beta.prob is a list with probabilities of TCR assembling taken from
Murugan et al. Statistical inference of the generation probability
of T-cell receptors from sequence repertoires. It's a list with the following elements:- P.V - matrix with 1 column and row names stands for V-beta segments. Each element is a probability of choosing corresponding V-beta segment.
- P.del.D1 - matrix 17x17 with probabilities of choosing D5-D3 deletions for TRBD1.
- P.del.D1 - matrix 17x17 with probabilities of choosing D5-D3 deletions for TRBD2.
- P.ins.len - matrix with first columns stands for number of insertions, second and third columns filled with probability values of choosing corresponding number of insertions in VD- and DJ-junctions correspondingly.
- P.ins.nucl - data frame with probability of choosing a nucleotide in the insertion on junctions with known previous nucleotide. First column with names of nucleotides, 2-5 columns are probabilities of choosing adjacent nucleotide in VD-junction, 6-9 columns are probabilities of choosing adjacent nucleotide in DJ-junction.
- P.del.J - matrix with the first column "P.del.V" with number of deletions, and other columns with names for V-segments and with probabilities of corresponding deletions.
- P.del.J - matrix with the first column "P.del.J" with number of deletions, and other columns with names for J-segments and with probabilities of corresponding deletions.
- P.J.D - matrix with two columns ("TRBD1" and "TRBD2") and 13 rows with row names stands for J-beta segments. Each element is a mutual probability of choosing J-D segments.
beta.prob is a list of matrices and data frames.# Generate 10 kmers with adjacent nucleotide probability.
generate.kmers.prob(rep.int(10, 10), .probs=beta.prob$P.ins.nucl[,c(1, 2:5)])Run the code above in your browser using DataLab