Method for analyzing biological data sets
The present invention relates to methods for analyzing biological data sets, and more specifically for identifying biomolecular differences between biological samples. In particular, the present invention is based in part, on the discovery that Markov's Inequality, and in certain illustrative aspects Chebyshev's Inequality, can be used to analyze biological data sets to identify positive signals. The data sets are typically generated using a biological assay, such as a biomolecule array assay.
1 . A method for determining a positive interaction on a protein or peptide array, comprising:
a) contacting a protein or peptide and a negative control immobilized on a protein or peptide array with a sample; and,
b) calculating a probability value for the protein or peptide using Markov's Inequality based on a comparison of a signal generated from the interaction of one or more molecules in the sample with the protein or peptide immobilized on the array and a signal generated for a negative control on the array, wherein a probability value below a threshold probability value identifies a positive interaction between the protein or peptide on the protein or peptide array and one or more molecules in the sample.
2 . The method of claim 1 , wherein the probability value is calculated using Chebyshev's Inequality to calculate a Chebyshev's Inequality precision value (CI-p-Value).
3 . The method of claim 1 , wherein the threshold probability is calculated based on experimental values obtained while performing the method.
4 . The method of claim 3 , wherein the threshold probability is calculated using signal values generated from negative controls on the array.
5 . The method of claim 1 , wherein the threshold probability is pre-set.
6 . The method of claim 1 , wherein the plurality of proteins or peptides are immobilized in a high density array on the solid support.
7 . The method of claim 1 , wherein the threshold probability is preset at a value equal to one divided by a number of protein spots on the array.
8 . The method of claim 1 , wherein a threshold probability value is calculated using a probability cutoff of between 0.5 and 2 false positive errors per protein or peptide array.
9 . The method of claim 1 , wherein the plurality of proteins or peptides are antibodies.
10 . The method of claim 1 , wherein the plurality of proteins or peptides comprise at least 1000 proteins from the same organism.
11 . The method of claim 1 , wherein the sample is a biological sample.
12 . The method of claim 11 , wherein the biological sample is a biological fluid.
13 . The method of claim 12 , wherein the biological fluid is serum or plasma.
14 . A method for determining whether a binding partner is present more frequently in a first biological sample type or a second biological sample type from a plurality of biological samples of each biological sample type, comprising:
a) contacting each sample individually with a plurality of proteins or peptides immobilized on a protein array;
b) calculating a probability value for each sample for each protein or peptide on each array using Markov's Inequality based on a comparison of a signal generated from the interaction of biomolecules in each sample with each protein on each array and a signal generated for a negative control on each array;
c) identifying significant probability values using a dynamic significance calculation calculated by identifying a minimum observed probability value for each sample for each protein or peptide on each array; and
d) determining for each protein or peptide, whether a significant probability value is observed more frequently in samples of the first biological sample type or samples of the second biological sample type to identify binding partners expressed more frequently in one of the biological sample types.
15 . The method of claim 14 , wherein the probability value for each protein on each array is calculated using Chebyshev's Inequality to calculate a Chebyshev's Inequality precision value (CI-p-Value).
16 . The method of claim 14 , wherein the biological sample is a biological fluid.
17 . The method of claim 16 , wherein the biological fluid is serum or plasma.
18 . The method of claim 14 , wherein the binding partner is a polypeptide or peptide.
19 . The method of claim 14 , wherein the first biological sample type is a normal sample and the second biological sample type is a sample from a patient afflicted with a disease.
20 . The method of claim 19 wherein the disease is an autoimmune condition, a microbiological infection, cancer, a neurological disorder, a circulatory disorder, or a respiratory disorder.
21 . The method of claim 14 , wherein a binding partner expressed in only one of the biological sample types are identified using a 95-99.9% confidence limit.
22 . The method of claim 14 , wherein a binding partner expressed in only one of the biological sample types are identified using a 97-99% confidence limit.
23 . The method of claim 14 , wherein the dynamic significance calculation is calculated using signal values generated from negative controls on the array.
24 - 28 . (canceled)