Hi guys,
We are using NGS to detect non-clonal, low frequency mutations, so we are quite concerned about the background the sequencer introduces, meaning the amount of inespecific mutations coming from the sequencing process rather than from our samples.
In that sense, all the information we've found refers to the error rates coming from base calling (99.9% accuracy for GAIIx, 99.99% for SOLiD, etc.), but nothing about the errors generated during the sequencing process per se (library preparation, cluster generation, SBS...).
Do you know if there is any experimental data available? For instance, a measure of the mutational load of a known sequence (let's say the phage PhiX genome -usually loaded as a calibration control-) in subsequent technical replicates, or something like that.
Thanks a lot!
We are using NGS to detect non-clonal, low frequency mutations, so we are quite concerned about the background the sequencer introduces, meaning the amount of inespecific mutations coming from the sequencing process rather than from our samples.
In that sense, all the information we've found refers to the error rates coming from base calling (99.9% accuracy for GAIIx, 99.99% for SOLiD, etc.), but nothing about the errors generated during the sequencing process per se (library preparation, cluster generation, SBS...).
Do you know if there is any experimental data available? For instance, a measure of the mutational load of a known sequence (let's say the phage PhiX genome -usually loaded as a calibration control-) in subsequent technical replicates, or something like that.
Thanks a lot!
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