METHODS FOR THE ANALYSIS OF DISSOCIATION MELT CURVE DATA
The present invention relates to the use of wavelet transform to analyze raw melting curve data of nucleic acids. The effect is decreased noise sensitive calculations and increased computational efficiency and speed. The invention is particularly suitable for classifying test samples involving the combined analysis of several, multiplexed targets within one experiment generating large raw datasets requiring discrimination of minute variations in the data.
1 . A method for analyzing melting curve raw data of nucleic acid from a test sample, the method comprising the steps of:
producing melting curve raw data from a nucleic acid;
performing discrete wavelet transform on the raw data to produce discrete wavelet transform coefficients, further referred to as dwt coefficients;
performing the analysis of the dwt coefficients;
and classifying the test sample based on the analysis.
2 . Method according to claim 1 , wherein the melting curve raw data are obtained from nucleic acids with one or more SNPs or nucleic acids with length variations, preferably being insertions or deletions.
3 . Method according to claim 1 , wherein the melting curve raw data are obtained from nucleic acids with subtle microsatellite changes, preferably being nucleic acids with homopolymeric repeat sequence variations.
4 . Method according to claim 1 , wherein the nucleic acid is an amplified nucleic acid.
5 . Method according to claim 1 , wherein melting curve raw data are produced by dissociating the amplified nucleic acid in the presence of a dye-labeled nucleic acid, preferably a dye-labeled beacon probe.
6 . Method according to claim 1 , wherein the step of producing melting curve raw data from a nucleic acid is followed by a step of performing data reduction on the raw data to generate a selection of raw data, and wherein the discrete wavelet transform is performed on the selection of raw data.
7 . Method according to claim 1 , wherein the step of performing the analysis of the dwt coefficients comprises selecting those dwt coefficients identified as the most relevant and performing the analysis of the selected dwt coefficients.
8 . Method according to claim 1 , wherein the discrete wavelet transform is a one-dimension wavelet transform.
9 . Method according to claim 1 , wherein the discrete wavelet transform uses a mother wavelet from the Daubechies family, preferably being the DB8 wavelet.
10 . Method according to claim 1 , wherein the classifying is a genotyping record and one or more visual displays of the genotyping.
11 . Method according to claim 1 , wherein the steps of:
producing melting curve raw data from a nucleic acid;
optionally, performing data reduction on the raw data to generate a selection of raw data;
performing discrete wavelet transform on the raw data or selection of raw data produce discrete wavelet transform coefficients, further referred to as dwt coefficients;
performing the analysis of the dwt coefficients,
wherein the performing the analysis of the dwt coefficients optionally comprises selecting those dwt coefficients identified as the most relevant and performing the analysis of the selected dwt coefficients; and
classifying the test sample based on the analysis are performed in an automated system.
12 . Method according to claim 7 wherein the method is a computer-implemented method.
13 . A data processing device comprising means for carrying out the computer-implemented method according to claim 12 .
14 . A computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the computer-implemented method according to claim 12 .
15 . A computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out the computer-implemented method according to claim 12 .