Hello,
I am trying to optimize my protocol for microbiome analysis using qiime2 2018.8.
I have data from Illumina Miseq PE 2x250 sequencing, presented in fastq format.
I uploaded reads in casava format. Next thing I have done was to denoise the reads using dada2 pipeline. I wanted also to filter out the reads using:
qiime feature-table filter-features
--i-table table-dada2-LB17_16.qza
--p-min-frequency 100
--p-min-samples 10
--o-filtered-table table-dada2-LB17_16-filtered.qza
Is that correct? Can I do so? What are the optimal rules for min frequency and min samples? I guess it all depends on samples but was my choice here correct?
table-dada2-LB17_16.qza (143.0 KB)
Obtained Feature Table and Feature Data I used in differential abundance analysis with gneiss. My aim was to generate proper heatmap.
I have several questions concerning the pipeline:
- The error:
qiime gneiss ols-regression
--p-formula "Group+Sex+Description"
--i-table balanses-LB17_16-filtered.qza
--i-tree hierarchy-LB17_16-filtered.qza
--m-metadata-file metadata-LB17_16.tsv
--o-visualization regression_summary-LB17_16-filtered.qzv
Plugin error from gneiss:
cannot convert float NaN to integer
Debug info has been saved to /tmp/qiime2-q2cli-err-2gou3btt.log
Metadata is here:
metadata-LB17_16.tsv (3.3 KB)
Yet, when I change only to one parameter -p-formula it passes but the outcome is strange.
Is my problem the metadata? I tried to format the file according to rules in tutorial.
- The heatmap
I generate it properly with a code:
qiime gneiss dendrogram-heatmap
--i-table composition-LB17-16-filtered.qza
--i-tree hierarchy-LB17_16-filtered.qza
--m-metadata-file metadata-LB17_16.tsv
--m-metadata-column Description
--p-color-map seismic
--o-visualization heatmap-LB17_16.qzv
I would like to modify it slighly eg. elognate it or correct the legend. How to do it? can I do it in qiime or should I use any external software? Can you suggest me something?
I would be very grateful for your support.
Joanna