Friday, 18 December 2015

Lessons for data collection from crystallography for viral data collection

I remember what a huge impact Denzo had on the processing of experimental data. Denzo allows you to model errors in the collection, such as slippage and x-ray damage. When we take samples of sequences from a population there are experimental errors that we need to consider. The sorts of question that we need to ask are:

  1. Is there a difference between the population of the virus in the host and that in the amplified sample?
  2. If the virus is a mixture of subtypes do the experimental methods favour one subtype over another?
  3. Does the sequencing technique favour AT or GC rich regions?
  4. Can we distinguish between sequencing error and point mutations?
Recent work on improving the collection and monitoring of wild bird avian influenza has shown that birds can be infected with multiple sub-types. In these cases how do we know which segments match with which other segments? How do they mix and produce mature virus?

No comments: