Graphs, often referred to as networks, offer a new visualisation paradigm for the analysis data generated from sequencing DNA or RNA. The approach showcased here uses sequence comparison algorithms to generate a similarity matrix between an assembly of reads mapping to given loci or assembled into a contig. The degree of sequence overlap between reads (similarity score) is used to calculate a network where nodes represent reads and edges their relationship to each other. When visualised using our advanced network analysis tools the network can be used to understand the structure of assemblies and how they relate to known genomic or RNA features.
Graph-based visualisation of data allows a researcher to better understand their data leading to the accelerated identification of issues with its assembly, as well as to examine complexities in sequence and transcript variation.
Graph generated from RNA-seq data. These includes the data from human tissue atlas with different type of tissue.
Roslin Institute, EH25 9RG Edinburgh, United Kingdom