BAMBAM: parallel comparative analysis of high-throughput sequencing data
The present invention relates to methods for evaluating and/or predicting the outcome of a clinical condition, such as cancer, metastasis, AIDS, autism, Alzheimer's, and/or Parkinson's disorder. The methods can also be used to monitor and track changes in a patient's DNA and/or RNA during and following a clinical treatment regime. The methods may also be used to evaluate protein and/or metabolite levels that correlate with such clinical conditions. The methods are also of use to ascertain the probability outcome for a patient's particular prognosis.
1. A computer-based method of calculating allele information from a tissue sample, the method comprising:
(a) retrieving, from a BAM/SAM file stored in a storage device, only a set of aligned short reads of genomic sequence data associated with a pileup, the set of aligned short reads being retrieved by a computer processor coupled with a computer readable memory, wherein the set of aligned short reads overlap a known genomic position of a reference sequence;
(b) storing, in the computer readable memory, the retrieved set of aligned short reads of genomic sequence data, all the stored aligned short reads overlapping the known genomic position;
(c) calculating, via the computer processor coupled with the computer readable memory, a probability of an allele measure at the known genomic position as a function of a number of observed alleles in the aligned short reads of the pileup;
(d) repeating (a)-(c) for additional known genomic positions using additional sets of aligned short reads, wherein the sets of aligned short reads represent at least 10% of a genome, transcriptome, or proteome of the tissue sample; and
(e) storing in the storage device the allele measure at one or more of the known genomic positions.
2. The method of claim 1 , wherein the allele measure represents a probability of alleles.
3. The method of claim 2 , further comprising calculating the probability of alleles as a function of a base probability from parental alleles and the number of observed alleles in the aligned short reads of the pileup.
4. The method of claim 1 , wherein the allele measure represents an allele specific copy number.
5. The method of claim 4 , further comprising expanding or contracting an analysis window around the known genomic position.
6. The method of claim 4 , further comprising calculating the allele specific copy number as a function of a number of supporting aligned short reads.
7. The method of claim 4 , further comprising calculating the allele specific copy number at the known genomic position, wherein the known genomic position has at least two different alleles.
8. The method of claim 7 , wherein the allele specific copy number comprises a majority allele count.
9. The method of claim 7 , wherein the allele specific copy number comprises a minority allele count.
10. The method of claim 4 , further comprising identifying a loss of heterozygosity at least at the known genomic position as a function of the allele specific copy number.
11. The method of claim 10 , wherein the loss of heterozygosity is associated with at least a region of the genome.
12. The method of claim 1 , wherein the allele measure represents an allelic imbalance.
13. The method of claim 1 , wherein the allele measure represents an allelic proportion.
14. The method of claim 1 , wherein the allele measure represents an allelic state.
15. The method of claim 14 , wherein the allelic state represents homozygosity.
16. The method of claim 1 , further comprising estimating an amount of a contaminant in the tissue sample as a function of the allele measure.
17. The method of claim 16 , wherein the allele measure comprises an allele-specific copy number.
18. The method of claim 17 , wherein the contaminant comprises a normal contaminant in the tissue sample.
19. The method of claim 18 , wherein the contaminant comprises a normal contaminant in a tumor tissue sample.
20. The method of claim 1 , wherein the tissue sample comprises a normal tissue sample.
21. The method of claim 20 , wherein the normal tissue sample comprises a blood sample.
22. The method of claim 1 , wherein the tissue sample comprises a diseased tissue sample.
23. The method of claim 22 , wherein the diseased tissue sample comprises a tumor tissue sample.
24. The method of claim 1 , wherein the pileup comprises at least 30 short reads.
25. The method of claim 1 , wherein the aligned short reads comprise polynucleotide sequences.
26. The method of claim 25 , wherein the aligned short reads comprise DNA sequences.
27. The method of claim 1 , wherein the aligned short reads comprise RNA sequences.
28. The method of claim 27 , wherein the RNA sequences include at least one of the following: mRNA transcript, rRNA, or tRNA sequences.
29. The method of claim 1 , wherein the tissue sample is a sample from at least one of the following: a rat, a dog, a mouse, a primate, an animal, a plant, and a human.
30. The method of claim 1 , wherein the tissue sample includes at least two samples.
31. The method of claim 30 , herein the at least two samples includes at least three samples.