Optical mapping and nanocoding are single molecule restriction mapping systems for interrogating genomic structure at a scale that cannot currently be achieved using DNA sequencing methods. In these mapping experiments, large DNA molecules approximately 500 kb are stretched, immobilized or confined, and then digested with a restriction endonuclease that cuts or nicks the DNA at its cognate sequence. The cut/nick sites are then observed through fluorescent microscopy and machine vision is used to estimate the length of the DNA fragments between consecutive sites. This produces, for each molecule, a barcode-like pattern comprising the ordered list of restriction fragment lengths

Despite the promise of the optical mapping and nanocoding systems, there are few open source tools for working with the data generated by these platforms. Most analyses rely on custom in-house software pipelines using proprietary software. In this dissertation we present open source software tools for the alignment and vizualization of restriction mapping data.

In this work we first present a review of the optical mapping and nanocoding systems and provide an overview of the current methods for aligning and assembling consensus restriction maps and their related applications.

Next, we present the Maligner software for the alignment of a query restriction pattern to a reference pattern. Alignment is a fundamental problem which is the first step in many downstream analyses, such as consensus map assembly or structural variant calling. The Maligner software features both a sensitive dynamic programming implementation and a faster but less sensitive index based mode of alignment. We compare the Maligner software to other available tools for the task of aligning a sequence contig assembly to a reference optical map and for aligning single molecule maps to a reference.

Next, we present a portable data visualization web application for visualizing pairwise alignments of restriction maps.

Finally, we present updates to the Maligner software to support partial alignments of single molecule maps, allowing for the clustering of compatible split map alignments to identify structural variants.