The rchime package allows you to detect and remove chimeras from your dataset using a de novo approach or alternatively a reference model. This package uses code from the vsearch tools.
rchime() detect and remove chimeras from your strollur dataset object or
data.frameYou can install the CRAN version with:
install.packages("rchime")You can install the development version of rchime from GitHub with:
pak::pak("mothur/rchime")The rchime() function accepts strollur objects or data.frames
as inputs. Let’s create a strollur::strollur
object using files from mothur’s Miseq_SOP example
analysis. Then we will use the de novo method in
rchime() to detect and remove the chimeras from the
dataset.
fasta_data <- readRDS(rchime_example("miseq_fasta.rds"))
abundance_data <- readRDS(rchime_example("miseq_abundance.rds"))
data <- strollur::new_dataset("rchime de novo example")
strollur::add(data, table = fasta_data, type = "sequence")
#> Added 6084 sequences.
strollur::assign(data, table = abundance_data, type = "sequence_abundance")
#> Assigned 6084 sequence abundances.
chimera_report <- rchime(data)
#> ℹ The denovo method runs with a single processor.
#> Added a chimera_report report.
#> → rchime removed `10453` chimeras from your dataset.
#> → It took `4.26320099830627` seconds to detect and remove the chimeras.
data
#> rchime de novo example:
#>
#> starts ends nbases ambigs polymers numns numseqs
#> Minimum: 1 249 249 0 3 0 1.00
#> 2.5%-tile: 1 252 252 0 4 0 2955.05
#> 25%-tile: 1 252 252 0 4 0 29550.50
#> Median: 1 253 253 0 4 0 59101.00
#> 75%-tile: 1 253 253 0 5 0 88651.50
#> 97.5%-tile: 1 254 254 0 6 0 115246.95
#> Maximum: 1 256 256 0 8 0 118202.00
#> Mean: 1 252 252 0 4 0 59101.14
#>
#> scrap_summary:
#> type trash_code unique total
#> 1 sequence rchime-chimeras 3588 10453
#>
#> Number of unique seqs: 2496
#> Total number of seqs: 118202
#>
#> Total number of samples: 20
#> Total number of custom reports: 1Many thanks for the great work of the vsearch and uchime teams!
Rognes T, Flouri T, Nichols B, Quince C, Mahé F. (2016) VSEARCH: a versatile open source tool for metagenomics. PeerJ 4:e2584. doi: 10.7717/peerj.2584
Edgar,R.C., Haas,B.J., Clemente,J.C., Quince,C. and Knight,R. (2011), UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27:2194.
Please note that the rchime project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.