load("dev/scores.rda")
names(scores)
head(scores$column_score)
id <- scores$residue_pair_column_score$col %in% scores$column_score$col
id <- scores$column_score$col %in% scores$residue_pair_column_score$col
cs <- scores$column_score
x <- cbind(cs$CS[rpcs$col], rpcs$col_score)
sapply(scores, dim)
head(rprs)
## residue_pair_residue_score as matrix
rprs <- scores$residue_pair_residue_score
m <- matrix(rprs$score, nrow = nrow(base.msa))
identical(dim(base.msa), dim(m)) # alignment and rprs matrix have same dimensions
x <- polentaDNA(base.msa, m)
## calculate residue_pair_column_score from m
rpcs <- colMeans(m, na.rm = TRUE)
rpcs <- rpcs[!is.na(rpcs)]
# id <- which(rpcs != scores$residue_pair_column_score$col_score)
# cbind(rpcs, scores$residue_pair_column_score$col_score)[id, ]
## calculate residue_pair_sequence_score from m
rpss <- rowMeans(m, na.rm = TRUE)
rpss <- rpss[!is.na(rpss)]
# id <- which(rpcs != scores$residue_pair_column_score$col_score)
# cbind(rpcs, scores$residue_pair_column_score$col_score)[id, ]
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