Do you think I could have bias due to different DNA extraction kit, library preparation and Illumina version used?
The idea is to perform genome comparison of these different bacterial strains we have sequenced.
Yes. All kits have bias. All Illumina versions of anything (platform, software, etc) have bias too. So your data absolutely has bias, which is one reason it's best to only compare data using identical methodologies. If, for example, you wanted to do some kind of quantification with group A using kit W and sequencer X, and group B using kit Y and sequencer Z, your results would be complete garbage.
If all you care about is genome assembly, and not quantification, then it typically does not matter at all as long as you have sufficient coverage.
Bias happens everywhere, especially for different platforms, different kits or different panels.
Remember to normalize your data before you do further analysis.
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version 2.3.6
@Brian: Not sure if the sequencers will have bias (long as the same chemistry is used). I recall Illumina asserting that irrespective of machine, chemistry used the sequence one gets should be equivalent (that was before the advent of 2-color chemistry). The Q-scores may vary depending on chemistry/machine but the basecalls themselves should remain the same. If that had not been true then we would not have been able to use these technologies reliably.
Thanks for your answer @Brian. The idea of the project is to perform genome comparison between 20-30 bacterial strains, of course preceded by genome assembly. Some of them have already been sequenced. One with PacBio and the other 4 with illumina. Do you think I should convince my PI to trow all they work away and sequence all 20-30 strains using identical procedures?
Well, let me clarify my statement. It would only be a major problem if you are doing quantification, for example, trying to determine the relative abundance in a metagenome. There's no problem with assembly. Of course, you'll get different qualities of assemblies depending on your input data, and PacBio will better assemble the repetitive parts of the genome, but that's not an issue if you want to compare genomic features. It sounds like you are sequencing these as isolates, in which case you wouldn't be able to do quantification anyway.