3. Import Data & Demultiplex - DianaCarolinaVergara/16S-rRNA-Analysis GitHub Wiki

Import Data

With these commands you can transform your .fastq.gz files to .qza (the accepted format in Qiime).

The --type command depends on the seq you performed (e.g. paired-end, single-end) and how the sequences are writed (e.g. with or without quality). In this tutorial we use paired-end reads with the quality (CasavaEightSingleLanePerSample Format):

sampleID_barcode_lanenumber_read_setnumber.fastq.gz

Somethimes need to be renamed similarly to the below (examples from the Cassava 1.8 paired-end data importing tutorial):

e.g., L2S357_15_L001_R1_001.fastq.gz

e.g., L2S357_15_L001_R2_001.fastq.gz

The --input-path command sellects the folder that contains the fasta reads.

The --input-format depends on how or in what format are the files to be analyzed.

Code:

qiime tools import \

   --type 'SampleData[PairedEndSequencesWithQuality]' \

   --input-path lane1 \

   --input-format CasavaOneEightSingleLanePerSampleDirFmt \

   --output-path demux-paired-end.qza

Demultiplex

Demultiplexing refers to the step in processing where you’d use the barcode information in order to know which sequences came from which samples after they had all be sequenced together1.

i.e. Figure 1. Demuxlet: demultiplexing and doublet identification from single cell data.

e.g. Figure 1. Demuxlet: demultiplexing and doublet identification from single cell data (ref1)

Code:

qiime demux summarize \

  --i-data demux-paired-end.qza \

  --o-visualization demux.qzv

Here another examples of how Demultiplexing and Trimming Adapters from Reads with q2-cutadapt

https://forum.qiime2.org/t/demultiplexing-and-trimming-adapters-from-reads-with-q2-cutadapt/2313

References