Here is a good paper comparing various sequencing technologies and options. Wish they included PacBio. They have an interesting chart comparing k-mer frequencies from various technologies. That method will not work with PacBio however, because very few 31-mers stay intact with 85% indel rate in PacBio.
The fully annotated genome sequence of the European strain, 26695 was first published in 1997 and, in 1999, it was directly compared to the USA isolate J99, promoting two standard laboratory isolates for Helicobacter pylori (H. pylori) research. With the genomic scaffolds available from these important genomes and the advent of benchtop high-throughput sequencing technology, a bacterial genome can now be sequenced within a few days. We sequenced and analysed strains J99 and 26695 using the benchtop-sequencing machines Ion Torrent PGM and the Illumina MiSeq Nextera and Nextera XT methodologies. Using publically available algorithms, we analysed the raw data and interrogated both genomes by mapping the data and by de novo assembly. We compared the accuracy of the coding sequence assemblies to the originally published sequences. With the Ion Torrent PGM, we found an inherently high-error rate in the raw sequence data. Using the Illumina MiSeq, we found significantly more non-covered nucleotides when using the less expensive Illumina Nextera XT compared with the Illumina Nextera library creation method. We found the most accurate de novo assemblies using the Nextera technology, however, extracting an accurate multi-locus sequence type was inconsistent compared to the Ion Torrent PGM. We found the cagPAI failed to assemble onto a single contig in all technologies but was more accurate using the Nextera. Our results indicate the Illumina MiSeq Nextera method is the most accurate for de novo whole genome sequencing of H. pylori.
The paper also mentioned observing different GC-content from different technologies.
Unique 31-mers in the output sequence data are expected to be errors given there is adequate depth to cover each genome more than 50-times. To determine if these mapped unique 31-mers were similar in GC content to highly covered regions, we compared their GC content to 105, randomly chosen, highly frequent 31-mers (occurring at a frequency between 20 and 50). This analysis may provide insights as to the reason for the low coverage. We found significant differences in GC content across all sequencing technologies and library preparation methods (Figure S4 and Table 2). The GC content of the Ion Torrent mapped unique reads was significantly higher for both genomes, suggesting a technical reason for the lack of coverage. Interestingly, the GC content of unique 31-mers that map to the reference genomes derived by the Illumina library preparation methods (Nextera and Nextera XT) identified conflicting results.