Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Showing content from https://grunwaldlab.github.io/demulticoder/reference/assign_tax.html below:

Assign taxonomy functions — assign_tax • demulticoder

Assign taxonomy functions

assign_tax(
  analysis_setup,
  asv_abund_matrix,
  retrieve_files = FALSE,
  overwrite_existing = FALSE,
  db_rps10 = "oomycetedb.fasta",
  db_its = "fungidb.fasta",
  db_16S = "bacteriadb.fasta",
  db_other1 = "otherdb1.fasta",
  db_other2 = "otherdb2.fasta"
)

analysis_setup

An object containing directory paths and data tables, produced by the prepare_reads function

asv_abund_matrix

The final abundance matrix containing amplified sequence variants

retrieve_files

Logical, TRUE/FALSE whether to copy files from the temp directory to the output directory. Default is FALSE.

overwrite_existing

Logical, indicating whether to remove or overwrite existing files and directories from previous runs. Default is FALSE.

db_rps10

The reference database for the rps10 metabarcode

db_its

The reference database for the ITS metabarcode

db_16S

The SILVA 16S-rRNA reference database provided by the user

db_other1

The reference database for other metabarcode 1 (assumes format is like SILVA DB entries)

db_other2

The reference database for other metabarcode 2 (assumes format is like SILVA DB entries)

Taxonomic assignments of each unique ASV sequence

At this point, 'DADA2' function assignTaxonomy is used to assign taxonomy to the inferred ASVs.

# \donttest{
# Assign taxonomies to ASVs on by metabarcode
analysis_setup <- prepare_reads(
  data_directory = system.file("extdata", package = "demulticoder"),
  output_directory = tempdir(),
  overwrite_existing = TRUE
)
#> Existing files found in the output directory. Overwriting existing files.
#> Rows: 2 Columns: 25
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr  (3): primer_name, forward, reverse
#> dbl (18): minCutadaptlength, maxN, maxEE_forward, maxEE_reverse, truncLen_fo...
#> lgl  (4): already_trimmed, count_all_samples, multithread, verbose
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> Rows: 2 Columns: 25
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr  (3): primer_name, forward, reverse
#> dbl (18): minCutadaptlength, maxN, maxEE_forward, maxEE_reverse, truncLen_fo...
#> lgl  (4): already_trimmed, count_all_samples, multithread, verbose
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> Rows: 4 Columns: 3
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (3): sample_name, primer_name, organism
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> Creating output directory: /tmp/RtmpAtZc28/demulticoder_run/prefiltered_sequences

cut_trim(
analysis_setup,
cutadapt_path="/usr/bin/cutadapt",
overwrite_existing = TRUE
)
#> Running cutadapt 3.5 for its sequence data

#> Running cutadapt 3.5 for rps10 sequence data

make_asv_abund_matrix(
analysis_setup,
overwrite_existing = TRUE
)
#> 80608 total bases in 307 reads from 2 samples will be used for learning the error rates.
#> Error rate plot for the  Forward  read of primer pair  its
#> Warning: log-10 transformation introduced infinite values.
#> Sample 1 - 163 reads in 84 unique sequences.
#> Sample 2 - 144 reads in 96 unique sequences.
#> 82114 total bases in 307 reads from 2 samples will be used for learning the error rates.
#> Error rate plot for the  Reverse  read of primer pair  its
#> Warning: log-10 transformation introduced infinite values.
#> Sample 1 - 163 reads in 128 unique sequences.
#> Sample 2 - 144 reads in 119 unique sequences.


#> 91897 total bases in 327 reads from 2 samples will be used for learning the error rates.
#> Error rate plot for the  Forward  read of primer pair  rps10
#> Warning: log-10 transformation introduced infinite values.
#> Sample 1 - 145 reads in 107 unique sequences.
#> Sample 2 - 182 reads in 133 unique sequences.
#> 91567 total bases in 327 reads from 2 samples will be used for learning the error rates.
#> Error rate plot for the  Reverse  read of primer pair  rps10
#> Warning: log-10 transformation introduced infinite values.
#> Sample 1 - 145 reads in 114 unique sequences.
#> Sample 2 - 182 reads in 170 unique sequences.


#> $its
#> [1] "/tmp/RtmpAtZc28/demulticoder_run/asvabund_matrixDADA2_its.RData"
#> 
#> $rps10
#> [1] "/tmp/RtmpAtZc28/demulticoder_run/asvabund_matrixDADA2_rps10.RData"
#> 
assign_tax(
analysis_setup,
asv_abund_matrix,
retrieve_files=FALSE,
overwrite_existing = TRUE
)
#> Tracking read counts:
#>   samplename_barcode input filtered denoisedF denoisedR merged nonchim
#> 1             S1_its   299      163       146       141    132     132
#> 2             S2_its   235      144       113        99     99      99
#> Tracking read counts:
#>   samplename_barcode input filtered denoisedF denoisedR merged nonchim
#> 1           S1_rps10   196      145       145       145    145     145
#> 2           S2_rps10   253      182       181       181    181     181
# }

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4