From 7e39f94ccb2770789a411114c09fe74431883bff Mon Sep 17 00:00:00 2001 From: Calvin Date: Fri, 3 May 2013 17:14:16 -0400 Subject: use a default kmer size of six --- src/python/quikr | 20 +++++++++++++------- 1 file changed, 13 insertions(+), 7 deletions(-) diff --git a/src/python/quikr b/src/python/quikr index 979f647..bae2b9f 100755 --- a/src/python/quikr +++ b/src/python/quikr @@ -14,18 +14,20 @@ def main(): You must supply a kmer and default lambda if using a custom trained \ matrix.") - parser.add_argument("-f", "--fasta", help="fasta file", required=True) - parser.add_argument("-o", "--output", help="output path (csv output)", required=True) - parser.add_argument("-t", "--trained-matrix", help="trained matrix", required=True) - parser.add_argument("-l", "--lamb", type=int, help="the default lambda value is 10,000") + parser.add_argument("-f", "--fasta", help="the sample's fasta file of NGS READS", required=True) + parser.add_argument("-o", "--output", help="OTU_FRACTION_PRESENT, a vector \ + representing the percentage of database sequence's presence in a sequence. (csv output)", required=True) + parser.add_argument("-t", "--trained-matrix", help="the trained matrix", required=True) + parser.add_argument("-l", "--lamb", type=int, help="the lambda size. (default is 10,000") parser.add_argument("-k", "--kmer", type=int, required=True, - help="specifies which kmer to use, must be used with a custom trained database") - + help="specifies the size of the kmer to use (the default is 6)") args = parser.parse_args() # our default lambda is 10,000 lamb = 10000 + # our default kmer size is 6 + kmer = 6 # Make sure our input exist if not os.path.isfile(args.fasta): @@ -38,8 +40,12 @@ def main(): if args.lamb is not None: lamb = args.lamb + # use alternative kmer + if args.kmer is not None: + kmer = args.kmer + trained_matrix = quikr.load_trained_matrix_from_file(args.trained_matrix) - xstar = quikr.calculate_estimated_frequencies(args.fasta, trained_matrix, args.kmer, lamb) + xstar = quikr.calculate_estimated_frequencies(args.fasta, trained_matrix, kmer, lamb) np.savetxt(args.output, xstar, delimiter=",", fmt="%f") return 0 -- cgit v1.2.3