prepare_taxa_charts.py: A Python program to automate generation of publication ready taxonomic pie chart images from QIIME
QIIME (Quantitative Insights Into Microbial Ecology) is one of the most popular open-source bioinformatics suite for performing metagenome, 16S rRNA amplicon and Internal Transcribed Spacer (ITS) data analysis. Although, it is very comprehensive and powerful tool, it lacks a method to provide publication ready taxonomic pie charts. The script plot_taxa_summary.py bundled with QIIME generate a html file and a folder containing taxonomic pie chart and legend as separate images. The images have randomly generated alphanumeric names. Therefore, it is difficult to associate the pie chart with the legend and the corresponding sample identifier. Even if the option to have the legend within the html file is selected while executing plot_taxa_summary.py, it is very tedious to crop a complete image (having both the pie chart and the legend) due to unequal image sizes. It requires a lot of time to manually prepare the pie charts for multiple samples for publication purpose. Moreover, there are chances of error while identifying the pie chart and legend pair due to random alphanumeric names of the images. To bypass all these bottlenecks and make this process efficient, we have developed a python based program, prepare_taxa_charts.py, to automate the renaming, cropping and merging of taxonomic pie chart and corresponding legend image into a single, good quality publication ready image. This program not only augments the functionality of plot_taxa_summary.py but is also very fast in terms of CPU time and user friendly.
Advancing our understanding of the soil microbial communities using QIIME software: a 16S data analysis pipeline
Rhazya stricta (Apocynaceae) is an important medicinal plant found commonly in South Asia (Pakistan, India and Afghanistan) and the Middle East (i.e. Saudi Arabia, Qatar, United Arab Emirates (UAE), Iran and Iraq). It is used in local folk medicine to treat many diseases such as diabetes mellitus, certain inflammatory conditions, and helminthiasis because leaves of Rhazya stricta contains more than 100 alkaloids with diverse pharmacological properties [1]. Furthermore, as a perennial, it is likely that the associated microflora in the rhizosphere and on the leaves is controlled by the plant itself via these gene products and compounds. Plants use an array of secondary metabolites to defend themselves against harmful organisms and to attract others that are beneficial [2].
Clinical chemical values and variations in Rasa Aragonesa ewes and lambs
Reference values of biochemical parameters in serum of Rasa Aragonesa ewes and their physiological variations were determined. Total proteins were 53.0–80.0 g/l, glucose 2.17–5.13 mmol/l, cholesterol 0.83–2.31 mmol/l, total bilirubin 1.85–6.49 μmol/l, urea 3.15–10.39 mmol/l, GGT 36–93 U/l (37°C), ALAT 11–33 U/l (37°C) and ASAT 71–209 U/l (37°C). Ewes were divided into three groups: A, 1- and 2-year-old ewes; B, ewes 3 and 4 years old; C, older ewes. Age had significant influence (P<0.05) on ASAT only during pregnancy, with higher levels for younger ewes. Blood parameters in lambs were determined at 5–10 d of life (nursing), 25 to 30 d of life receiving their mother's milk and 80–90 g of feed; and 45 to 50 d of life, weaned, receiving only solid feed. Serum urea and ALAT tended to increase with age, whereas total protein, globulins, cholesterol and GGT decreased with age. These values are of practical importance in the diagnosis of diseases and metabolic disorders in Rasa Aragonesa ewes and lambs under field conditions.