Nothing
featureVectors <- data.frame(
IsMismatch.pos1 = c(rep(0,5),1, rep(0,3)),
IsMismatch.pos2 = rep(0,9),
IsMismatch.pos3 = rep(0,9),
IsMismatch.pos4 = c(rep(0,2),1, rep(0,6)),
IsMismatch.pos5 = rep(0,9),
IsMismatch.pos6 = c(0, 1, rep(0,7)),
IsMismatch.pos7 = rep(0,9),
IsMismatch.pos8 = c(rep(0,3),1,1, rep(0,4)),
IsMismatch.pos9 = c(rep(0,4),1,1, rep(0,3)),
IsMismatch.pos10 = rep(0,9),
IsMismatch.pos11 = rep(0,9),
IsMismatch.pos12 = c(rep(0,8), 1),
IsMismatch.pos13 = c(1, rep(0,7), 1),
IsMismatch.pos14 = c(rep(0,6), 1, rep(0,2)),
IsMismatch.pos15 = c(rep(0,6), 1, rep(0,2)),
IsMismatch.pos16 = c(rep(0,7), 1, 0),
IsMismatch.pos17 = c(rep(0,7), 1, 0),
IsMismatch.pos18 = rep(0,9),
IsMismatch.pos19 = rep(0,9),
IsMismatch.pos20 = rep(0,9),
n.mismatch = c(1,1,1,1, 2,2,2,2,2),
mismatch.type = c("rG:dT", "rA:dC", "rC:dA", "rC:dA", "rU:dC,rC:dA",
"rU:dT,rC:dA", "rG:dT,rA:dG", "rG:dT,rC:dT", "rU:dC,rC:dA"),
subPAM = rep("GG",9), score = rep(1,9), alignment = rep("", 9))
correct.scores <- c(0.9230769, 0.7142857, 0.8000000, 0.8750000, 0.6416667,
0.8750000, 0.2045455, 0.4666667, 0.35)
featureVectors$score <- correct.scores
correct.scores <- featureVectors[order(
c(featureVectors$name,featureVectors$score),decreasing = TRUE), ]
correct.scores <- unique(correct.scores[!is.na(correct.scores$score), ])
featureVectors <- correct.scores
test_getOfftargetScore2 <- function() {
cat("Testing for getOfftargetScore2...\n")
scores <- CRISPRseek:::getOfftargetScore2(featureVectors)
if (checkEquals(featureVectors$score, scores$score, tolerance = 0.001 ))
cat("getOfftargetScore2 passed test \n")
else
cat("getOfftargetScore2 failed test \n")
}
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