Google AI variant caller goes deep on rice genomes
/Analyzing 3024 rice genomes characterized by DeepVariant
“Rice is an ideal candidate for study in genomics, not only because it’s one of the world’s most important food crops, but also because centuries of agricultural cross-breeding have created unique, geographically-induced differences. With the potential for global population growth and climate change to impact crop yields, the study of this genome has important social considerations.
This post explores how to identify and analyze different rice genome mutations with a tool called DeepVariant. To do this, we performed a re-analysis of the Rice 3Kdataset and have made the data publicly available as part of the Google Cloud Public Dataset Program pre-publication and under the terms of the Toronto Statement.
We aim to show how AI can improve food security by accelerating genetic enhancement to increase rice crop yield. According to the Food and Agriculture Organization of the United Nations, crop improvements will reduce the negative impact of climate change and loss of arable land on rice yields, as well as support an estimated 25% increase in rice demand by 2030.”
