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# Expanding Prediction To Multiple Viruses We will attempt to replicate dominant strain prediction to two more viruses: + HIV1-A - This will attempt to predict dominant strain within individual patients + CCHFV - This is an attempt to predict dominant strain over time, say for 5 years The key ponts here are: 1) is there enough data available to carry out this modeling? And 2) should we consider geographic stratification? Lets start with CCHF. We do the following steps: + Download all CCHFV sequences between collection years 2010 and 2020 + breakdown by 2 year periods + check which *segments* are most common (there is S, M, and L segements in the virus) + Try making Qnets with this 2 year data (after aliognment, and segment choice) + Carry out dominant strain pred and validation (check how well we do from the actual dominant strain prediction) Currently looking at HIV patient specific data availability # Task List 1. generate the alphabeta and the metadata csvs as above 2. Shere the link with the diffusion simulation u did for the different viruses 3. Dominat strain tracking task (above) 4. We need to do a EPITOPE MATCH task (detailed later) 5. We need to do a IRAT calculation task as well (this will be a seprate paper) # Epitope Match Task Let k be the diffusion simulation step. 1. compute the MHCI top epitopes using the application u tried, call this set E_k 2. compute the deviation of E_k from E_0 as follows: Note these are sets of strings Compute $$average_{x \in E_k} min_{y \in E_0} L(x,y)$$ 3. Plot the averge E_k line, averaged over mutiple simulation runs # IRAT task 1. Show qIRAT for 100 H1N1, 100 H3N2, and sufficient number of recent H5 and H7 sequences (report minimum score over 2010-current, and the current year score) 2. List top 3 for each variety (minimum current year score) 3. as usual report seqName, seqAccession, etc
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