📄 distmat.txt
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distmat Function Creates a distance matrix from multiple alignmentsDescription distmat calculates the evolutionary distances between every pair of sequences in a multiple alignment. The sequences need to be aligned before running this program. The quality of the alignment is of paramount importance in obtaining meaningful information from this analysis. This application calculates a distance matrix for the set of sequences in the alignment. The distances are expressed in terms of the number of substitutions per 100 bases or amino acids. As sequence diverge so does the probability of there being multiple substitutions at any one site in the alignment increase. The distance will then be an underestimate of the true evolutionary distance between the sequences. Therefore, there are a number of methods for correcting the observed substitution rate for the occurence of multiple substutions. For nucleotides, the "-position" flag allows the user to choose base positions to analyse in each codon, i.e. 123 (all bases), 12 (the first two bases), 1, 2, or 3 individual bases. Uncorrected distances This method does not make any corrections for multiple substitutions. Therefore, the score will be an underestimate of the distance between the sequences. This will not be less significant for highly similar sets of sequences.S = m/(npos + gaps*gap_penalty) (1)m - score of matches (1 for an exact match, a fraction for partial matches and 0 for no match)npos - number of positions included in mgaps - number of gaps in the sequencesgap_penalty - the score given to a gapped positionD = uncorrected distance = p-distance = 1-S (2) The score of match includes all exact matches. For nucleotides, if the flag "-ambiguous" is used then partial matches are included in the score. For example, a match of M (A or C) with A will increment m by 0.5 (0.5*1.0). Gaps are not included in the calculation unless a non zero value is given with "-gapweight". It should be noted that end gaps and internal gaps will be weighted by the same amount. So it is recommended that this be used with "-sbegin"and "-send" to specify the start and end of the region to calculate the distance from.Multiple Substitution correction algorithms Jukes-Cantor This can be used for nucleotide and protein sequences.distance = -b ln (1-D/b)D - uncorrected distanceb - constant. b= 3/4 for nucleotides and 19/20 for proteins. Partial matches and gap positions can be taken into account in the calculation of D, by setting the "-ambiguous" and "-gapweight" flags (see "uncorrected distance" method). Reference: "Phylogenetic Inference", Swofford, Olsen, Waddell, and Hillis, in Molecular Systematics, 2nd ed., Sinauer Ass., Inc., 1996, Ch. 11. Tajima-Nei This method is only for nucleotide sequences. It uses the same equation as Jukes-Cantor, but the b-parameter is not constant. Also, only exact matches are considered in the calculation of the match score and gap positions are ignored.A = 1, T = 2, C = 3, G = 4b = 0.5(1.- Sum(i=A,G)(fraction[i]^2 + D^2/h)h = Sum(i=A,C)Sum(k=T,G) (0.5 * pair_frequency[i,k]^2/(fraction[i]*fraction[k]))distance = -b ln(1.-D/b)pair_frequency[i,k] - frequency of the i and k base pair at sites in the alignement of the pair of sequences.fraction[i] - average content of the base i in both sequences Reference: F. Tajima and M. Nei, Mol. Biol. Evol. 1984, 1, 269. Kimura Two-Parameter distance This method is only for nucleotide sequences. This uses the principle that transition substitutions (purine-purine and pyrimidine-purine) are more likely than transversion substitutions (purine-pyprimidine). Purine being the nucleic acid constituent of A and G, and pyrimidine being the nucleic acid derivative of the bases C, T and U. Gaps are ignored and abiguous symbols other than R (purine) and Y (pyrimidine) are ingnored.P = transitions/nposQ = transversions/nposnpos - number of positions scoreddistance = -0.5 ln[ (1-2P-Q)*sqrt(1-2Q)] Reference: M. kimura, J. Mol. Evol. 1980, 16, 111. Tamura This method is only for nucleotide sequences. This method uses transition and transversion rates and takes into account the deviation of GC content from the expected value of 50 %. Gap and ambiguous positions are ignored.P = transitions/nposQ = transversions/nposnpos - number of positions scoredGC1 = GC fraction in sequence 1GC2 = GC fraction in sequence 2C = GC1 + GC2 - 2*GC1*GC2distance = -C ln(1-P/C-Q) - 0.5(1-C) ln(1-2Q) Reference: K. Tamura, Mol. Biol. Evol. 1992, 9, 678. Jin-Nei Gamma distance This method applies to nucleotides only. This again uses transition and transversion rates. As with the Kimura two parameter method, gaps and ambiguous symbols other than R and Y are not oncluded in the score. The shape parameter, i.e. "a", is the square of the inverse of the coefficient of variation of the average substitution,L = average substituition = transition_rate + 2 * transversion_ratea = (average L)^2/(variance of L)P = transitions/nposQ = transversions/nposnpos - number of positions scoreddistance = 0.5 * a ((1-2P-Q)^(-1/a) + 0.5 (1-2Q)^(-1/a) -3/2) It is suggested [Jin et al.], in general, that the distance be calculated with an a-value of 1. However, the user can specify their own value, using the "-parametera" option, or calculate for each pair of sequence, using "-calculatea". Reference: L. Jin and M. Nei, Mol. Biol. Evol. 1990, 7, 82. Kimura Protein distance This method is used for proteins only. Gaps are ignored and only exact matches and ambiguity codes contribute to the match score.S = m/nposm - exact matchnpos - number of positions scoredD = 1-Sdistance = -ln(1 - D - 0.2D^2) Reference: M. Kimura, The Neutral Theory of Molecular Evolution, Camb. Uni. Press, Camb., 1983.Usage Here is a sample session with distmat% distmat pax.align Creates a distance matrix from multiple alignmentsMultiple substitution correction methods for proteins 0 : Uncorrected 1 : Jukes-Cantor 2 : Kimura ProteinMethod to use [0]: 2Phylip distance matrix output file [pax.distmat]: Go to the input files for this example Go to the output files for this exampleCommand line arguments Standard (Mandatory) qualifiers (* if not always prompted): [-sequence] seqset File containing a sequence alignment.* -nucmethod menu [0] Multiple substitution correction methods for nucleotides. (Values: 0 (Uncorrected); 1 (Jukes-Cantor); 2 (Kimura); 3 (Tamura); 4 (Tajima-Nei); 5 (Jin-Nei Gamma))* -protmethod menu [0] Multiple substitution correction methods for proteins. (Values: 0 (Uncorrected); 1 (Jukes-Cantor); 2 (Kimura Protein)) [-outfile] outfile [*.distmat] Phylip distance matrix output file Additional (Optional) qualifiers (* if not always prompted):* -ambiguous boolean [N] Option to use the ambiguous codes in the calculation of the Jukes-Cantor method or if the sequences are proteins.* -gapweight float [0.] Option to weight gaps in the uncorrected (nucleotide) and Jukes-Cantor distance methods. (Any numeric value)* -position integer [123] Choose base positions to analyse in each codon i.e. 123 (all bases), 12 (the first two bases), 1, 2, or 3 individual bases. (Any integer value)* -calculatea boolean [N] This will force the calculation of parameter 'a' in the Jin-Nei Gamma distance calculation, otherwise the default is 1.0 (see -parametera option).* -parametera float [1.0] User defined parameter 'a' to be use in the Jin-Nei Gamma distance calculation. The suggested value to be used is 1.0 (Jin et al.) and this is the default. (Any numeric value) Advanced (Unprompted) qualifiers: (none) Associated qualifiers:
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