Bambam: parallel comparative analysis of high-throughput sequencing data

• US 20120059670A1
• Filed: 05/25/2011
• Published: 03/08/2012
• Est. Priority Date: 05/25/2010
• Status: Active Grant

• Current Assignee: Regents of the University of California (University of California)
• Original Assignee: Regents of the University of California (University of California)
• Inventors: Haussler, David, Sanborn, John Zachary
• Granted Patent: US 9,652,587 B2
• Time in Patent Office: Days
• US Class Current: 705/3
• CPC Class Codes: C12Q 1/6886 for cancer immunoassay for cancer G01N33/574
• CPC Class Codes: C12Q 2600/106 Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
• CPC Class Codes: C12Q 2600/118 Prognosis of disease development
• CPC Class Codes: C12Q 2600/156 Polymorphic or mutational markers
• CPC Class Codes: G06F 2203/04806 Zoom, i.e. interaction techniques or interactors for controlling the zooming operation
• CPC Class Codes: G06F 3/04845 for image manipulation, e.g. dragging, rotation, expansion or change of colour
• CPC Class Codes: G06F 40/169 Annotation, e.g. comment data or footnotes
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs
• CPC Class Codes: G16B 20/20 Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids
• CPC Class Codes: G16B 30/10 Sequence alignment; Homology search
• CPC Class Codes: G16B 40/00 ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 70/20 relating to practices or guidelines
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
• CPC Class Codes: Y02A 90/30 Assessment of water resources

Abstract

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.

Claims

1. A method of deriving a differential genetic sequence object, the method comprising:

providing access to a genetic database storing (a) a first genetic sequence string representing a first tissue and (b) a second genetic sequence string representing a second tissue, wherein the first and second sequence strings have a plurality of corresponding sub-strings;

providing access to a sequence analysis engine coupled with the genetic database;

producing, using the sequence analysis engine, a local alignment by incrementally synchronizing the first and second sequence strings using a known position of at least one of plurality of corresponding sub-strings;

using, by the sequence analysis engine, the local alignment to generate a local differential string between the first and second sequence strings within the local alignment; and

using, by the sequence analysis engine, the local differential string to update a differential genetic sequence object in a differential sequence database.

2. The method of claim 1 wherein the first and second genetic sequence strings represent at least 10% of a genome, transcriptome, or proteome of the first and second tissues, respectively.

3. The method of claim 1 wherein the first and second genetic sequence strings represent at least 50% of a genome, transcriptome, or proteome of the first and second tissues, respectively.

4. The method of claim 1 wherein the first and second genetic sequence strings represent substantially the entire genome, transcriptome, or proteome of the first and second tissues, respectively.

5. The method of claim 1 wherein the first and second tissues originate from the same biological entity, the biological entity selected from the group consisting of a patient, a healthy individual, a cell line, a stem cell, an experimental animal model, a recombinant bacterial cell, and a virus.

6. The method of claim 1 wherein the first tissue is a healthy tissue and wherein the second is a diseased tissue.

7. The method of claim 6 wherein the diseased tissue comprises a tumor tissue.

8. The method of claim 1 wherein the corresponding sub-strings comprise homozygous alleles.

9. The method of claim 1 wherein the corresponding sub-strings comprise heterozygous alleles.

10. The method of claim 1 wherein the step of synchronizing comprises aligning at least one of the plurality of sub-strings is based on an a priori known location within the first string.

11. The method of claim 1 wherein the step of synchronizing comprises aligning at least one of the plurality of sub-strings based on a known reference string comprising known locations for the at least one of the plurality of sub-strings.

12. The method of claim 11 wherein the known reference string is a consensus sequence.

13. The method of claim 1 wherein the step of synchronizing comprises aligning the at least one of the plurality of sub-strings within a window having a length of less than a length of the at least one of the plurality of sub-strings.

14. The method of claim 1 further comprising iteratively incrementally synchronizing the first and second sequence strings throughout the entire length of the first sequence string.

15. The method of claim 1 wherein the differential genetic sequence object represents a plurality of local differential strings for at least one chromosome.

16. The method of claim 1 wherein the differential genetic sequence object represents a plurality of local differential strings for substantially the entire genome of the first tissue.

17. The method of claim 1 wherein the differential genetic sequence object comprises an attribute comprising metadata describing the differential genetic sequence object.

18. The method of claim 17 wherein the attribute comprises a state of at least one of the first and second tissues.

19. The method of claim 18 wherein the state comprises a physiological state of at least one of the first and second tissues.

20. The method of claim 19 wherein the physiological state comprises a state selected from the group consisting of neoplastic growth, apoptosis, state of differentiation, tissue age, and responsiveness to treatment.

21. The method of claim 18 wherein the state comprises genetic status.

22. The method of claim 21 wherein the genetic status comprises a status selected from the group consisting of at least one ploidy, gene copy number, repeat copy number, inversion, deletion, insertion of viral genes, somatic mutation, germline mutation, structural rearrangement, transposition, and loss of heterozygosity.

23. The method of claim 17 wherein the state comprises pathway model information associated with a signaling pathway within the tissues.

24. The method of claim 23 wherein the signaling pathway is selected from the group consisting of a growth factor signaling pathway, a transcription factor signaling pathway, an apoptosis pathway, a cell cycle pathway, and a hormone response pathway.

25. The method of claim 1 wherein the genetic sequence object comprises a file.

26. The method of claim 25 wherein the file conforms to a standardized format.

27. The method of claim 26 wherein the file conforms to a SAM/BAM format.

48. The method of claim 1, claim 28, claim 36, or claim 45, wherein the patient or person is selected from the group consisting of a patient or person diagnosed with a condition, the condition selected from the group consisting of a disease and a disorder.

49. The method of claim 48 wherein the condition is selected from the group consisting of acquired immunodeficiency syndrome (AIDS), Addison'"'"'s disease, adult respiratory distress syndrome, allergies, ankylosing spondylitis, amyloidosis, anemia, asthma, atherosclerosis, autoimmune hemolytic anemia, autoimmune thyroiditis, benign prostatic hyperplasia, bronchitis, Chediak-Higashi syndrome, cholecystitis, Crohn'"'"'s disease, atopic dermatitis, dermnatomyositis, diabetes mellitus, emphysema, erythroblastosis fetalis, erythema nodosum, atrophic gastritis, glomerulonephritis, Goodpasture'"'"'s syndrome, gout, chronic granulomatous diseases, Graves'"'"' disease, Hashimoto'"'"'s thyroiditis, hypereosinophilia, irritable bowel syndrome, multiple sclerosis, myasthenia gravis, myocardial or pericardial inflammation, osteoarthritis, osteoporosis, pancreatitis, polycystic ovary syndrome, polymyositis, psoriasis, Reiter'"'"'s syndrome, rheumatoid arthritis, scleroderma, severe combined immunodeficiency disease (SCID), Sjogren'"'"'s syndrome, systemic anaphylaxis, systemic lupus erythematosus, systemic sclerosis, thrombocytopenic purpura, ulcerative colitis, uveitis, Werner syndrome, complications of cancer, hemodialysis, and extracorporeal circulation, viral, bacterial, fungal, parasitic, protozoal, and helminthic infection;

and adenocarcinoma, leukemia, lymphoma, melanoma, myeloma, sarcoma, teratocarcinoma, and, in particular, cancers of the adrenal gland, bladder, bone, bone marrow, brain, breast, cervix, gall bladder, ganglia, gastrointestinal tract, heart, kidney, liver, lung, muscle, ovary, pancreas, parathyroid, penis, prostate, salivary glands, skin, spleen, testis, thymus, thyroid, and uterus, akathesia, Alzheimer'"'"'s disease, amnesia, amyotrophic lateral sclerosis (ALS), ataxias, bipolar disorder, catatonia, cerebral palsy, cerebrovascular disease Creutzfeldt-Jakob disease, dementia, depression, Down'"'"'s syndrome, tardive dyskinesia, dystonias, epilepsy, Huntington'"'"'s disease, multiple sclerosis, muscular dystrophy, neuralgias, neurofibromatosis, neuropathies, Parkinson'"'"'s disease, Pick'"'"'s disease, retinitis pigmentosa, schizophrenia, seasonal affective disorder, senile dementia, stroke, Tourette'"'"'s syndrome and cancers including adenocarcinomas, melanomas, and teratocarcinomas, particularly of the brain.

50. The method of claim 48 wherein the condition is selected from the group consisting of cancers such as adenocarcinoma, leukemia, lymphoma, melanoma, myeloma, sarcoma, teratocarcinoma, and, in particular, cancers of the adrenal gland, bladder, bone, bone marrow, brain, breast, cervix, gall bladder, ganglia, gastrointestinal tract, heart, kidney, liver, lung, muscle, ovary, pancreas, parathyroid, penis, prostate, salivary glands, skin, spleen, testis, thymus, thyroid, and uterus;

immune disorders such as acquired immunodeficiency syndrome (AIDS), Addison'"'"'s disease, adult respiratory distress syndrome, allergies, ankylosing spondylitis, amyloidosis, anemia, asthma, atherosclerosis, autoimmune hemolytic anemia, autoimmune thyroiditis, bronchitis, cholecystitis, contact dermatitis, Crohn'"'"'s disease, atopic dermatitis, dermatomyositis, diabetes mellitus, emphysema, episodic lymphopenia with lymphocytotoxins, erythroblastosis fetalis, erythema nodosum, atrophic gastritis, glomerulonephritis, Goodpasture'"'"'s syndrome, gout, Graves'"'"' disease, Hashimoto'"'"'s thyroiditis, hypereosinophilia, irritable bowel syndrome, multiple sclerosis, myasthenia gravis, myocardial or pericardial inflammation, osteoarthritis, osteoporosis, pancreatitis, polymyositis, psoriasis, Reiter'"'"'s syndrome, rheumatoid arthritis, scleroderma, Sjogren'"'"'s syndrome, systemic anaphylaxis, systemic lupus erythematosus, systemic sclerosis, thrombocytopenic purpura, ulcerative colitis, uveitis, Werner syndrome, complications of cancer, hemodialysis, and extracorporeal circulation, viral, bacterial, fungal, parasitic, protozoal, and helminthic infections, trauma, X-linked agammaglobinemia of Bruton, common variable immunodeficiency (CVI), DiGeorge'"'"'s syndrome (thymic hypoplasia), thymic dysplasia, isolated IgA deficiency, severe combined immunodeficiency disease (SCID), immunodeficiency with thrombocytopenia and eczema (Wiskott-Aldrich syndrome), Chediak-Higashi syndrome, chronic granulomatous diseases, hereditary angioneurotic edema, and immunodeficiency associated with Cushing'"'"'s disease; and

developmental disorders such as renal tubular acidosis, anemia, Cushing'"'"'s syndrome, achondroplastic dwarfism, Duchenne and Becker muscular dystrophy, epilepsy, gonadal dysgenesis, WAGR syndrome (Wilms'"'"' tumor, aniridia, genitourinary abnormalities, and mental retardation), Smith-Magenis syndrome, myelodysplastic syndrome, hereditary mucoepithelial dysplasia, hereditary keratodermas, hereditary neuropathies such as Charcot-Marie-Tooth disease and neurofibromatosis, hypothyroidism, hydrocephalus, seizure disorders such as Syndenham'"'"'s chorea and cerebral palsy, spina bifida, anencephaly, craniorachischisis, congenital glaucoma, cataract, sensorineural hearing loss, and any disorder associated with cell growth and differentiation, embryogenesis, and morphogenesis involving any tissue, organ, or system of a subject, for example, the brain, adrenal gland, kidney, skeletal or reproductive system.

51. The method of claim 48 wherein the condition is selected from the group consisting of endocrinological disorders such as disorders associated with hypopituitarism including hypogonadism, Sheehan syndrome, diabetes insipidus, Kallman'"'"'s disease, Hand-Schuller-Christian disease, Letterer-Siwe disease, sarcoidosis, empty sella syndrome, and dwarfism;

hyperpituitarism including acromegaly, giantism, and syndrome of inappropriate antidiuretic hormone (ADH) secretion (SIADH); and

disorders associated with hypothyroidism including goiter, myxedema, acute thyroiditis associated with bacterial infection, subacute thyroiditis associated with viral infection, autoimmune thyroiditis (Hashimoto'"'"'s disease), and cretinism;

disorders associated with hyperthyroidism including thyrotoxicosis and its various forms, Grave'"'"'s disease, pretibial myxedema, toxic multinodular goiter, thyroid carcinoma, and Plummer'"'"'s disease; and

disorders associated with hyperparathyroidism including Conn disease (chronic hypercalemia);

respiratory disorders such as allergy, asthma, acute and chronic inflammatory lung diseases, ARDS, emphysema, pulmonary congestion and edema, COPD, interstitial lung diseases, and lung cancers;

cancer such as adenocarcinoma, leukemia, lymphoma, melanoma, myeloma, sarcoma, teratocarcinoma, and, in particular, cancers of the adrenal gland, bladder, bone, bone marrow, brain, breast, cervix, gall bladder, ganglia, gastrointestinal tract, heart, kidney, liver, lung, muscle, ovary, pancreas, parathyroid, penis, prostate, salivary glands, skin, spleen, testis, thymus, thyroid, and uterus; and

immunological disorders such as acquired immunodeficiency syndrome (AIDS), Addison'"'"'s disease, adult respiratory distress syndrome, allergies, ankylosing spondylitis, amyloidosis, anemia, asthma, atherosclerosis, autoimmune hemolytic anemia, autoimmune thyroiditis, bronchitis, cholecystitis, contact dermatitis, Crohn'"'"'s disease, atopic dermatitis, dermatomyositis, diabetes mellitus, emphysema, episodic lymphopenia with lymphocytotoxins, erythroblastosis fetalis, erythema nodosum, atrophic gastritis, glomerulonephritis, Goodpasture'"'"'s syndrome, gout, Graves'"'"' disease, Hashimoto'"'"'s thyroiditis, hypereosinophilia, irritable bowel syndrome, multiple sclerosis, myasthenia gravis, myocardial or pericardial inflammation, osteoarthritis, osteoporosis, pancreatitis, polymyositis, psoriasis, Reiter'"'"'s syndrome, rheumatoid arthritis, scleroderma, Sjogren'"'"'s syndrome, systemic anaphylaxis, systemic lupus erythematosus, systemic sclerosis, thrombocytopenic purpura, ulcerative colitis, uveitis, Werner syndrome, complications of cancer, hemodialysis, and extracorporeal circulation, viral, bacterial, fungal, parasitic, protozoal, and helminthic infections, and trauma.

28. A method of providing a health care service, comprising:

providing access to an analysis engine that is informationally coupled to a medical records storage device, wherein the storage device stores a differential genetic sequence object for a patient;

producing, by the analysis engine, a patient-specific data set using presence of a local differential string or constellation of a plurality of local differential strings in the differential genetic sequence object for the patient; and

producing, by the analysis engine, a patient-specific instruction based on the patient-specific data set.

29. The method of claim 28 wherein the medical records storage device is configured as a smart-card and is carried by the patient.

30. The method of claim 28 wherein the medical records storage device is remotely accessible by a healthcare provider.

31. The method of claim 28 wherein the differential genetic sequence object for the patient comprises a plurality of local differential strings for at least two chromosomes.

32. The method of claim 28 wherein the differential genetic sequence object for the patient comprises a plurality of local differential strings for substantially the entire genome of the patient.

33. The method of claim 28 wherein the differential genetic sequence object for the patient comprises a plurality of local differential strings representing at least two tissue types, or at least two temporally spaced results for the same tissue.

34. The method of claim 33 wherein the at least two temporally spaced results for the same tissue are obtained from before and after commencement of a treatment.

35. The method of claim 28 wherein the patient-specific instruction is selected from the group consisting of a diagnosis, a prognosis, a prediction of treatment outcome, a recommendation for a treatment strategy, and a prescription.

36. A method of analyzing a population, comprising:

obtaining and storing a plurality of differential genetic sequence objects in a medical records database of a population, wherein the records database is informationally coupled to an analysis engine;

identifying, by the analysis engine, a constellation of a plurality of local differential strings within the plurality of differential genetic sequence objects to produce a constellation record; and

using, by the analysis engine, the constellation record to generate a population analysis record.

37. The method of claim 36 wherein the population comprises a plurality of blood relatives.

38. The method of claim 36 wherein the population comprises a plurality of members characterized by sharing at least one common feature selected from the group consisting of exposure to a pathogen, exposure to a noxious agent, health history, treatment history, treatment success, gender, species, and age.

39. The method of claim 36 wherein the population comprises a plurality of members characterized by sharing at least one common feature selected from the group consisting of geographic location, ethnicity, and occupation.

40. The method of claim 36 wherein the population analysis record comprises paternity or maternity confirmation.

41. The method of claim 36 further comprising a step of comparing a constellation record of an individual patient with the population analysis record.

42. The method of claim 41 wherein the step of comparing of the constellation record of the individual patient with the population analysis record creates a patient-specific record.

43. The method of claim 42 wherein the patient-specific record comprises a risk assessment or an identification of the patient as belonging to a specified population.

44. The method of claim 42 wherein the patient-specific record comprises a diagnosis, a prognosis, a prediction of treatment outcome, a recommendation for a treatment strategy, and a prescription.

45. A method of analyzing a differential genetic sequence object of a person, comprising:

storing a reference differential genetic sequence object in a medical records database that is informationally coupled to an analysis engine;

calculating, by the analysis engine, a deviation between a plurality of local differential strings in the differential genetic sequence object of the person and a plurality of local differential strings in the reference differential genetic sequence object to produce a deviation record;

using, by the analysis engine, the deviation record to generate a person-specific deviation profile.

46. The method of claim 45 wherein the reference differential genetic sequence object is calculated from a plurality of local differential strings of the person.

47. The method of claim 45 wherein the reference differential genetic sequence object is calculated from a plurality of local differential strings of the person.