PacBio: Debunking the Error Myth
Richard J Roberts, Mauricio O Carneiro and Michael C Schatz published a short commentary in Genome Biology that is worth taking a look at.
The power of SMRT sequencing data lies both in its long read lengths and in the random nature of the error process (Figure 2). It is true that individual reads contain a higher number of errors: approximately 11% to 14% or Q12 to Q15, compared with Q30 to Q35 from Illumina and other technologies. However, given sufficient depth (8x or more, say), SMRT sequencing provides a highly accurate statistically averaged consensus perspective of the genome, as it is highly unlikely that the same error will be randomly observed multiple times. Notoriously, other platforms have been found to suffer from systematic errors that need to be resolved by complementary methods before the final sequence is produced [16].
In a nutshell, smart (SMRT) people make mistakes and many smart persons are whimsical :)
In our understanding, more than the errors, the type of error made the PacBios so difficult for bioinformaticians. Bioinformatics tools and algorithms are designed to cope with SNPs, whereas PacBio data have mostly indels. That is why we took time to explain the point in the (still incomplete and error- prone) Pacbio tutorials.
