Open lakhujanivijay opened 8 years ago
@lakhujanivijay, thanks a lot for your input and for your interest in QIIME!
We're currently working on QIIME 2, and QIIME 1 is in maintenance only mode, so we're not working on these types of new features. However, you can expect this in QIIME 2. To get some information about where we're going with QIIME 2 you can read my blog post on it, and for a more computationally technical introduction to the QIIME 2 alpha release you can see my SciPy 2016 presentation. We expect to have much improved taxonomic visualizations as part of QIIME 2, and one feature that we plan on is better integration of taxonomy figures and legends.
Thanks again for your interest in QIIME!
Dear QIIME team,
First of all, please accept my heartfelt thanks that you people developed such a user-friendly and comprehensive tool for 16S data analysis. We are into bioinformatics research and development, specially 16S rRNA/metagenomic sequencing data analysis and use QIIME very often. So far, we found it to be really fast and easy to use when compared with any other tool serving the same purpose.
One of the important aspect of our day to day work is to report the taxonomy of the OTUs selected using the taxonomic pie charts generated by
plot_taxa_summary.py
script. Though, the script serves the purpose of plotting the taxonomies, it always becomes difficult for us to crop the pie chart image and the corresponding legend image into one image (please find below an image for example purpose; it has been created in MS paint) having both of them (this is our standard way of delivering reports).Now, the problem is even bigger when there are say ~100 samples analysed using QIIME. In that case, we have ~100 pie charts and ~100 legend images to be cropped and compiled manually; which is very tedious and time consuming task.
We request this feature to output the pie chart and the legend in a single image file. We understand that the development team should be really busy with other developments and improvements and we appreciate their efforts, but implementation of this feature should be treated on priority for the next release. I am sure that other users might have also encountered this issue.
Again, my sincere thanks to the team for their hard work and efforts. You people are doing a great job!
Thanks & Regards Vijay Lakhujani Bioinformatician,
INDIA