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population-diversity:microbiome-analysis-with-qiime2-using-illumina-paired-end-sequence-data [2020/03/30 14:22]
bngina [Importing data into Qiime2]
population-diversity:microbiome-analysis-with-qiime2-using-illumina-paired-end-sequence-data [2020/04/29 15:09] (current)
bngina [Qiime2 data filtering and feature (OTU) table construction]
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 </code> </code>
-We mentioned that qiime2 provides method to summarize and view artifacts by storing them as visualizations, .qzv, files. The ''.qzv'' files can be opened on any browser using [[ |qiime viewer]]. To view the imported data;+We mentioned that qiime2 provides method to summarize and view artifacts by storing them as visualizations, .qzv, files. The ''.qzv''  files can be opened on any browser using [[ |qiime viewer]]. To create visualization for the imported data;
 <code> <code>
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  --i-data  /home/mydir/qiime2_data/my_raw_data.qza \  --i-data  /home/mydir/qiime2_data/my_raw_data.qza \
  --o-visualization /home/mydir/qiime2_data/my_raw_data.qzv  --o-visualization /home/mydir/qiime2_data/my_raw_data.qzv
 +==== Qiime2 data filtering and feature (OTU) table construction ====
 +Qiime2 provides two pluggins/methods for filtering your sequences to the required quality and length.Sequence Variants are then selected from quality filtered data and the results are feature tables better known as OTU tables and the representative feature sequences. These methods are [[| Dada2]] and [[| Deblur]]. 
 +Important to keep in mind is the size of the amplified region covered by the primers used and what is the expected fragment length after read joining? This will determine the trim and truncate length parameters for dada2 and deblur pipelines.
 +=== Dada2 ===
 +The Dada2 pipeline detects and corrects illumina amplicon sequence data and additionally filters any phiX reads identified in sequencing data and also filter out any chimeric sequences. 
 +To see usage and parameters that can be adjusted get the help for the pluggin i.e
 +qiime dada2 --help
 +The data we are using is paired-end, hence we will use the [[|qiime dada2 denoise-paired]] method of the pluggin. 
 +A key parameter to be careful about is the //''--p-trunc-q''//, which is a Q-score value. This means that in filtering for base quality, while reading the sequence from left to right, as soon as it encounters a base with a Q-score lower that threshold, by default its set to 2, the read is truncated at that position.Be careful with this, best to leave it at the default.
 +The other key parameters in quality control of the sequences are those used to trim the forward, ''--p-trim-left-f''; ''--p-trunc-len-f'' and reverse '' --p-trim-left-r''; ''--p-trunc-len-r'' reads. The //''--p-trim-left-[f/r]''// tell qiime how many bases to trim from the beginning of the sequence, while the //''--p-trunc-len[f|r]''// tell qiime at what position the sequences should be truncated at the end. 
 +To determine what values to pass for these two parameters;
 +  *Review the Interactive Quality Plot tab in the //''demux.qzv''// file that was generated by ''qiime demux summarize'' after importing the data to trim of the poor quality bases. 
 +  *The expected fragment size after the reads are joined, particularly for the //''--p-trunc-len[f|r]''// Refer to the expected fragment length for the primers used to prepare the libraries for sequencing. For example if the expected fragment length for your sequences is 465bp, and lets say the insert size during the sequencing was 300bp. We would want to have a final length of at least 465by or more to have better chances of final sequences of full length for the alignment. Considering that more often than not the forward sequences from illumina sequences have better quality than the reverse sequences. We could use a //''--p-trunc-len-f''// of //''250''// and a //''--p-trunc-len-r''// of //''220''//. to have a final sequence length of //''470bp''//.
 +The command would therefore be
 +qiime dada2 denoise-paired \
 + --i-demultiplexed-seqs /home/mydir/qiime2_data/my_raw_data.qza \
 + --p-trim-left-f 0 \
 + --p-trim-left-r 0 \
 + --p-trunc-len-f 250 \
 + --p-trunc-len-r 220\
 + --o-table /home/mydir/qiime2_data/dada2_470_table.qza \
 + --o-representative-sequences /home/mydir/qiime2_data/dada2_470_rep-seqs.qza \
 + --o-denoising-stats /home/mydir/qiime2_data/dada2_470_denoising-stats.qza \
 + --p-n-threads 4
 +#summarise the features table to view it, 
 +qiime feature-table summarize \
 + --i-table /home/mydir/qiime2_data/dada2_470_table.qza \
 + --o-visualization /home/mydir/qiime2_data/dada2_470_table.qzv
 +#view a summary of the rep sequences
 +qiime feature-table tabulate-seqs \
 + --i-data  /home/mydir/qiime2_data/dada2_470_rep-seqs.qza \
 + --o-visualization  /home/mydir/qiime2_data/dada2_470_rep-seqs.qzv
 +#and also view the denoising statistics
 +qiime metadata tabulate \
 +  --m-input-file /home/mydir/qiime2_data/dada2_470_denoising-stats.qza \
 +  --o-visualization /home/mydir/qiime2_data/dada2_470_denoising-stats.qza
 </code> </code>
population-diversity/microbiome-analysis-with-qiime2-using-illumina-paired-end-sequence-data.1585578158.txt.gz · Last modified: 2020/03/30 14:22 by bngina