Using Nucleus and TensorFlow for DNA Sequencing Error Correction

Editorial Note: This post is published with identical content on the Google DeepVariant blog. In this post, we formulate DNA sequencing error correction as a multiclass classification problem and propose two deep learning solutions. Our first approach corrects errors in a single read, whereas the second approach, shown in Figure 1, builds a consensus from several reads to predict the correct DNA sequence. Our Colab notebook tutorial implements the second approach using the Nucleus and TensorFlow libraries. Our goal is to show how Nucleus can be used alongside TensorFlow for solving machine learning problems in genomics.