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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 dataset 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.

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: 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.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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