Methods and systems for selecting nucleic acid probes for microarrays

• US 20050282174A1
• Filed: 06/19/2004
• Published: 12/22/2005
• Est. Priority Date: 06/19/2004
• Status: Abandoned Application

• Current Assignee: Agilent Technologies, Inc.
• Original Assignee: Agilent Technologies, Inc.
• Inventors: Shannon, Karen W., Gao, Jing, Collins, Patrick J., Webb, Peter G., Fulmer-Smentek, Stephanie B.
• Application Number:
  US10/871,303
• Publication Number:
  US 20050282174A1
• Time in Patent Office: Days
• US Class Current: 435/6.11
• CPC Class Codes: G16B 25/00 ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
• CPC Class Codes: G16B 25/20 Polymerase chain reaction [PCR]; Primer or probe design; Probe optimisation
• 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: G16B 40/10 Signal processing, e.g. from mass spectrometry [MS] or from PCR

Abstract

Methods and systems for identifying and selecting nucleic acid probes for detecting a target with a nucleic acid probe array or microarray, comprising selecting a plurality of candidate probes, forming a plurality of clusters from the plurality of candidate probes according to hybridization characteristics of the candidate probes, forming at least one SuperCluster from the clusters; and selecting at least one probe from each SuperCluster for the probe array.

Claims

1. A method for identifying and selecting nucleic acid probes for detecting a target with a probe array, said method comprising:

selecting a plurality of candidate probes;

forming a plurality of clusters from said plurality of candidate probes according to hybridization characteristics of said candidate probes to a target sequence;

forming at least one SuperCluster from said clusters; and

selecting at least one probe from each said SuperCluster for said probe array.

2. The method of claim 1, wherein said hybridization characteristics for said plurality of probes are measured using a plurality of different tissue samples comprising said target sequence.

3. The method of claim 1, wherein only a single probe is selected from each said SuperCluster.

4. The method of claim 3, further comprising forming a microarray from said probes selected from said SuperClusters wherein said array includes only one probe from each said SuperCluster.

5. The method of claim 1, further comprising:

identifying clusters that do not belong to any SuperCluster; and

identifying at least one alternative splice form from said clusters that do not belong to any SuperCluster.

6. The method of claim 2, wherein said forming said plurality of clusters from said plurality of candidate probes comprises:

forming a plurality of microarrays, each said microarrays comprising said plurality of candidate probes;

hybridizing each of said plurality of microarrays to nucleic acids from each of said plurality of different tissue samples; and

clustering said candidate probes based on mutually consistent differential expression of said target sequence across said plurality of different tissue samples.

7. The method of claim 1, further comprising identifying outlier probes not associated with any of said clusters.

8. The method of claim 1, further comprising identifying outlier probes each associated with one of said clusters, based on a metric different from a metric used for said forming a plurality of clusters.

9. The method of claim 8, wherein said metric different from a metric used for said forming a plurality of clusters comprises Euclidean distance measurement.

10. The method of claim 1, further comprising:

compiling and aligning a plurality of nucleic acid transcripts to identify sequence redundancy in said transcripts; and

identifying a consensus region for said plurality of transcripts.

11. The method of claim 10, wherein said plurality of candidate probes are associated with said consensus region.

12. A method comprising forwarding a result obtained from the method of claim 1 to a remote location.

13. A method comprising transmitting data representing a result obtained from the method of claim 1 to a remote location.

14. A method comprising receiving a result obtained from a method of claim 1 from a remote location.

15. A method for identifying and selecting nucleic acid probes for detecting a target with a probe array, said method comprising:

selecting a plurality of candidate probes from a consensus region associated with a plurality of nucleic acid transcripts;

hybridizing nucleic acids from each of a plurality of tissue samples to each of a plurality of microarrays, each of said microarrays comprising said plurality of candidate probes;

forming a plurality of clusters from said plurality of probes according to hybridization characteristics of said candidate probes across said different tissue samples;

forming at least one SuperCluster from said clusters; and

selecting at least one probe from each said SuperCluster for said probe array.

16. The method of claim 15, further comprising identifying outlier probes not associated with any of said clusters.

17. The method of claim 15, further comprising identifying outlier probes each associated with one of said clusters, based on a metric different from a metric used for said forming a plurality of clusters.

18. The method of claim 17, wherein said metric different from a metric used for said forming a plurality of clusters comprises Euclidean distance measurement.

19. The method of claim 16, further comprising identifying SuperCluster outliers not associated with said SuperCluster.

20. The method of claim 15, further comprising:

compiling and aligning a plurality of nucleic acid transcripts to identify sequence redundancy in said transcripts; and

identifying a consensus region for said plurality of transcripts.

21. The method of claim 20, wherein said plurality of candidate probes are associated with said consensus region.

22. A method comprising forwarding a result obtained from the method of claim 15 to a remote location.

23. A method comprising transmitting data representing a result obtained from the method of claim 15 to a remote location.

24. A method comprising receiving a result obtained from a method of claim 15 from a remote location.

25. A system for identifying and selecting nucleic acid probes for detecting a target with a probe array, said system comprising:

means for selecting a plurality of candidate probes;

means for forming a plurality of clusters from said plurality of candidate probes according to hybridization characteristics of said candidate probes to a target sequence;

means for forming at least one SuperCluster from said clusters; and

means for selecting at least one probe from each said SuperCluster for said probe array.

26. The system of claim 25, further comprising means for identifying outlier probes not associated with any of said clusters.

27. The system of claim 25, further comprising means for identifying outlier probes each associated with one of said clusters, based on a metric different from a metric used for said forming a plurality of clusters.

28. The system of claim 27, wherein said metric different from a metric used for said forming a plurality of clusters comprises Euclidean distance measurement.

29. The system of claim 25, further comprising means for identifying SuperCluster outliers not associated with any of said SuperClusters.

30. The system of claim 25, further comprising:

means for compiling and aligning a plurality of nucleic acid transcripts to identify any sequence redundancy in said transcripts; and

means for identifying a consensus region for said plurality of transcripts.

31. A computer readable medium carrying one or more sequences of instructions for identifying and selecting nucleic acid probes for detecting a target with a probe array, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the steps of:

selecting a plurality of candidate probes;

forming a plurality of clusters from said plurality of candidate probes according to hybridization characteristics of said candidate probes to a target sequence;

forming at least one SuperCluster from said clusters; and

selecting at least one probe from each said SuperCluster for said probe array.

32. A computer readable medium carrying one or more sequences of instructions for identifying and selecting nucleic acid probes for detecting a target with a probe array, wherein execution of one or more sequences of instructions by one or more processors causes the one or more processors to perform the steps of:

selecting a plurality of candidate probes from a consensus region associated with a plurality of nucleic acid transcripts;

hybridizing nucleic acids from each of a plurality of tissue samples to each of a plurality of microarrays, each of said microarrays comprising said plurality of candidate probes;

forming a plurality of clusters from said plurality of probes according to hybridization characteristics of said candidate probes across said different tissue samples;

forming at least one SuperCluster from said clusters; and

selecting at least one probe from each said SuperCluster for said probe array.