do_sample_infer_step: Dereplicated Data and Infer Sample Sequence Variants

In erictleung/dada2HPCPipe: DADA2 HPC Workflow Wrapper

Description

Here is the main step in the DADA2 pipeline, which uses the 'dada()' function and dereplicate data.

Usage

do_sample_infer_step(filt_Fs, err_f, filt_Rs, err_r, name_samples)

Arguments

filt_Fs	filtered forward sequences
err_f	error rates from filtered forward sequences
filt_Rs	filtered forward sequences
err_r	error rates from filtered reverse sequences
name_samples	vector of sample names

Details

For DADA2 to work efficiently, samples sequences are dereplicated into "unique sequences" with corresponding counts of these sequences.

This step reduces compute time by eliminating redundant comparisons.

**Note**: DADA retains quality information associated with each unique sequence. It averages the sequences for each unique sequence. These quality scores are used in the error model.

It is intended to take the output filtered results from 'filterAndTrim()' into this function.

Value

Returns list of

mergers

merged paired reads

dadaFs

inferred sequence variants for forward sequences

dadaRs

inferred sequence variants for reverse sequences

References

See "Dereplication" http://benjjneb.github.io/dada2/tutorial.html#dereplication

See "Sample Inference" http://benjjneb.github.io/dada2/tutorial.html#sample-inference

Examples

do_sample_infer_step(filt_Fs, err_f, filt_Rs, err_r, name_samples)

erictleung/dada2HPCPipe documentation built on May 10, 2019, 1:19 p.m.