BamBam: parallel comparative analysis of high-throughput sequencing data

1. A computer-based method of analyzing genetic sequences, comprising:

reading from a first genomic short read sequencing dataset and a second genomic short read sequencing dataset, wherein the first genomic short read sequencing dataset and the second genomic short read sequencing dataset represent at least 10% of a human genome;

keeping the first genomic short read sequencing data set and the second genomic short read sequencing dataset in synchrony with each other in a device memory;

piling up or clustering genomic short reads that overlap each of a plurality of common genomic locations of the first genomic short read sequencing dataset and the second genomic short read sequencing dataset, thereby generating pileups or clusters;

analyzing the pileups or the clusters of genomic short reads, to maximize joint probability of both genotype of the first genomic short read sequencing dataset and genotype of the second genomic short read data sequencing dataset at each of the plurality of common genomic locations; and

generating a differential genetic sequence object that represents a difference between the first genomic short read sequencing dataset and the second genomic short read sequencing dataset, based on the analyzing.

2. The method of claim 1 , further comprising:

detecting and quantifying at least one altered gene structure, based on the differential genetic sequence object.

3. The method of claim 1 , further comprising:

detecting and quantifying at least one altered gene expression, based on the differential genetic sequence object.

4. The method of claim 1 , further comprising:

detecting and quantifying at least one gene biochemical modification, based on the differential genetic sequence object.

5. The method of claim 1 , further comprising:

at least partially diagnosing a condition, disease or disorder, based on the differential genetic sequence object, wherein the first genomic short read sequencing dataset is from a normal subject and the second genomic short read sequencing dataset is from a subject symptomatic for the condition, disease or disorder.

6. The method of claim 1 , further comprising:

at least partially evaluating efficacy of a treatment or therapy, based on the differential genetic sequence object, wherein the first genomic short read sequencing dataset is from a subject prior to the treatment or therapy and the second genomic short read sequencing dataset is from the subject after the treatment or therapy.

7. The method of claim 1 , further comprising:

detecting and quantifying a change in gene structure, a gene mutation or a gene biochemical modification, wherein the first genomic short read sequencing dataset is from a subject associated with a specified disease, disorder, or condition.

8. The method of claim 1 , further comprising:

determining whether or how genotoxic an agent is, based on the differential genetic sequence object, wherein the first genomic short read sequencing dataset is from a subject that has exposure to the agent.

9. The method of claim 1 , further comprising:

analyzing expression of phenotype or tissue-specific mRNA (messenger ribonucleic acid) expression, based on the differential genetic sequence object, wherein the first genomic short read sequencing dataset is from an animal or human subject before, during or after a drug therapy.

10. The method of claim 1 , further comprising:

performing gene knockout or gene knockin analysis to a cell or to a non-human animal based on the differential genetic sequence object, wherein the first genomic short read sequencing dataset is from a subject with a modified gene.

11. The method of claim 1 , further comprising:

evaluating a drug, toxin or therapeutic agent, based on the differential genetic sequence object, wherein the first genomic short read sequencing dataset is from a non-human primate having exposure to the drug, toxin or therapeutic agent.

12. The method of claim 1 , further comprising:

evaluating a drug, toxin or therapeutic agent, based on the differential genetic sequence object, wherein the first genomic short read sequencing dataset is from a rodent having exposure to the drug, toxin or therapeutic agent.

13. The method of claim 1 , further comprising:

analyzing at least one phenotype difference, based on the differential genetic sequence object, wherein the first genomic short read sequencing dataset and the second genomic short read sequencing dataset have or represent differing genotypes.

14. The method of claim 1 , wherein the first genomic short read sequencing dataset and the second genomic short read sequencing dataset are for a first subject, wherein a group of subjects includes the first subject, the method further comprising:

assessing genotype frequencies in the group of subjects comprising a first plurality of subjects with a disorder and a second plurality of subjects without the disorder, based on the differential genetic sequence object and additional differential genetic sequence objects determined for other subjects in the group.

15. The method of claim 1 , further comprising:

detecting a cancer tissue or a metastatic tissue, based on the differential genetic sequence object.

16. The method of claim 1 , further comprising:

detecting a neurological disorder, based on the differential genetic sequence object.

17. The method of claim 1 , further comprising:

detecting a condition, disease or disorder associated with altered expression of a gene or protein, based on the differential genetic sequence object.

18. The method of claim 1 , further comprising:

detecting, quantifying or measuring one or more gene structures, gene mutations or gene biochemical modifications that indicate or identify presence or absence of a tumor or status of a remission, based on the differential genetic sequence object.

19. A tangible, non-transitory, computer-readable media having instructions thereupon which, when executed by a processor, cause the processor to perform a method comprising:

reading from a first genomic short read sequencing dataset and a second genomic short read sequencing dataset, wherein the first genomic short read sequencing dataset and the second genomic short read sequencing dataset represent at least 10% of a human genome;

keeping the first genomic short read sequencing data set and the second genomic short read sequencing dataset in synchrony with each other in a device memory;

piling up or clustering genomic short reads that overlap each of a plurality of common genomic locations of the first genomic short read sequencing dataset and the second genomic short read sequencing dataset, thereby generating pileups or clusters;

analyzing the pileups or the clusters of genomic short reads, to maximize joint probability of both genotype of the first genomic short read sequencing dataset and genotype of the second genomic short read data sequencing dataset at each of the plurality of common genomic locations; and

generating a differential genetic sequence object that represents a difference between the first genomic short read sequencing dataset and the second genomic short read sequencing dataset, based on the analyzing.

20. A genetic sequence analyzer, comprising:

a memory; and

at least one processor, coupled to the memory and configured to:

read from a first genomic short read sequencing dataset and a second genomic short read sequencing dataset, wherein the first genomic short read sequencing dataset and the second genomic short read sequencing dataset represent at least 10% of a human genome;

keep the first genomic short read sequencing data set and the second genomic short read sequencing dataset in synchrony with each other in a device memory;

pile up or cluster genomic short reads that overlap each of a plurality of common genomic locations of the first genomic short read sequencing dataset and the second genomic short read sequencing dataset, thereby generating pileups or clusters;

analyze the pileups or the clusters of genomic short reads, to maximize joint probability of both genotype of the first genomic short read sequencing dataset and genotype of the second genomic short read data sequencing dataset at each of the plurality of common genomic locations; and

generate a differential genetic sequence object that represents a difference between the first genomic short read sequencing dataset and the second genomic short read sequencing dataset, based on such analyzing.