updated extreme_muts.R with number of budding hotspots and mult muts numbers
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@ -124,3 +124,40 @@ hs_foldx
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#===============
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#===============
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aa_muts = merged_df3[merged_df3$ligand_distance<5,]
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aa_muts = merged_df3[merged_df3$ligand_distance<5,]
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aa_dist = paste0(5, angstroms_symbol)
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cat("No. of active site residues within", aa_dist, ":", nrow(aa_muts))
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#====================
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# budding hotspots
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#====================
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# Method
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# this is what you want
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foo = merged_df3 %>% group_by(position) %>% tally()
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bar = merged_df3 %>% group_by(position) %>% count()
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# sanity check
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all(table(foo$n) == table(bar$n))
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table(foo$n)
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n_budding_sites = table(foo$n)[[2]]
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n_mult_muts_sites = sum(table(foo$n)) - (table(foo$n)[[1]] - table(foo$n)[[2]])
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cat("No of budding hotspots (sites with 2 mutations):", n_budding_sites
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, "\nNo. of sites with mutiple (>2) mutations:", n_mult_muts_sites)
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# another way
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setDT(merged_df3)[, pos_count := .N, by = .(position)]
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# this is cummulative
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table(merged_df3$pos_count)
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# use group by on this: same as the
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snpsBYpos_df <- merged_df3 %>%
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group_by(position) %>%
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summarize(snpsBYpos = mean(pos_count))
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