Abstract
Background Unique Molecular Identifiers (UMI) are used in many experiments to find and remove PCR duplicates. Although there are many tools for solving the problem of deduplicating reads based on their finding reads with the same alignment coordinates and UMIs, many tools either cannot handle substitution errors, or require expensive pairwise UMI comparisons that do not efficiently scale to larger datasets.
Results We formulate the problem of deduplicating UMIs in a manner that enables optimizations to be made, and more efficient data structures to be used. We implement our data structures and optimizations in a tool called UMICollapse, which is able to deduplicate over one million unique UMIs of length 9 at a single alignment position in around 26 seconds.
Conclusions We present a new formulation of the UMI deduplication problem, and show that it can be solved faster, with more sophisticated data structures.
Footnotes
Updated experiments due to bug fix in code.