DesignArray(myDNAStringSet, maxProbeLength = 24, minProbeLength = 20, maxPermutations = 4, numRecordedMismatches = 500, numProbes = 10, start = 1, end = NULL, maxOverlap = 5, hybridizationFormamide = 10, minMeltingFormamide = 15, maxMeltingFormamide = 20, minScore = -1e+12, processors = 1, verbose = TRUE)DNAStringSet object of aligned consensus sequences.
minMeltingFormamide.
minScore will accelerate the code because more target sites will be excluded from consideration. However, if the minScore is too high it will prevent any target sites from being recorded.
NULL to automatically detect and use all available processors.
data.frame with the optimal set of probes matching the specified constraints. Each row lists the probe's target sequence (name), start position, length in nucleotides, start and end position in the sequence alignment, number of permutations, score, melt point in percent formamide at 42 degrees Celsius, hybridization efficiency (hyb_eff), target site, and probe(s). Probes are designed such that the stringency is determined by the equilibrium hybridization conditions and not subsequent washing steps.
DR Noguera, et al. (2014). Mathematical tools to optimize the design of oligonucleotide probes and primers. Applied Microbiology and Biotechnology. doi:10.1007/s00253-014-6165-x.
Array2Matrix, NNLS
fas <- system.file("extdata", "Bacteria_175seqs.fas", package="DECIPHER")
dna <- readDNAStringSet(fas)
names(dna) <- 1:length(dna)
probes <- DesignArray(dna)
probes[1,]
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