rchime

Overview

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 object or data.frame

Installation

You can install the CRAN version with:

install.packages("rchime")

Development version

You can install the development version of rchime from GitHub with:

pak::pak("mothur/rchime")

Usage

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.

rchime(data)
#> ℹ The de novo method runs with a single processor.
#> → rchime removed `10453` chimeras from your dataset.
#> → It took `4.24229192733765` 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   2956.03
#> 25%-tile:        1  252    252      0        4     0  29551.25
#> Median:          1  253    253      0        4     0  59101.50
#> 75%-tile:        1  253    253      0        5     0  88651.75
#> 97.5%-tile:      1  254    254      0        6     0 115246.97
#> Maximum:         1  256    256      0        8     0 118202.00
#> Mean:            1  252    252      0        4     0  59101.50
#> 
#> 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: 1

References

Many 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.

Code of Conduct

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.