
#> Total number of resource references: 2
#> Total number of custom reports: 2We can see from the summary that 361 ‘dgc’ bins were added to miseq_from_rds and not to miseq.
Export and Import
The .rds file is in binary format and is not human readable.
You can use the strollur::export_dataset() to see a human
readable form of the raw data stored in the dataset. Let’s export
miseq and look at the table created.
table <- strollur::export_dataset(miseq)
str(table)
#> List of 16
#> $ sequence_data :'data.frame': 2425 obs. of 5 variables:
#> ..$ sequence_id : int [1:2425] 0 1 2 3 4 5 6 7 8 9 ...
#> ..$ sequence_name : chr [1:2425] "M00967_43_000000000-A3JHG_1_1101_10133_8460" "M00967_43_000000000-A3JHG_1_1101_10331_23332" "M00967_43_000000000-A3JHG_1_1101_10382_22128" "M00967_43_000000000-A3JHG_1_1101_11035_15765" ...
#> ..$ sequence : chr [1:2425] "TAC--GT-AG-GGG--GCA-A-G-C-G-T-T--AT-C-CGG-AT--TT-A-C-T--GG-GT--GT-A-AA-GG-GA-GC-G-TA-GGC-G-G-C-CA-T-G-C-AA-G-T-"| __truncated__ "TAC--GG-AG-GAT--GCG-A-G-C-G-T-T--AT-C-CGG-AT--TT-A-T-T--GG-GT--TT-A-AA-GG-GA-GC-G-CA-GGC-G-G-C-AT-G-G-C-AA-G-T-"| __truncated__ "TAC--GT-AG-GTA--GCA-A-G-C-G-T-T--GT-C-CGG-AT--TT-A-C-T--GG-GT--GT-A-AA-GG-GC-GT-G-TA-GCC-G-G-G-CT-T-A-C-AA-G-T-"| __truncated__ "TAC--GT-AG-GGG--GCA-A-G-C-G-T-T--AT-C-CGG-AT--TT-A-C-T--GG-GT--GT-A-AA-GG-GG-GC-G-TA-GAC-G-G-C-AG-T-G-C-AA-G-T-"| __truncated__ ...
#> ..$ taxonomy : chr [1:2425] "Bacteria(100);Firmicutes(100);Clostridia(100);Clostridiales(100);Lachnospiraceae(85);Lachnospiraceae_unclassified(85);" "Bacteria(100);Firmicutes(99);Clostridia(98);Clostridiales(98);Lachnospiraceae(95);Lachnospiraceae_unclassified(95);" "Bacteria(100);Firmicutes(100);Clostridia(100);Clostridiales(100);Ruminococcaceae(98);Ruminococcaceae_unclassified(98);" "Bacteria(100);Firmicutes(100);Clostridia(100);Clostridiales(100);Lachnospiraceae(100);Lachnospiraceae_unclassified(100);" ...
#> ..$ include_sequence: logi [1:2425] TRUE TRUE TRUE TRUE TRUE TRUE ...
#> $ sequence_report :'data.frame': 2425 obs. of 7 variables:
#> ..$ sequence_id : int [1:2425] 0 1 2 3 4 5 6 7 8 9 ...
#> ..$ start : int [1:2425] 1 1 1 1 1 1 1 1 1 1 ...
#> ..$ end : int [1:2425] 375 375 375 375 375 375 375 375 375 375 ...
#> ..$ length : int [1:2425] 253 253 253 252 253 252 253 253 252 252 ...
#> ..$ ambig : int [1:2425] 0 0 0 0 0 0 0 0 0 0 ...
#> ..$ longest_homopolymer: int [1:2425] 5 4 5 5 4 5 5 5 4 4 ...
#> ..$ num_n : int [1:2425] 0 0 0 0 0 0 0 0 0 0 ...
#> $ sequence_abundance_table :'data.frame': 5539 obs. of 4 variables:
#> ..$ sequence_id: int [1:5539] 0 0 0 0 0 0 0 0 0 0 ...
#> ..$ abundance : num [1:5539] 32 127 1 1 1 222 5 13 20 17 ...
#> ..$ sample : chr [1:5539] "F3D0" "F3D1" "F3D146" "F3D149" ...
#> ..$ treatment : chr [1:5539] "Early" "Early" "Late" "Late" ...
#> $ sample_distance_table :'data.frame': 171 obs. of 4 variables:
#> ..$ sample1 : chr [1:171] "F3D1" "F3D141" "F3D141" "F3D142" ...
#> ..$ sample2 : chr [1:171] "F3D0" "F3D0" "F3D1" "F3D0" ...
#> ..$ distance: num [1:171] 0.468 0.528 0.553 0.565 0.597 ...
#> ..$ include : logi [1:171] TRUE TRUE TRUE TRUE TRUE TRUE ...
#> $ otu_bin_data :'data.frame': 531 obs. of 5 variables:
#> ..$ bin_id : int [1:531] 0 1 2 3 4 5 6 7 8 9 ...
#> ..$ bin_name : chr [1:531] "Otu001" "Otu002" "Otu003" "Otu004" ...
#> ..$ abundance : num [1:531] 12288 8892 7794 7476 7450 ...
#> ..$ taxonomy : chr [1:531] "Bacteria(100);\"Bacteroidetes\"(100);\"Bacteroidia\"(100);\"Bacteroidales\"(100);\"Porphyromonadaceae\"(100);\""| __truncated__ "Bacteria(100);\"Bacteroidetes\"(100);\"Bacteroidia\"(100);\"Bacteroidales\"(100);\"Porphyromonadaceae\"(100);\""| __truncated__ "Bacteria(100);\"Bacteroidetes\"(100);\"Bacteroidia\"(100);\"Bacteroidales\"(100);\"Porphyromonadaceae\"(100);\""| __truncated__ "Bacteria(100);\"Bacteroidetes\"(100);\"Bacteroidia\"(100);\"Bacteroidales\"(100);\"Porphyromonadaceae\"(100);Barnesiella(100);" ...
#> ..$ include_bin: logi [1:531] TRUE TRUE TRUE TRUE TRUE TRUE ...
#> $ otu_sequence_bin_assignment :'data.frame': 2425 obs. of 2 variables:
#> ..$ bin_id : int [1:2425] 28 274 34 32 41 3 123 333 220 0 ...
#> ..$ sequence_id: int [1:2425] 0 1 2 3 4 5 6 7 8 9 ...
#> $ otu_bin_representative_sequence :'data.frame': 531 obs. of 2 variables:
#> ..$ bin_id : int [1:531] 0 1 2 3 4 5 6 7 8 9 ...
#> ..$ sequence_id: int [1:531] 592 439 21 373 1501 419 666 859 2027 87 ...
#> $ asv_bin_data :'data.frame': 2425 obs. of 5 variables:
#> ..$ bin_id : int [1:2425] 0 1 2 3 4 5 6 7 8 9 ...
#> ..$ bin_name : chr [1:2425] "Asv0001" "Asv0002" "Asv0003" "Asv0004" ...
#> ..$ abundance : num [1:2425] 12196 8829 7698 7436 7307 ...
#> ..$ taxonomy : chr [1:2425] "Bacteria(100);\"Bacteroidetes\"(100);\"Bacteroidia\"(100);\"Bacteroidales\"(100);\"Porphyromonadaceae\"(100);\""| __truncated__ "Bacteria(100);\"Bacteroidetes\"(100);\"Bacteroidia\"(100);\"Bacteroidales\"(100);\"Porphyromonadaceae\"(100);\""| __truncated__ "Bacteria(100);\"Bacteroidetes\"(100);\"Bacteroidia\"(100);\"Bacteroidales\"(100);\"Porphyromonadaceae\"(100);\""| __truncated__ "Bacteria(100);\"Bacteroidetes\"(100);\"Bacteroidia\"(100);\"Bacteroidales\"(100);\"Porphyromonadaceae\"(100);Barnesiella(100);" ...
#> ..$ include_bin: logi [1:2425] TRUE TRUE TRUE TRUE TRUE TRUE ...
#> $ asv_sequence_bin_assignment :'data.frame': 2425 obs. of 2 variables:
#> ..$ bin_id : int [1:2425] 27 2419 2404 2401 518 2382 2377 2372 2363 283 ...
#> ..$ sequence_id: int [1:2425] 0 1 2 3 4 5 6 7 8 9 ...
#> $ phylotype_bin_data :'data.frame': 63 obs. of 5 variables:
#> ..$ bin_id : int [1:63] 0 1 2 3 4 5 6 7 8 9 ...
#> ..$ bin_name : chr [1:63] "Phylo01" "Phylo02" "Phylo03" "Phylo04" ...
#> ..$ abundance : num [1:63] 21639 53147 2805 1773 5337 ...
#> ..$ taxonomy : chr [1:63] "Bacteria(100);Firmicutes(100);Clostridia(100);Clostridiales(100);Lachnospiraceae(100);Lachnospiraceae_unclassified(100);" "Bacteria(100);\"Bacteroidetes\"(100);\"Bacteroidia\"(100);\"Bacteroidales\"(100);\"Porphyromonadaceae\"(100);\""| __truncated__ "Bacteria(100);Firmicutes(100);Clostridia(100);Clostridiales(100);Ruminococcaceae(100);Ruminococcaceae_unclassified(100);" "Bacteria(100);Firmicutes(100);Clostridia(100);Clostridiales(100);Clostridiales_unclassified(100);Clostridiales_"| __truncated__ ...
#> ..$ include_bin: logi [1:63] TRUE TRUE TRUE TRUE TRUE TRUE ...
#> $ phylotype_sequence_bin_assignment:'data.frame': 2425 obs. of 2 variables:
#> ..$ bin_id : int [1:2425] 0 0 2 0 0 1 3 0 24 1 ...
#> ..$ sequence_id: int [1:2425] 0 1 2 3 4 5 6 7 8 9 ...
#> $ resource_reference :'data.frame': 2 obs. of 10 variables:
#> ..$ vendor : chr [1:2] "Schloss Lab - University of Michigan" "SILVA"
#> ..$ name : chr [1:2] "R phylotypr package" "silva.bacteria.fasta"
#> ..$ version : chr [1:2] "0.1.1" "1.38.1"
#> ..$ usage : chr [1:2] "classification of sequences" "alignment of sequences"
#> ..$ note : chr [1:2] "classification using Bayesian method" "alignment reference trimmed to V4 region"
#> ..$ method_url : chr [1:2] "doi:10.1128/mra.01144-24" "NA"
#> ..$ documentation_url: chr [1:2] "https://mothur.org/phylotypr/" "https://mothur.org/wiki/silva_reference_files/"
#> ..$ parameter : chr [1:2] "kmer_size=8,num_bootstraps=100,min_confidence=80" "NA"
#> ..$ citation : chr [1:2] "@article{doi:10.1128/AEM.00062-07, author = {Qiong Wang and George M. Garrity and James M. Tiedje and James R. "| __truncated__ "NA"
#> ..$ creation_date : chr [1:2] "2026-09-02" "2026-09-02"
#> $ contigs_report :'data.frame': 2425 obs. of 8 variables:
#> ..$ Name : chr [1:2425] "M00967_43_000000000-A3JHG_1_1101_10133_8460" "M00967_43_000000000-A3JHG_1_1101_10331_23332" "M00967_43_000000000-A3JHG_1_1101_10382_22128" "M00967_43_000000000-A3JHG_1_1101_11035_15765" ...
#> ..$ Length : num [1:2425] 253 253 253 252 253 252 253 253 252 252 ...
#> ..$ Overlap_Length : num [1:2425] 249 249 249 250 249 249 248 249 250 248 ...
#> ..$ Overlap_Start : num [1:2425] 2 2 2 1 2 2 3 2 1 3 ...
#> ..$ Overlap_End : num [1:2425] 251 251 251 251 251 251 251 251 251 251 ...
#> ..$ MisMatches : num [1:2425] 0 0 2 19 2 0 4 1 2 8 ...
#> ..$ Num_Ns : num [1:2425] 0 0 0 0 0 0 0 0 0 0 ...
#> ..$ Expected_Errors: num [1:2425] 0.00207 0.00231 0.01135 0.08721 0.00674 ...
#> ..- attr(*, "sequence_name")= chr "Name"
#> $ metadata :'data.frame': 19 obs. of 2 variables:
#> ..$ sample : chr [1:19] "F3D0" "F3D1" "F3D141" "F3D142" ...
#> ..$ days_post_wean: num [1:19] 0 1 141 142 143 144 145 146 147 148 ...
#> $ sequence_tree :List of 4
#> ..$ edge : int [1:4848, 1:2] 2426 2427 2427 2426 2428 2429 2429 2428 2430 2431 ...
#> ..$ edge.length: num [1:4848] NaN 0.00395 0.00395 0 0.00198 ...
#> ..$ Nnode : int 2424
#> ..$ tip.label : chr [1:2425] "M00967_43_000000000-A3JHG_1_1114_15727_25995" "M00967_43_000000000-A3JHG_1_2109_19976_22044" "M00967_43_000000000-A3JHG_1_1102_9244_9305" "M00967_43_000000000-A3JHG_1_2101_14159_9619" ...
#> ..- attr(*, "class")= chr "phylo"
#> ..- attr(*, "order")= chr "cladewise"
#> $ sample_tree :List of 5
#> ..$ edge : int [1:36, 1:2] 20 21 22 23 24 25 26 27 27 26 ...
#> ..$ edge.length: num [1:36] 0.03913 0.01741 0.02565 0.00379 0.01732 ...
#> ..$ Nnode : int 18
#> ..$ tip.label : chr [1:19] "F3D9" "F3D8" "F3D6" "F3D5" ...
#> ..$ root.edge : num 0.221
#> ..- attr(*, "class")= chr "phylo"
#> ..- attr(*, "order")= chr "cladewise"
#> - attr(*, "strollur_version")= chr "0.1.2"
#> - attr(*, "dataset_name")= chr "miseq_sop"Similarly to strollur::load_dataset(), you can use the
strollur::import_dataset() function to create a new dataset
object from the exported table.
miseq_import <- strollur::import_dataset(table = table)
#> Added 2425 sequences.
#> Assigned 2425 sequence taxonomies.
#> Assigned 2425 sequence abundances.
#> Assigned 531 otu bins.
#> Assigned 531 otu bin representative sequences.
#> Assigned 531 otu bin taxonomies.
#> Assigned 2425 asv bins.
#> Assigned 2425 asv bin taxonomies.
#> Assigned 63 phylotype bins.
#> Assigned 63 phylotype bin taxonomies.
#> Assigned 171 samples distances.
#> Added 2 resource references.
#> Added a contigs_report report.
#> Added a metadata report.
miseq_import
#> miseq_sop:
#>
#> starts ends nbases ambigs polymers numns numseqs
#> Minimum: 1 375 249 0 3 0 1.00
#> 2.5%-tile: 1 375 252 0 4 0 2850.05
#> 25%-tile: 1 375 252 0 4 0 28491.50
#> Median: 1 375 253 0 4 0 56982.00
#> 75%-tile: 1 375 253 0 5 0 85472.50
#> 97.5%-tile: 1 375 254 0 6 0 111113.95
#> Maximum: 1 375 256 0 6 0 113963.00
#> Mean: 1 375 252 0 4 0 56982.00
#>
#> Number of unique seqs: 2425
#> Total number of seqs: 113963
#>
#> Total number of samples: 19
#> Total number of treatments: 2
#> Total number of otus: 531
#> Total number of otu bin classifications: 531
#> Total number of asvs: 2425
#> Total number of asv bin classifications: 2425
#> Total number of phylotypes: 63
#> Total number of phylotype bin classifications: 63
#> Total number of sequence classifications: 2425
#> Total number of resource references: 2
#> Total number of custom reports: 2Again, we can see that the summary of miseq_import is identical to
the summary of miseq. Note, strollur::export_dataset and
strollur::import_dataset() is the best method to use to
convert an older version of the strollur_object to a newer
version.
Copy
Lastly, you can make a deep copy of your dataset using the
strollur::copy_dataset() function. Note, if you use an
assignment operator to copy it’s a shallow copy. The dataset object is
an R6 object to keep the memory usage low. First let’s learn how to use
the strollur::copy_dataset() function, then we will take a
closer look at how deep and shallow copying differ.
miseq_deep_copy <- copy_dataset(miseq)
miseq_shallow_copy <- miseqLet’s add the dgc_data to miseq_shallow_copy and then compare miseq, miseq_deep_copy, and mise_shallow_copy.
strollur::assign(miseq_shallow_copy, table = dgc_data, bin_type = "dgc")
#> Assigned 361 dgc bins.
miseq
#> miseq_sop:
#>
#> starts ends nbases ambigs polymers numns numseqs
#> Minimum: 1 375 249 0 3 0 1.00
#> 2.5%-tile: 1 375 252 0 4 0 2850.05
#> 25%-tile: 1 375 252 0 4 0 28491.50
#> Median: 1 375 253 0 4 0 56982.00
#> 75%-tile: 1 375 253 0 5 0 85472.50
#> 97.5%-tile: 1 375 254 0 6 0 111113.95
#> Maximum: 1 375 256 0 6 0 113963.00
#> Mean: 1 375 252 0 4 0 56982.00
#>
#> Number of unique seqs: 2425
#> Total number of seqs: 113963
#>
#> Total number of samples: 19
#> Total number of treatments: 2
#> Total number of otus: 531
#> Total number of otu bin classifications: 531
#> Total number of asvs: 2425
#> Total number of asv bin classifications: 2425
#> Total number of phylotypes: 63
#> Total number of phylotype bin classifications: 63
#> Total number of dgcs: 361
#> Total number of dgc bin classifications: 361
#> Total number of sequence classifications: 2425
#> Total number of resource references: 2
#> Total number of custom reports: 2
miseq_shallow_copy
#> miseq_sop:
#>
#> starts ends nbases ambigs polymers numns numseqs
#> Minimum: 1 375 249 0 3 0 1.00
#> 2.5%-tile: 1 375 252 0 4 0 2850.05
#> 25%-tile: 1 375 252 0 4 0 28491.50
#> Median: 1 375 253 0 4 0 56982.00
#> 75%-tile: 1 375 253 0 5 0 85472.50
#> 97.5%-tile: 1 375 254 0 6 0 111113.95
#> Maximum: 1 375 256 0 6 0 113963.00
#> Mean: 1 375 252 0 4 0 56982.00
#>
#> Number of unique seqs: 2425
#> Total number of seqs: 113963
#>
#> Total number of samples: 19
#> Total number of treatments: 2
#> Total number of otus: 531
#> Total number of otu bin classifications: 531
#> Total number of asvs: 2425
#> Total number of asv bin classifications: 2425
#> Total number of phylotypes: 63
#> Total number of phylotype bin classifications: 63
#> Total number of dgcs: 361
#> Total number of dgc bin classifications: 361
#> Total number of sequence classifications: 2425
#> Total number of resource references: 2
#> Total number of custom reports: 2
miseq_deep_copy
#> miseq_sop:
#>
#> starts ends nbases ambigs polymers numns numseqs
#> Minimum: 1 375 249 0 3 0 1.00
#> 2.5%-tile: 1 375 252 0 4 0 2850.05
#> 25%-tile: 1 375 252 0 4 0 28491.50
#> Median: 1 375 253 0 4 0 56982.00
#> 75%-tile: 1 375 253 0 5 0 85472.50
#> 97.5%-tile: 1 375 254 0 6 0 111113.95
#> Maximum: 1 375 256 0 6 0 113963.00
#> Mean: 1 375 252 0 4 0 56982.00
#>
#> Number of unique seqs: 2425
#> Total number of seqs: 113963
#>
#> Total number of samples: 19
#> Total number of treatments: 2
#> Total number of otus: 531
#> Total number of otu bin classifications: 531
#> Total number of asvs: 2425
#> Total number of asv bin classifications: 2425
#> Total number of phylotypes: 63
#> Total number of phylotype bin classifications: 63
#> Total number of sequence classifications: 2425
#> Total number of resource references: 2
#> Total number of custom reports: 2You can see from the summaries that the dgc_data was added to both miseq and miseq_shallow_copy because they actually reference the same object, but miseq_deep_copy was not modified.