SHREC mines errors
SHREC: a short-read error correction method
Bioinformatics doi:10.1093/bioinformatics/btp379 (2009)
In their paper, the authors stress on the importance of read correction in sequencing applications -- such as resequencing and de novo assembly. They mention that error correction techniques for Sanger reads are outdated, and that novelty is required. The authors say that assemblers are better when there're no errors -- that they work well with error-corrected reads. This is incorrect, as both the resequencing and de novo assembly applications, allow consensus calling. The authors write that the Euler assembly program is 'established', meanwhile, nobody uses it. Over the Sanger reign, only a very few software were introduced for error correction in reads. Accordingly, the authors only cite two such works.
They compare SHREC with the error-correction component of EULER-SR and ALLPATHS -- two assemblers -- on simulated and real data. The paper is fun to read, and the described work is sound and easy to grasp. The author are careful and scientific, they define every terms they use. Their method outperforms the others, and the approach is easy to use on a computer. The authors generated random errors, and utilized Illumina reads -- which also include solely randomly-located errors. However, the use of coverage depth only addresses minor errors, and it ignores correlated errors, such as the 454's insertions and deletions in homopolymers.
The novelty of the paper is at the rendez-vous, the work is well-motivated, the software is open-source, and benchmarks are adequately reported.
Bioinformatics doi:10.1093/bioinformatics/btp379 (2009)
In their paper, the authors stress on the importance of read correction in sequencing applications -- such as resequencing and de novo assembly. They mention that error correction techniques for Sanger reads are outdated, and that novelty is required. The authors say that assemblers are better when there're no errors -- that they work well with error-corrected reads. This is incorrect, as both the resequencing and de novo assembly applications, allow consensus calling. The authors write that the Euler assembly program is 'established', meanwhile, nobody uses it. Over the Sanger reign, only a very few software were introduced for error correction in reads. Accordingly, the authors only cite two such works.
They compare SHREC with the error-correction component of EULER-SR and ALLPATHS -- two assemblers -- on simulated and real data. The paper is fun to read, and the described work is sound and easy to grasp. The author are careful and scientific, they define every terms they use. Their method outperforms the others, and the approach is easy to use on a computer. The authors generated random errors, and utilized Illumina reads -- which also include solely randomly-located errors. However, the use of coverage depth only addresses minor errors, and it ignores correlated errors, such as the 454's insertions and deletions in homopolymers.
The novelty of the paper is at the rendez-vous, the work is well-motivated, the software is open-source, and benchmarks are adequately reported.
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