Identifying Taxonomic Units in Metagenomic DNA Streams

With the emergence of portable DNA sequencers, such as Oxford Nanopore Technology MinION, metagenomic DNA sequencing can be performed in real-time and directly in the field. However, because metagenomic DNA analysis is computationally and memory intensive, and the current methods are designed for batch processing, the current metagenomic tools are not well suited for mobile devices.In this paper, we propose a new memory-efficient method to identify Operational Taxonomic Units (OTUs) in metagenomic DNA streams. Our method is based on finding connected components in overlap graphs constructed over a real-time stream of long DNA reads as produced by MinION platform. We propose an efficient algorithm to maintain connected components when an overlap graph is streamed, and show how redundant information can be removed from the stream by transitive closures. Through experiments on simulated and real-world metagenomic data, we demonstrate that the resulting solution is able to recover OTUs with high precision while remaining suitable for mobile computing devices.

AN EFFICIENT METHOD TO DETECT MUTUAL OVERLAP OF A LARGE SET OF UNORDERED IMAGES FOR STRUCTURE-FROM-MOTION

Recently, low-cost 3D reconstruction based on images has become a popular focus of photogrammetry and computer vision research. Methods which can handle an arbitrary geometric setup of a large number of unordered and convergent images are of particular interest. However, determining the mutual overlap poses a considerable challenge.<br><br> We propose a new method which was inspired by and improves upon methods employing random k-d forests for this task. Specifically, we first derive features from the images and then a random k-d forest is used to find the nearest neighbours in feature space. Subsequently, the degree of similarity between individual images, the image overlaps and thus images belonging to a common block are calculated as input to a structure-from-motion (sfm) pipeline. In our experiments we show the general applicability of the new method and compare it with other methods by analyzing the time efficiency. Orientations and 3D reconstructions were successfully conducted with our overlap graphs by sfm. The results show a speed-up of a factor of 80 compared to conventional pairwise matching, and of 8 and 2 compared to the VocMatch approach using 1 and 4 CPU, respectively.