dada-class


A multi-item List with the following named values...
<ul>
<li>$denoised: Integer vector, named by sequence valued by abundance, of the denoised sequences.
 </li>
<li>$clustering: An informative data.frame containing information on each cluster.
 </li>
<li>$sequence: A character vector of each denoised sequence. Identical to names($denoised).
 </li>
<li>$quality: The average quality scores for each cluster (row) by position (col).
 </li>
<li>$map: Integer vector that maps the unique (index of derep$unique) to the denoised sequence (index of dada$denoised).
 </li>
<li>$birth_subs: A data.frame containing the substitutions at the birth of each new cluster.
 </li>
<li>$trans: The matrix of transitions by type (row), eg. A2A, A2C..., and quality score (col)
         observed in the final output of the dada algorithm.
 </li>
<li>$err_in: The err matrix used for this invocation of dada.
 </li>
<li>$err_out: The err matrix estimated from the output of dada. NULL if err_function not provided.
 </li>
<li>$opts: A list of the dada_opts used for this invocation of dada.
 </li>
<li>$call: The function call used for this invocation of dada.
</li>
</ul><p></p><p></p>

The dada2 package provides "OTU picking" functionality, but instead
of picking OTUs the DADA2 algorithm exactly infers samples sequences. The dada2
pipeline starts from demultiplexed fastq files, and outputs inferred sample
sequences and associated abundances after removing substitution and chimeric
errors. Taxonomic classification is also available via a native implementation
of the RDP classifier method.

Benjamin Callahan

dada2

Accurate, high-resolution sample inference from amplicon
sequencing data

dada-class function

A multi-item List with the following named values...
<ul><li>$denoised:</li></ul>{Integer vector, named by sequence valued by abundance, of the denoised sequences.}
 <item>$clustering:</item>{An informative data.frame containing information on each cluster.}
 <item>$sequence:</item>{A character vector of each denoised sequence. Identical to names($denoised).}
 <item>$quality:</item>{The average quality scores for each cluster (row) by position (col).}
 <item>$map:</item>{Integer vector that maps the unique (index of derep$unique) to the denoised sequence (index of dada$denoised).}
 <item>$birth_subs:</item>{A data.frame containing the substitutions at the birth of each new cluster.}
 <item>$trans:</item>{The matrix of transitions by type (row), eg. A2A, A2C..., and quality score (col)
         observed in the final output of the dada algorithm.}
 <item>$err_in:</item>{The err matrix used for this invocation of dada.}
 <item>$err_out:</item>{The err matrix estimated from the output of dada. NULL if err_function not provided.}
 <item>$opts:</item>{A list of the dada_opts used for this invocation of dada.}
 <item>$call:</item>{The function call used for this invocation of dada.}

dada-class: The object class returned by `dada`

Description

Arguments

See Also