Plasmid ATLAS: plasmid visual analytics and identification in high-throughput sequencing data

Abstract

Plasmid ATLAS (pATLAS, http://www.patlas.site) provides an easy-to-use web accessible database with visual analytics tools to explore the relationships of plasmids available in NCBI's RefSeq database. pATLAS has two main goals: (i) to provide an easy way to search for plasmids deposited in NCBI RefSeq and their associated metadata; (ii) to visualize the relationships of plasmids in a graph, allowing the exploration of plasmid evolution. pATLAS allows searching by plasmid name, bacterial host taxa, antibiotic resistance and virulence genes, plasmid families, and by sequence length and similarity. pATLAS is also able to represent in the plasmid network, plasmid sets identified by external pipelines using mapping, mash screen or assembly from high-throughput sequencing data. By representing the identified hits within the network of relationships between plasmids, allowing the possibility of removing redundant results, and by taking advantage of the browsing capabilities of pATLAS, users can more easily interpret the pipelines' results. All these analyses can be saved to a JSON file for sharing and future re-evaluation. Furthermore, by offering a REST-API, the pATLAS database and network display are easily accessible by other interfaces or pipelines.

Figure 1.

Schematic representation of pATLAS (A) database creation in the backend and (B) processing of external requests and file imports via the frontend and REST API in the backend.

Figure 2.

Example of an annotation plot showing the annotations for a given plasmid appearing when its node was clicked in the network of plasmids.

Figure 3.

Identifying plasmids related to imported sequence results. Plasmids highlighted in darker red are those with higher percentages of either sequence coverage of (using mapping approaches) or sequence identity with (using mash approaches) imported sequences. If the ‘redundancy removal’ option is used plasmids to remove the highlight on plasmids that are deemed to be less likely to be present in the imported HTS data (with a mash distance of <0.1 between them, using the equations described in this manuscript), compared with other linked plasmids.

Figure 4.

Example of table with metadata available for the selected plasmids in the network of plasmids.

Figure 5.

Example bar plot showing length distribution of selected plasmids. The plot is interactive and changes dynamically by highlighting the selection in the various series.