It is a really exciting time for crop improvement with new tools available and a modernization agenda. ICRISAT and other CGIAR institutions are moving crop improvement into the 21st century, Dr Peter S Carberry, Director General, ICRISAT, echoed the sentiments of over 40 researchers from 14 countries who participated in a workshop on the use of R and R-QTL.
R is a freely available statistical programming language used mainly to analyze data and develop statistical software. The five-day 2nd International Workshop on R & R-QTL was organized by the Statistics, Bio-Informatics & Data Management (SBDM) team at ICRISAT with support from CRP-GLDC, EiB Module 5 and CGIAR’s Big Data Platform. The participants, mostly new users of R, said the workshop jump-started their learning.
“It is a statistical tool that can reveal how genes express themselves. The workshop helped me understand how data can be analyzed and how reports can be effectively explained,” says groundnut breeder Dr Kalule Okello David of National Semi-Arid Resources Research Institute in Uganda.
Trainers from ICRISAT, University of California, Davis, and University of Wisconsin School of Medicine and Public Health showed participants how R can be used for analyzing large datasets and for other applications including QTL-mapping.
Rice breeder Dr P Revathi from ICAR- Indian Institute of Rice Research says learning R is essential for QTL-mapping, a statistical process that helps correlate observed plant traits with the genes responsible.
“It is better to do QTL-mapping with a widely used tool. The workshop has provided a good introduction and participants now can go back to try it on their datasets. Besides QTL-mapping, I also plan to use R for graphical representation of data,” she says.
Chickpea genomic researcher Dr K R Soren of ICAR- Indian Institute of Pulses Research felt R’s prowess in graphical data presentation is one of its big draws. He said the learnings from the workshop will also benefit his students.
Dr Abhishek Rathore, Theme Leader, SBDM, termed the workshop a capacity building exercise for crop scientists across disciplines.
“The workshop was divided into four modules, each aimed at making the training comprehensive. The participants were taught to design experiments for phenotype analysis, QTL-mapping and how research can be reproduced with R,” he says.
The workshop also covered use of R to produce dynamic reports and for writing packages.