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RIFRAF: a frame-resolving consensus algorithm

Kemal Eren, Ben Murrell
doi: https://doi.org/10.1101/227520
Kemal Eren
Bioinformatics and Systems Biology, University of California San Diego,
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  • For correspondence: keren@ucsd.edu
Ben Murrell
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Abstract

Motivation Protein coding genes can be studied using long-read next generation sequencing. However, high rates of indel sequencing errors are problematic, corrupting the reading frame. Even the consensus of multiple independent sequence reads retains indel errors. To solve this problem, we introduce RIFRAF, a sequence consensus algorithm that takes a set of error-prone reads and a reference sequence and infers an accurate in-frame consensus. RIFRAF uses a novel structure, analogous to a two-layer hidden Markov model: the consensus is optimized to maximize alignment scores with both the set of noisy reads and with a reference. The template-to-reads component of the model encodes the preponderance of indels, and is sensitive to the per-base quality scores, giving greater weight to more accurate bases. The reference-to-template component of the model penalizes frame-destroying indels. A local search algorithm proceeds in stages to find the best consensus sequence for both objectives.

Results Using Pacific Biosciences SMRT sequences of NL4-3 env, we compare our approach to other consensus and frame correction methods. RIFRAF consistently finds a consensus sequence that is more accurate and in-frame, especially with small numbers of reads. It was able to perfectly reconstruct over 80% of consensus sequences from as few as three reads, whereas the best alternative required twice as many. RIFRAF is able to achieve these results and keep the consensus in-frame even with a distantly related reference sequence. Moreover, unlike other frame correction methods, RIFRAF can detect and keep true indels while removing erroneous ones.

Availability RIFRAF is implemented in Julia, and source code is publicly available at https://github.com/MurrellGroup/Rifraf.jl

Contact bmurrell{at}ucsd.edu

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted December 03, 2017.
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RIFRAF: a frame-resolving consensus algorithm
Kemal Eren, Ben Murrell
bioRxiv 227520; doi: https://doi.org/10.1101/227520
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RIFRAF: a frame-resolving consensus algorithm
Kemal Eren, Ben Murrell
bioRxiv 227520; doi: https://doi.org/10.1101/227520

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