LoRDEC: Accurate and Efficient Long Read Error Correction

Readers may recall our post about Rayan Chikhi, Guillaume Rizk, Dominique Lavenier and their collaborators converting their efficient programs like Minia into an entire library with useful modules. Now others are building on top of GATB and LoRDEC is one success story. You can access the paper at this link (h/t: E. Rivals).

Motivation: PacBio single molecule real-time sequencing is a third- generation sequencing technique producing long reads, with comparatively lower throughput and higher error rate. Errors include numerous indels and complicate downstream analysis like mapping or de novo assembly. A hybrid strategy that takes advantage of the high accuracy of second-generation short reads has been proposed for correcting long reads. Mapping of short reads on long reads provides sufficient coverage to eliminate up to 99% of errors, however, at the expense of prohibitive running times and considerable amounts of disk and memory space.

Results: We present LoRDEC, a hybrid error correction method that builds a succinct de Bruijn graph representing the short reads, and seeks a corrective sequence for each erroneous region in the long reads by traversing chosen paths in the graph. In comparison, LoRDEC is at least six times faster and requires at least 93% less memory or disk space than available tools, while achieving comparable accuracy.

Availability and implementaion: LoRDEC is written in C++, tested on Linux platforms and freely available at http://atgc.lirmm.fr/lordec.

Readers may also find the following posts relevant.

Very Efficient Hybrid Assembler for PacBio Data

Cerulean: A Hybrid Assembly using High Throughput Short and Long Reads