LAPD program estimates pairwise distances for a set of protein sequences.
A special feature is that the specialized rate matrices, estimated by modelestimator, can be used as input to the program.
The method is described in a forthcoming paper.
Usage: lapd [< options >] < infile >
The infile should be in either FASTA, STOCKHOLM, or PHYLIP format. Output is a matrix of expected distances and, if possible, estimates of standard deviation.
-indels Remove gap columns. A gap is denoted by '-'.
-ml Compute a Maximum Likelihood estimate instead. This option implies -sd.
-sd Do not output a matrix with standard deviations after the distance matrix.
-id Output percent identity.
-jc Use a simplistic Jukes-Cantor model.
-jck Use -jc, but use Kimura's correction.
-jcss Like -jck, but using Storm-Sonhammer's correction.
-wag Default. Use the WAG matrix (see Wheelan and Goldman, 2001).
-jtt Use the JTT matrix (see Jones, Taylor, Thornton, 1992).
-day Use the Dayhoff matrix (Dayhoff et al, 1978).
-arve Use the Arvestad matrix.
-mv Use the Muller-Vingron matrix (2000).
-f < file > Read matrix and equilibrium distribution from file.
-pfam Use a normal distribution as distance prior, estimated from Pfam 7.2.
-s "Speed". High speed results in low precision. Default is 5. Valid range is [1, 10].
-v Verbose. Show progress info on STDERR.
-octave < path > Point to the Octave binary to run. 'octave -q' by default.
-d Debug option. Output Octave commands to STDOUT.
-u, -h This help text.