Method and system to characterize transcriptionally active regions and quantify sequence abundance for large scale sequencing data

1. A computer-implemented method for determining a quantitative measure for an RNA expression profile of a biological sample containing sequences of nucleotides, the method comprising:

for each of a plurality of output sequences from the biological sample:

receiving, information of an alignment of the respective output sequence onto a reference sequence that has a nucleotide at each of a plurality of nucleotide positions, the alignment aligning the output sequences to specific nucleotide positions of the reference sequence, wherein at least a portion of the output sequences are derived from RNA, and wherein the reference sequence includes at least a portion of a genome;

calculating a count histogram for the reference sequence based on the alignment of the plurality of output sequences onto the reference sequence, the count histogram including a respective coverage count for each nucleotide position of the reference sequence, wherein calculating the count histogram includes:

for each nucleotide position of the reference sequence:

determining, the corresponding coverage count for the respective nucleotide position by determining the number of output sequences that align to the respective nucleotide position of the reference sequence;

locating a first contiguous region in the count histogram where the coverage count for each nucleotide position in the first contiguous region is equal to or greater than a threshold; and

calculating a first abundance score for the first contiguous region, wherein an abundance score includes an average of the coverage count for each nucleotide position in a contiguous region; wherein the method is performed by a computer.

2. The computer-implemented method of claim 1 , further comprising:

identifying the first contiguous region of the plurality of nucleotide positions of the reference sequence as being a transcriptionally active region.

3. The computer-implemented method of claim 2 , further comprising

using the identified transcriptionally active region as a biomarker to differentiate between different types of biological samples.

4. The computer-implemented method of claim 3 , wherein the different types of biological samples include tumor and normal samples.

5. The computer-implemented method of claim 1 , wherein the threshold is a fractional number.

6. The computer-implemented method of claim 1 , wherein the first contiguous region of the reference sequence is required to be equal to or greater than a minimum length.

7. The computer-implemented method of claim 6 , wherein the minimum length is 20 nucleotides, and wherein the threshold is greater than or equal to three.

8. The computer-implemented method of claim 1 , wherein the first abundance score is calculated as a sum of all the coverage counts for the first contiguous region divided by the length of the first contiguous region, and wherein the length is the number of nucleotide positions in the first contiguous region.

9. The computer-implemented method of claim 1 , wherein the human genome is used as the reference sequence.

10. The computer-implemented method of claim 1 , wherein the reference sequence is a predetermined target gene sequence for which the RNA expression profile is being determined.

11. The computer-implemented method of 10 , wherein the threshold is zero for the predetermined target gene sequence.

12. The computer-implemented method of claim 1 , wherein the reference sequence is assembled from a consensus of the output sequences.

13. The computer-implemented method of claim 1 , further comprising:

determining a second coverage count for each of the nucleotide positions of the reference sequence using second output sequences from a different biological sample;

locating a second contiguous region of the plurality of nucleotide positions where the second coverage count for each nucleotide position is equal to or greater than the threshold;

calculating a second abundance score for the second contiguous region;

comparing the first abundance score to the second abundance score; and

determining that one of the biological samples is a disease sample based on the comparison.

14. The computer-implemented method of claim 13 , further comprising:

identifying the second contiguous region for comparison to the first contiguous region by determining an overlap between the first contiguous region and the second contiguous region.

15. The computer-implemented method of claim 14 , wherein determining an overlap between the first contiguous region and the second contiguous region includes:

representing each of the first contiguous region and the second contiguous region with reference coordinates based on nucleotide positions of an alignment to the reference sequence, wherein the reference coordinates include sequence start and end positions; and

comparing the start and end positions of the first contiguous region to the start and end positions of the second contiguous region.

16. The computer-implemented method of claim 15 , wherein the reference coordinates of a contiguous region are implemented with the start position less than or equal to the end position, or with the start position always greater than or equal to the end position.

17. The computer-implemented method of claim 15 , wherein the reference coordinates are comprised of a chromosome location, strand, a start position and an end position according to an alignment onto the reference sequence.

18. The computer-implemented method of claim 17 , wherein the chromosome location of the first contiguous region equals the chromosome location of the second contiguous region, and wherein the strand of the first contiguous region equals the strand of the second contiguous region.

19. The computer-implemented method of claim 15 , wherein a minimum overlap length is required for a determination that the first contiguous region and the second contiguous region overlap.

20. The computer-implemented method of claim 1 , further comprising:

determining an overlap between the first contiguous region and another sequence of nucleotides by:

representing each of the first contiguous region and the another sequence with reference coordinates based on nucleotide positions of an alignment to the reference sequence, wherein the reference coordinates include sequence start and end positions; and

comparing the start and end positions of the first contiguous region to the start and end positions of the another sequence; and

if an overlap exists, associating the first contiguous region with the another sequence.

21. The computer-implemented method of claim 20 , wherein the reference coordinates are comprised of a chromosome location, strand, a start position and an end position according to an alignment onto the reference sequence.

22. The computer-implemented method of claim 20 , wherein a minimum overlap length is required for a determination that the first contiguous region and the another sequence overlap.

23. A system for determining a quantitative measure for an RNA expression profile of a biological sample containing sequences of nucleotides, the system comprising:

a database storing, for each of a plurality of output sequences from the biological sample:

information of an alignment of the respective output sequence onto a reference sequence that has a nucleotide at each of a plurality of nucleotide positions, the alignment aligning the output sequences to specific nucleotide positions of the reference sequence, wherein at least a portion of the output sequences are derived from RNA, and wherein the reference sequence includes at least a portion of a genome; and

one or more processors that are communicably coupled with the database and that are programmed to:

calculate a count histogram for the reference sequence based on the alignment of the plurality of output sequences onto the reference sequence, the count histogram including a respective coverage count for each nucleotide position of the reference sequence, wherein calculating the count histogram includes:

for each nucleotide position of the reference sequence:

determine the corresponding coverage count for the respective nucleotide position by determining the number of output sequences that align to the respective nucleotide position of the reference sequence;

locate a first contiguous region in the count histogram where the coverage count for each nucleotide position in the first contiguous region is equal to or greater than a threshold; and

calculate a first abundance score for the first contiguous region, wherein an abundance score includes an average of the coverage count for each nucleotide position in a contiguous region.

24. The system of claim 23 , wherein the one or more processors are further programmed to:

determine a second coverage count for each of the nucleotide positions of the reference sequence using second output sequences from a different biological sample;

locate a second contiguous region of the plurality of nucleotide positions where the second coverage count for each nucleotide position is equal to or greater than the threshold;

calculate a second abundance score for the second contiguous region;

compare the first abundance score to the second abundance score; and

determine that one of the biological samples is a disease sample based on the comparison.

25. The system of claim 23 , further comprising:

a computer output device that is coupled with the one or more processors and that displays the first contiguous region with the first abundance score.

26. A computer-implemented method for determining a transcriptionally active region of a reference sequence associated with a biological sample containing sequences of nucleotides, the method comprising:

for each of a plurality of output sequences from the biological sample:

receiving, information of an alignment of the respective output sequence onto a reference sequence that has a nucleotide at each of a plurality of nucleotide positions, the alignment aligning the output sequences to specific nucleotide positions of the reference sequence, wherein at least a portion of the output sequences are derived from RNA, and wherein the reference sequence includes at least a portion of a genome;

calculating a count histogram for the reference sequence based on the alignment of the plurality of output sequences onto the reference sequence, the count histogram including a respective coverage count for each nucleotide position of the reference sequence, wherein calculating the count histogram includes:

for each nucleotide position of the reference sequence:

determining, the corresponding coverage count for the respective nucleotide position by determining the number of output sequences that align to the respective nucleotide position of the reference sequence;

locating a first contiguous region in the count histogram where the coverage count for each nucleotide position in the first contiguous region is equal to or greater than a threshold; and

identifying the first contiguous region of the plurality of nucleotide positions of the reference sequence as being a transcriptionally active region; wherein the method is performed by a computer.

27. The computer-implemented method of claim 26 , further comprising

using the identified transcriptionally active region as a biomarker to differentiate between different types of biological samples.

28. The computer-implemented method of claim 27 , wherein the different types of biological samples include tumor and normal samples.

29. The computer-implemented method of claim 26 , wherein the first contiguous region of the reference sequence is required to be equal to or greater than a minimum length.

30. The computer-implemented method of claim 29 , wherein the minimum length is 20 nucleotides, and wherein the threshold is greater than or equal to three.

31. The computer-implemented method of claim 26 , wherein the human genome is used as the reference sequence.

32. The computer-implemented method of claim 26 , wherein the reference sequence is a predetermined target gene sequence for which the RNA expression profile is being determined.

33. The computer-implemented method of claim 32 , wherein the threshold is zero for the predetermined target gene sequence.

34. The computer-implemented method of claim 26 , wherein the reference sequence is assembled from a consensus of the output sequences.

35. The computer-implemented method of claim 26 , further comprising:

determining an overlap between the first contiguous region and another sequence of nucleotides by:

representing each of the first contiguous region and the another sequence with reference coordinates based on nucleotide positions of an alignment to the reference sequence, wherein the reference coordinates include sequence start and end positions; and

comparing the start and end positions of the first contiguous region to the start and end positions of the another sequence; and

if an overlap exists, associating the first contiguous region with the another sequence.

36. The computer-implemented method of claim 35 , wherein the reference coordinates are comprised of a chromosome location, strand, a start position and an end position according to an alignment onto the reference sequence.

37. The computer-implemented method of claim 35 , wherein a minimum overlap length is required for a determination that the first contiguous region and the another sequence overlap.

38. A system for determining a transcriptionally active region of a reference sequence associated with a biological sample containing sequences of nucleotides, the system comprising:

a database storing, for each of a plurality of output sequences from the biological sample:

information of an alignment of the respective output sequence onto a reference sequence that has a nucleotide at each of a plurality of nucleotide positions, the alignment aligning the output sequences to specific nucleotide positions of the reference sequence, wherein at least a portion of the output sequences are derived from RNA, and wherein the reference sequence includes at least a portion of a genome; and

one or more processors that are communicably coupled with the database and that are programmed to:

calculate a count histogram for the reference sequence based on the alignment of the plurality of output sequences onto the reference sequence, the count histogram including a respective coverage count for each nucleotide position of the reference sequence, wherein calculating the count histogram includes:

for each nucleotide position of the reference sequence:

determine the corresponding coverage count for the respective nucleotide position by determining the number of output sequences that align to the respective nucleotide position of the reference sequence;

locate a first contiguous region in the count histogram where the coverage count for each nucleotide position in the first contiguous region is equal to or greater than a threshold; and

identify the first contiguous region of the plurality of nucleotide positions of the reference sequence as being a transcriptionally active region.

39. The system of claim 38 , further comprising:

a computer output device that is coupled with the one or more processors and that displays the first contiguous region as being a transcriptionally active region.