Cross Talk Compensation

Abstract

Method and system for compensating intensity biases in a plurality of digital images. Each digital image of the plurality of digital images contains a plurality of objects and each of the plurality of objects is configured to receive at least one molecule comprising genetic information, wherein the at least one molecule is configured to receive one of at least a first fluorescent compound and a second fluorescent compound. A first digital image of the plurality of digital images is taken by an optical imaging system during emission of electromagnetic radiation by the first fluorescent compound, and a second digital image of the plurality of digital images is taken by the optical imaging system during emission of electromagnetic radiation by the second fluorescent compound.

Claims

1. (canceled)

2. A method of cross-talk compensation in a plurality of digital images, wherein: each digital image of the plurality of digital images contains image information about a plurality of objects, each of the plurality of objects being configured to receive at least one molecule comprising genetic information, the at least one molecule being configured to receive one of at least a first fluorescent compound and a second fluorescent compound, a first digital image of the plurality of digital images being taken by an optical imaging system during emission of electromagnetic radiation by the first fluorescent compound, a second digital image of the plurality of digital images being taken by the optical imaging system during emission of electromagnetic radiation by the second fluorescent compound, wherein the method comprises: determining a first intensity value from the first digital image for each object; determining a second intensity value from the second digital image for each object, the first and second intensity values defining data points, each data point comprising a first intensity value and a second intensity value; specifying a subset of the data points; determining a cross-correlation between the first and second intensity values of the subset of the data points using a polynomial fitting method or a random sample consensus algorithm; and determining compensated intensity values based on the first intensity values, the second intensity values, and the cross-correlation between the first intensity values and the second intensity values.

3. The method of claim 2, further comprising: determining noise offsets based on the first and second intensity values; and subtracting the determined noise offsets from the first and second intensity values.

4. The method of claim 2, further comprising: determining a first intensity distribution for the first intensity values and a second intensity distribution for the second intensity values; determining a scaling function between the first intensity distribution and the second intensity distribution; and rescaling the first or second intensity values with the scaling function.

5. The method of claim 2, wherein the specifying the subset of the data points further comprises: specifying the subset of the data points by receiving a selection of a region of interest in the first and second digital images.

6. The method of claim 2, further comprising: determining a cross-talk matrix based on the cross-correlation between the first and second intensity values.

7. The method of claim 2, further comprising: in response to the specifying the subset of the data points, grouping the subset of the data points into a plurality of groups with fixed borders or having a fixed number of data points, wherein each group of the plurality of groups comprises one representative data point.

8. The method of claim 7, wherein the determining the cross-correlation comprises determining the cross-correlation between the first and second intensity values for only the representative data points.

9. A system for cross-talk compensation in at least a first digital image and a second digital image, wherein: each digital image of the at least first and second digital images contains a plurality of objects, each of the plurality of objects being configured to receive at least one molecule comprising genetic information, the at least one molecule being configured to receive one of at least a first fluorescent compound and a second fluorescent compound, the first digital image being taken by an optical imaging system during emission of electromagnetic radiation by the first fluorescent compound, the second digital image being taken by the optical imaging system during emission of electromagnetic radiation by the second fluorescent compound, the system comprising: a memory; and at least one processor coupled to the memory and configured to: determine a first intensity value from the first digital image for each object; determine a second intensity value from the second digital image for each object, the first and second intensity values defining data points, each data point comprising a first intensity value and a second intensity value; specify a subset of the data points; determine a cross-correlation between the first and second intensity values of the subset of the data points using a polynomial fitting method or a random sample consensus algorithm; and determine compensated intensity values based on the first intensity values, the second intensity values, and the cross-correlation between the first intensity values and the second intensity values.

10. The system of claim 9, wherein the at least one processor is further configured to: determine noise offsets based on the first and second intensity values; and subtract the determined noise offsets from the first and second intensity values.

11. The system of claim 9, wherein the at least one processor is further configured to: determine a first intensity distribution for the first intensity values and a second intensity distribution for the second intensity values; determine a scaling function between the first intensity distribution and the second intensity distribution; and rescale the first or second intensity values with the scaling function.

12. The system of claim 9, wherein to specify the subset of the data points the at least one processor is further configured to: specify the subset of the data points by receiving a selection of a region of interest in the first and second digital images.

13. The system of claim 9, wherein the at least one processor is further configured to: determine a cross-talk matrix based on the cross-correlation between the first and second intensity values.

14. The system of claim 9, wherein the at least one processor is further configured to: in response to the specifying the subset of the data points, group the subset of the data points into a plurality of groups with fixed borders or having a fixed number of data points, wherein each group of the plurality of groups comprises one representative data point.

15. The system of claim 14, wherein to determine the cross-correlation the at least one processor is further configured to determine the cross-correlation between the first and second intensity values for only the representative data points.

16. A computer program product comprising a non-transitory computer readable media, wherein: each digital image of a plurality of digital images contains image information about a plurality of objects, each of the plurality of objects being configured to receive at least one molecule comprising genetic information, the at least one molecule being configured to receive one of at least a first fluorescent compound and a second fluorescent compound, a first digital image of the plurality of digital images being taken by an optical imaging system during emission of electromagnetic radiation by the first fluorescent compound, a second digital image of the plurality of digital images being taken by the optical imaging system during emission of electromagnetic radiation by the second fluorescent compound, wherein the non-transitory computer readable media comprises computer executable instructions for performing the following steps: determining a first intensity value from the first digital image for each object; determining a second intensity value from the second digital image for each object, the first and second intensity values defining data points, each data point comprising a first intensity value and a second intensity value; specifying a subset of the data points; determining a cross-correlation between the first and second intensity values of the subset of the data points using a polynomial fitting method or a random sample consensus algorithm; and determining compensated intensity values based on the first intensity values, the second intensity values, and the cross-correlation between the first intensity values and the second intensity values.

17. The computer program product of claim 16, wherein the non-transitory computer readable media further comprises computer executable instructions for performing the following steps determining noise offsets based on the first and second intensity values; and subtracting the determined noise offsets from the first and second intensity values.

18. The computer program product of claim 16, wherein the non-transitory computer readable media further comprises computer executable instructions for performing the following steps: determining a first intensity distribution for the first intensity values and a second intensity distribution for the second intensity values; determining a scaling function between the first intensity distribution and the second intensity distribution; and rescaling the first or second intensity values with the scaling function.

19. The computer program product of claim 16, wherein the specifying comprises: specifying the subset of the data points by receiving a selection of a region of interest in the first and second digital images.

20. The computer program product of claim 16, wherein the non-transitory computer readable media further comprises computer executable instructions for performing the following steps: in response to the specifying the subset of the data points, grouping the subset of the data points into a plurality of groups with fixed borders or having a fixed number of data points, wherein each group of the plurality of groups comprises one representative data point

21. The computer program product of claim 20, wherein the determining the cross-correlation comprises determining the cross-correlation between the first and second intensity values for only the representative data points.

Description

BRIEF DESCRIPTION OF THE FIGURES

[0077] FIG. 1 illustrates a method according to an exemplary embodiment of the invention.

[0078] FIG. 2 illustrates a system according to an exemplary embodiment of the invention.

[0079] FIG. 3 illustrates an ideal signal of the different channels.

[0080] FIG. 4 illustrates cross-talk effects between the different channels.

[0081] FIG. 5 illustrates the interdependence of intensity values between two different channels.

[0082] FIG. 6 illustrates the images taken in different cycles according to an embodiment of the present invention.

[0083] FIG. 7 illustrates noise-offset effects and their correction according to an embodiment of the invention.

[0084] FIG. 8 illustrates channel-scaling effects and their correction according to an embodiment of the invention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

[0085] FIG. 1 illustrates a method according to an exemplary embodiment of the invention. The method is adapted for compensating intensity biases and in particular cross talk effects in a plurality of digital images. Each digital image of the plurality of digital images contains a plurality of objects, wherein each of the plurality of objects is configured to receive at least one molecule comprising genetic information. The at least one molecule is configured to receive one of at least a first fluorescent compound and a second fluorescent compound. A first digital image of the plurality of digital images is taken by an optical imaging system during emission of electromagnetic radiation by the first fluorescent compound and a second digital image of the plurality of digital images is taken by the optical imaging system during emission of electromagnetic radiation by the second fluorescent compound. The method comprises the following steps, preferably in the following order: [0086] S1: determining a first intensity value from the first digital image for each object; [0087] S2: determining a second intensity value from the second digital image for each object, the first and second intensity values defining data points, each data point comprising a first intensity value and a second intensity value; [0088] S3: specifying a subset of the data points; [0089] S4: determining a relation between the respective first and second intensity values on the basis of only the subset of the data points; and [0090] S5: determining compensated first intensity values on the basis of the first intensity values, the second intensity values, and the relation between the first intensity values and the second intensity values.

[0091] According to an exemplary embodiment of the invention, the method may further comprise the following steps: [0092] S6: determining noise offsets on the basis of the first and second intensity values; and [0093] S7: subtracting the determined noise offsets from the first and second intensity values.

[0094] According to an exemplary embodiment of the invention, the method may further comprising the following steps: [0095] S8: determining a first intensity distribution for the first intensity values and a second intensity distribution for the second intensity values; [0096] S9: determining a scaling function between the first intensity distribution and the second intensity distribution; [0097] S10: rescaling the first and/or second intensity values with the scaling function.

[0098] According to an exemplary embodiment of the invention, the subset of data points is specified (step S3) by selecting a region of interest in the first and second digital images. However, the subset may also alternatively or additionally be specified by selecting one or more cycles of the plurality of cycles as described in more detail with respect to FIG. 6.

[0099] According to an exemplary embodiment of the invention, the relation between the first and second intensity values and the noise-offset is expressed in form of a cross-talk matrix, i.e. the cross-talk matrix is determined on the basis of the relation between the first and second intensity values. As described before, the (n+1×n+1) cross-talk matrix A, where n equals the number of channels may be written as

[00003]$\begin{array}{cccc}{\beta }_{0,0}& \mathrm{.Math.}& {\beta }_{0,n}& 0\\ \mathrm{.Math.}& \ddots & \mathrm{.Math.}& 0\\ {\beta }_{n,0}& \mathrm{.Math.}& {\beta }_{n,n}& 0\\ {\mathrm{.Math.}}_0^{\prime }& \mathrm{.Math.}& {\mathrm{.Math.}}_n^{\prime }& 1\end{array}\hspace{1em}$

[0100] A vector of emitted intensity values (e) of length n may be gained by multiplying a vector of determined intensity values (d) of length n+1 (d.sub.n+1=1) with the cross talk matrix A:

d=e*A

[0101] Thus, the emitted intensity values (i.e. the compensated intensity values) can be determined by means of the inverted matrix A.sup.1:

e=d*A.sup.−1

[0102] According to a further exemplary embodiment of the invention, the method is further adapted for determining compensated first and second intensity values on the basis of the first and second intensity values as well as the relation between the first and second intensity values.

[0103] Moreover, in the method, only objects having received a molecule with genetic information may be selected, i.e., the subset of data points may only comprise intensity values of objects that have received such a molecule.

[0104] FIG. 2 illustrates a system according to the present invention. The system comprises an intensity determination unit 201, a subset determination unit 202, and a cross-talk compensation unit 203.

[0105] According to an exemplary embodiment, the system may further comprise a noise-offset compensation unit 204. According to another exemplary embodiment, the system may further comprise an intensity-scaling compensation unit 205. All of these units are configured to execute one or more of the steps of the present invention. While the present invention is described using independent units 201, 202, 203, 204, 205 it is apparent that the independent units can also be part of one single unit as long as the steps of the present invention are executed.

[0106] The intensity determination unit 201 is configured for determining a first intensity value for each object from the first digital image and a second intensity value for each object from the second digital image. Thus, for each object, a first and second intensity value may be determined. However, it may be possible that a first and/or second intensity value is not determined for some objects, e.g., because one object is lost.

[0107] The subset determination unit 202 receives the determined first and second intensity values. It may be understood that the first and second intensity values come in pairs and that each pair of first and second intensity values defines a data point. Furthermore, the subset determination unit 202 is configured for specifying a subset of the data points. This may be carried out as described in the context of the present invention.

[0108] The cross-talk compensation unit 203 receives the subset of the intensity values. On the basis of said subset, the cross-talk compensation unit 203 determines a relation between the first and second intensity values. This may, e.g., be carried out as described in the context of the present invention. Furthermore, the cross-talk compensation unit 203 is configured for determining compensated first intensity values on the basis of the first intensity values, the second intensity values, and the relation between the first intensity values and the second intensity values.

[0109] According to an exemplary embodiment of the invention, the cross-talk compensation unit 203 also receives the determined first and second intensity values and determines compensated first intensity values on the basis of the first intensity values, the second intensity values, and the relation between the first and second intensity values.

[0110] The noise-offset compensation unit 204 receives a subset of the intensity values. The intensity values may be received from the intensity determination unit 201 or from the cross-talk compensation unit 203. The subset may be the same or a distinct subset received by the cross-talk compensation unit. The noise-offset compensation unit is configured to determine the channel-specific noise offset values and compensate for this offset.

[0111] The channel-scaling compensation unit 205 receives a subset of intensity values. The intensity values may be received from the intensity determination unit 201, the cross-talk compensation unit 203 or the noise-offset compensation unit 204. The channel-scaling compensation unit is configured to determine the channel-specific intensity value distribution and compensate for distinct distributions.

[0112] The functionality of the intensity determination unit 201, the subset determination unit 202, the cross-talk compensation unit 203, the noise-offset compensation unit 204, and the channel-scaling compensation unit 205 is further described in terms of method steps in the in the exemplary embodiments of the present invention. It is obvious for a person skilled in the art that the following description of method steps gives rise to corresponding functions of the intensity determination unit 201, the subset determination unit 202, the cross-talk compensation unit 203, the noise-offset compensation unit 204, and the channel-scaling compensation unit 205 or a further unit.

[0113] FIG. 3 shows the signal strength determined from four cycles for one bead. Each of the cycles comprises four images, wherein FIG. 3 illustrates the signal strength for the respective channels G, C, A, T, i.e. the base call for that specific cycle. That is, in an ideal case each channel would provide a single signal for each channel. However, due to different parasitic effects, like auto-fluorescence effects and cross-talk effects between different channels, the signals for the different channels are most likely to be different from the ideal case.

[0114] FIG. 4 illustrates an exemplary cross-talk effect. In comparison to the ideal case illustrated by FIG. 3, not only the main signal has a value different from zero but also the other channels show non-zero values, due to overlapping fluorescent spectra. That is, due to an overlap in the dye (fluorescent compound) emission frequencies an interdependency between pairs of color channels can be observed (cross-talk). Consequently, bead intensities are inherently biased. This crosstalk between different channels is compensated with the method and system described in the context of the present invention.

[0115] FIG. 5 also illustrates an exemplary cross-talk effect. In the diagram of FIG. 5, the first intensity values are plotted against the second intensity values. In this example, the first intensity values correspond to the intensities of the yellow channel and the second intensity values correspond to the intensities of the green channel. Each point 500 in the diagram corresponds to a data point, i.e. a pair of first and second intensity values. The relation between the first and second intensity values is exemplarily shown with the dashed line 501. According to exemplary embodiments, this relation is determined with a polynomial fitting method or a RANSAC algorithm. For this purpose, the data points may be grouped into a plurality of groups, wherein each group is represented by one data point. I.e., the data points can be grouped into bins 502. These bins are then used for determining the relation between the first and second intensity values. According to exemplary embodiments of the invention, the bins 502 are bins with fixed borders or bins with a fixed number of data points.

[0116] FIG. 6 illustrates the images 11-14, 21-24, 31-34, 41-44, 51-54 taken in a plurality of cycles 10-50 of the method. This illustration should not be construed as limiting as of the amount of images taken in a corresponding cycle or the amounts of cycles. As can be seen in FIG. 6 in each of the cycles 10-50 four images 11-14, 21-24, 31-34, 41-44, 51-54 are taken, i.e. acquired, captured etc., in this example. In particular, each of the four images 11-14, 21-24, 31-34, 41-44, 51-54 in one cycle 10-50 corresponds to one channel of the optical imaging system, i.e. red, green, yellow and blue. For example, every first image may be taken with a first color filter, every second image with a second color filter, every third image with a third color filter, and every fourth image with a fourth color filter. The different colors are emitted by fluorescent compounds carried by different molecules which are received by DNA strands attached to the objects (beads). More particular, each of the different fluorescent compounds represents one of a specific DNA base, i.e. thymine (T), adenine (A), cytosine (C), and guanine (G). For example, the fluorescent compounds are associated to the DNA bases as follows: T=green; A=yellow; C=blue; and G=red.

[0117] In each cycle 10-50 the first images 11, 21, 31, 41, 51 corresponds to one of the four channels T, A, C, G, e.g. G. The second images 12, 22, 32, 42, 52 then correspond to a second one of the remaining three channels T, A, C, e.g. C. The third images 13, 23, 33, 43, 53 then correspond to a third one of the remaining two channels T, A, e.g. A. The fourth images 14, 24, 34, 44, 54 then correspond to a fourth one of the remaining channel, e.g. T.

[0118] According to an exemplary embodiment of the invention, the subset may be specified in that only first and second intensity values of a given number of cycles, e.g. of cycles 10-30, are selected.

[0119] FIG. 7 illustrates noise-offset effects and their correction according to an exemplary embodiment of the invention. The graph 700 shows the distribution of detected intensities 701 as well as the contributors to the detected intensities (noise: 702, signal: 703). Distributions are visualized as count vs. intensity plots for a plurality of measured objects, wherein the x-axis indicates the intensity and the y-axis the number of objects at a given intensity. The noise-offset correction method identifies the first mode of the noise signal in the input intensity distribution (graph 700) and corrects the detected intensity such that this mode is aligned with a specified value (graph 704). For this visualization the specified value was set to 0. Performing noise-offset correction for each channel individually allows the specification of a common noise-offset for all channels. The first mode of the noise signal may be detected by a data driven approach, by probabilistic modeling of the noise or by another method.

[0120] FIG. 8 illustrates channel-scaling effects and their correction according to an exemplary embodiment of the invention. The graph 800 shows the distribution of detected intensities for two channels (channel 1: 801, channel 2: 802). Distributions are visualized as count vs. intensity plots for a plurality of measured objects, wherein the x-axis indicates the intensity and the y-axis the number of objects at a given intensity. Different channels may have distinct signal intensity distributions as shown in the left graph 800. The channel-scaling correction characterizes the channel-specific intensity distributions and corrects them such that all channel intensity distribution collapse to a common one (right graph 803). The intensity distribution characterization may be performed by a probabilistic model or by another method. If the correction can be performed by a linear transform the channel-scaling correction can be performed via the diagonal components of the cross-talk matrix described herein. A non-linear transform may be corrected by another method.

[0121] The forgoing method steps and the system of the exemplary embodiments have been described as relating to DNA/RNA sequencing. However, as it will be apparent to the person skilled in the art the present invention is not restricted to this technical field. It is clear that the solution of the present invention can be applied to numerous other technical fields, where fluorescent images comprising different types of objects are analyzed. That is, the objects do not have to be beads, but can also be any kind of fluorescent emitting objects.

[0122] As the present invention may be embodied in several forms without departing from the scope or essential characteristics thereof, it should be understood that the above-described embodiments are not limited by any of the details of the foregoing descriptions, unless otherwise specified, but rather should be construed broadly within the scope as defined in the appended claims, and therefore all changes and modifications that fall within the present invention are therefore intended to be embraced by the appended claims.

[0123] Furthermore, in the claims the word “comprising” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude a plurality. A single unit may fulfil the functions of several features recited in the claims. The terms “essentially”, “about”, “approximately” and the like in connection with an attribute or a value particularly also define exactly the attribute or exactly the value, respectively.