A dual-channel digital PCR droplet data screening method and device

Abstract

The present invention discloses a dual-channel digital PCR droplet data screening method and device. Among them, the method includes: respectively calculating the first fluorescence background noise average value of the droplet fluorescence raw data of the two channel liquids in the background noise stage, determining the appearance time of normal droplets according to the first fluorescence background noise average value and judging the droplet stable detection stage through the extracted droplet rate; calculating the fixed extraction threshold of ordinary droplets and the dynamic extraction threshold of fluorescent droplets, and extracting the target droplets from the droplet fluorescence raw data according to the fixed extraction threshold and the dynamic extraction threshold. By calculating the fixed extraction threshold of ordinary droplets and the dynamic extraction threshold of fluorescent droplets, the present invention ensures the consistency of channel PCR droplet data extraction, reduces the consistency requirements of the photoelectric conversion module, reduces the requirements for the consistency of the fluorescence intensity of biological agents, and reduces the impact on the sample amplification cycle efficiency.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of digital PCR droplet data processing, and in particular to a dual-channel digital PCR droplet data screening method and device. Background Art

[0002] The final result of dual-channel digital PCR is the data of each droplet that has passed through digital PCR. The droplet data includes the fluorescence intensity of the droplet in channel 1, the width of the droplet in channel 1, the fluorescence intensity of the droplet in channel 2, and the width of the droplet in channel 2. The properties of the droplet can be analyzed through the fluorescence intensity of the droplets in channels 1 and 2. It is relatively easy to read the fluorescence intensity, and the more common method is to read the extreme value of the droplet fluorescence intensity.

[0003] The width of the droplet in the channel is affected by factors such as background noise, fluorescence intensity, acquisition card rate, and consistency of the photoelectric conversion device during the reading process. Usually, when reading the droplet width of the same droplet in different channels, the droplet widths of the two channels are very different. The more common flow cytometer analysis software on the market uses droplet width as a screening method for whether the droplet data is valid. This places higher requirements on the consistency of the width calculated for the same droplet in different channels of dual fluorescent channels and the width calculated for different droplets in the same channel. However, there is no effective method in the prior art to ensure the width of droplet extraction, so this patent comes from this. Summary of the invention

[0004] The present invention provides a dual-channel digital PCR droplet data screening method to achieve consistency in droplet extraction width, ensure the effectiveness of extracted droplets, and thus more effectively discriminate digital PCR droplet properties.

[0005] First, an embodiment of the present invention provides a dual-channel digital PCR droplet data screening method, comprising:

[0006] S1, respectively calculating the first fluorescence background noise average of the droplet fluorescence raw data of the two channels in the background noise stage, determining the appearance time of the droplet according to the first fluorescence background noise average, and judging the droplet stable detection stage according to the droplet appearance frequency;

[0007] S2, calculating the average value of the fluorescence extreme value of common droplets and the fixed extraction threshold of common droplets according to the droplet data in the droplet stabilization detection stage;

[0008] S3, judging whether the current droplet to be detected is a common droplet according to the average value of the common droplet fluorescence extreme value, and if so, determining the extraction width of the current droplet to be extracted according to the fixed extraction threshold of the common droplet;

[0009] If not, the dynamic extraction threshold of the current droplet to be extracted is calculated, and the extraction width of the current droplet to be extracted is determined according to the dynamic extraction threshold.

[0010] Optionally, the S1 specifically includes:

[0011] According to the droplet fluorescence raw data of the two channels at the droplet fluorescence data background noise stage, the first fluorescence background noise average values ​​of the two channels are calculated respectively;

[0012] According to the first fluorescence background noise average value, the background noise thresholds of the two channels are respectively set;

[0013] The pulse images of the droplet fluorescence raw data in the two channels collected by the bioanalysis equipment are analyzed by the two-segment slope method. When the pulse peaks in the pulse images of the two channels are both greater than the corresponding background noise thresholds, and the pulses both show frequency changes, it is determined that the droplet fluorescence raw data has entered the droplet appearance stage.

[0014] When the pulse frequencies in the pulse images of the two channels are stable, it is determined that the droplet fluorescence raw data enters the droplet stability detection stage.

[0015] Optionally, S2 includes:

[0016] Screening out the droplet fluorescence raw data whose fluorescence background noise value is greater than the corresponding background noise threshold in the background noise stage of the two channels, and calculating the average value of the second fluorescence background noise of the two channels based on the screened data;

[0017] Calculate the average value of the fluorescence extreme value of the first common droplet of 20,000 consecutive droplets in the droplet stabilization stage, screen out the fluorescent droplets in the current 20,000 data according to the average value threshold of the fluorescence extreme value of the first common droplet, and calculate the average value of the fluorescence extreme value of the common droplets based on the screened droplets;

[0018] The fixed extraction threshold of the common droplets is calculated according to the second fluorescence background noise average value and the fluorescence extreme value average value of the common droplets.

[0019] Optionally, judging whether the current droplet to be detected is a common droplet according to the average value of the common droplet fluorescence extreme value includes:

[0020] If the difference between the fluorescence extreme value of the droplet to be extracted and the average fluorescence extreme value of the common droplet exceeds a certain threshold, the droplet to be extracted is judged to be a fluorescent droplet, otherwise the droplet to be extracted is a common droplet.

[0021] Optionally, calculating a dynamic extraction threshold of the current droplet to be extracted includes:

[0022] The dynamic extraction threshold of the fluorescent droplets is determined according to the fluorescence extreme value of the fluorescent droplets in the dual channels, the average value of the second fluorescence background noise, and the average value of the fluorescence extreme value of the common droplets.

[0023] In a second aspect, an embodiment of the present invention further provides a dual-channel digital PCR droplet data screening device, comprising:

[0024] A normal droplet appearance stage judgment module is used to respectively calculate the first fluorescence background noise average of the droplet fluorescence raw data of the two channels in the background noise stage, determine the droplet appearance time according to the first fluorescence background noise average, and judge the droplet stable detection stage according to the droplet appearance frequency;

[0025] A fixed extraction threshold calculation module for common droplets, used to calculate the average value of common droplet fluorescence extreme values ​​and the fixed extraction threshold of common droplets based on the droplet data in the droplet stabilization detection stage;

[0026] A droplet extraction module, used to determine whether the droplet to be detected is a common droplet according to the average value of the common droplet fluorescence extreme value, and if so, determine the extraction width of the droplet to be extracted according to the fixed extraction threshold of the common droplet;

[0027] If not, the dynamic extraction threshold of the current droplet to be extracted is calculated, and the extraction width of the current droplet to be extracted is determined according to the dynamic extraction threshold.

[0028] Beneficial effects of the present invention:

[0029] The present invention ensures the consistency of channel PCR droplet data extraction by calculating the fixed extraction threshold of ordinary droplets and the dynamic extraction threshold of fluorescent droplets, thereby reducing the consistency requirements of the photoelectric conversion module, reducing the requirements for the consistency of the fluorescence intensity of biological preparations, and reducing the impact on the sample amplification cycle efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a data acquisition waveform diagram in the droplet-free stage in an embodiment of the present invention;

[0031] Figure 2 This is a data acquisition waveform diagram of a normal droplet stage in an embodiment of the present invention;

[0032] Figure 3 This is a flow chart of dual-channel digital PCR droplet data screening in an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0034] The equipment used in the embodiments of the present invention includes: a fully automatic sample processing system; a biochip analyzer; and an amplification instrument.

[0035] Among them, the fully automatic sample processing system is used to generate a consistent and uniform number of droplets, including ordinary droplets and fluorescent droplets.

[0036] Among them, ordinary droplets are droplets without DNA during the digital PCR droplet sample detection process.

[0037] Fluorescent droplets are droplets with a large difference in fluorescence extreme value from ordinary droplets during digital PCR sample detection.

[0038] Among them, the fluorescent droplets are divided into two categories: droplets with wild-type DNA (WT droplets) and droplets with mutant DNA (MT droplets).

[0039] When the droplets pass through the amplification device, the DNA in the WT / MT droplets will grow exponentially (amplification cycle number). When the DNA is in the exponential growth process, each DNA will bind to a specific fluorescent probe.

[0040] During the biochip analyzer test, when ordinary droplets are irradiated by a laser beam of a specific wavelength, basic probe fluorescence will appear. When WT / MT droplets are irradiated by a laser beam of a specific wavelength, a fluorescence wavelength unique to WT / MT droplets will be generated.

[0041] The biochip analyzer, correspondingly, needs to detect two different wavelengths of fluorescence to obtain the intensity of the WT / MT droplet-specific fluorescence. The fluorescence intensity of WT / MT will change with the change of the amplification efficiency during the amplification process. The fluorescence intensity is converted into a digital signal through two channel photoelectric conversion modules and synchronous data acquisition to complete the acquisition of raw fluorescence data.

[0042] Furthermore, according to the entire test process of the biochip analyzer, the collection of fluorescence raw data can be divided into the following stages:

[0043] The first stage: background noise stage (lasts about 6 minutes): The background noise stage is the time when the droplet does not flow into the detection position at the beginning of the detection. Figure 1 is the data acquisition waveform. The horizontal axis represents the acquisition time corresponding to the droplet, and the vertical axis represents the fluorescence intensity of the droplet.

[0044] The second stage: the droplet starting stage.

[0045] The third stage: droplet stability detection stage, Figure 2 The waveform is for data acquisition.

[0046] The fourth stage: droplet reduction stage.

[0047] Dual-channel fluorescence parameter description:

[0048] CH1: fluorescence intensity specific to WT droplets.

[0049] CH2: Specific fluorescence intensity for MT droplets.

[0050] Among them, the droplet width is the time it takes for the droplet to flow through the observation position (an important parameter for screening effective droplets), and the droplet fluorescence intensity is the fluorescence peak value when the droplet flows through the observation position (an important parameter for judging the droplet properties).

[0051] Example

[0052] Figure 3 A flowchart of dual-channel digital PCR droplet data screening provided by an embodiment of the present invention specifically includes the following steps:

[0053] S1. Calculate the first fluorescence background noise average of the droplet fluorescence raw data of the two channels in the background noise stage respectively, determine the appearance time of the droplet according to the first fluorescence background noise average, and judge the droplet stable detection stage according to the droplet appearance frequency.

[0054] Wherein, the S1 specifically includes:

[0055] According to the droplet fluorescence raw data of the two channels at the droplet fluorescence data background noise stage, the first fluorescence background noise average values ​​of the two channels are calculated respectively;

[0056] According to the first fluorescence background noise average value, the background noise thresholds of the two channels are respectively set;

[0057] The pulse images of the droplet fluorescence raw data in the two channels collected by the bioanalysis equipment are analyzed by the two-segment slope method. When the pulse peaks in the pulse images of the two channels are both greater than the corresponding background noise thresholds, and the pulses both show frequency changes, it is determined that the droplet fluorescence raw data has entered the droplet appearance stage.

[0058] When the pulse frequencies in the pulse images of the two channels are stable, it is determined that the droplet fluorescence raw data enters the droplet stability detection stage.

[0059] For example, the first fluorescence background noise average values ​​of the two channel data can be calculated from the droplet fluorescence raw data 2 minutes before the droplet start stage, which are CH1_N_AVG1 and CH2_N_AVG1 respectively.

[0060] Add a certain value to CH1_N_AVG1 and CH2_N_AVG1 respectively as the noise floor thresholds of the two channels.

[0061] The pulse images of the droplet fluorescence raw data in the two channels collected by the bioanalysis equipment are analyzed by the two-segment slope method. When the pulse peaks in the pulse images of the two channels are greater than the corresponding background noise threshold and the pulses show frequency changes, it is judged that the droplet fluorescence raw data has entered the droplet appearance stage, and each pulse represents a droplet; when the pulse frequency is stable, it is confirmed that the droplet fluorescence raw data has entered the droplet stability detection stage.

[0062] S2. Calculate the average value of the fluorescence extreme value of common droplets and the fixed extraction threshold of common droplets based on the droplet data in the droplet stabilization detection stage.

[0063] Calculating the average value of the fluorescence extreme value of the common droplet and the fixed extraction threshold of the common droplet specifically includes the following steps:

[0064] Step 1. Calculate the second fluorescence background noise average of the two channel data through 50%-80% of the droplet fluorescence data in the background noise stage. During the calculation process, screen out the relevant data with fluorescence background noise values ​​greater than 20% of the fluorescence background noise average (at the beginning of droplet collection, the acquisition card needs to be stabilized for a period of time), and calculate CH1_AVG and CH2_AVG based on the screened data.

[0065] Step 2: By analyzing the normal droplet data within a certain period of time, such as 2 minutes, in the normal droplet stage, read the fluorescence extreme value, and screen out the droplet fluorescence data with a fluctuation greater than 20% of the fluorescence extreme value average value and the droplet fluorescence data with a droplet frequency lower than the standard frequency (currently designed to be 3500 per second). The above steps are to screen out the fluorescence extreme values ​​and invalid droplet extreme values ​​of dual-channel WT / MT fluorescent droplets. As long as one channel needs to screen out the droplet extreme value data, the other channel must also screen out the data at the same time. The fluorescence extreme value average values ​​of the dual-channel ordinary droplets are calculated based on the screened droplets, which are: CH1_PT1_AVG1 and CH2_PT1_AVG1 respectively.

[0066] Specifically,

[0067]

[0068]

[0069] Note: The zero voltage value is the acquisition value of the acquisition card at 0 potential.

[0070] In this embodiment, the actual test data of ordinary droplets are relatively uniform, so a fixed threshold value can be used for calculation to reduce the amount of software calculation.

[0071] S3, judging whether the current droplet to be detected is a common droplet according to the average value of the common droplet fluorescence extreme value, and if so, determining the extraction width of the current droplet to be extracted according to the fixed extraction threshold of the common droplet;

[0072] If not, the dynamic extraction threshold of the current droplet to be extracted is calculated, and the extraction width of the current droplet to be extracted is determined according to the dynamic extraction threshold.

[0073] Specifically, if the difference between the fluorescence extreme value of the droplet to be extracted and the average fluorescence extreme value of the common droplet exceeds a certain threshold, the droplet to be extracted is judged to be a fluorescent droplet, otherwise the droplet to be extracted is a common droplet.

[0074] Exemplarily, when the fluorescence extreme value of the droplet to be extracted exceeds 10% of the average fluorescence extreme value of ordinary droplets, it means that the droplet to be extracted is a droplet containing DAN, and the dynamic extraction threshold of the droplet needs to be calculated.

[0075] The WT / MT dynamic threshold calculation method is as follows:

[0076]

[0077]

[0078] Note: The zero voltage value is the acquisition value of the acquisition card at 0 potential.

[0079] illustrate:

[0080] CH1_WT / MT_F is the fluorescence extreme value of the droplet containing WT / MT in CH1. The fluorescence extreme value of the droplet containing WT / MT is greater than the fluorescence value of ordinary droplets.

[0081] CH2_WT / MT_F is the fluorescence extreme value of the droplet containing WT / MT in CH2. The fluorescence extreme value of the droplet containing WT / MT is greater than the fluorescence value of ordinary droplets.

[0082] The embodiment of the present invention further provides a dual-channel digital PCR droplet data screening device, comprising:

[0083] A normal droplet appearance stage judgment module is used to respectively calculate the first fluorescence background noise average of the droplet fluorescence raw data of the two channels in the background noise stage, determine the droplet appearance time according to the first fluorescence background noise average, and judge the droplet stable detection stage according to the droplet appearance frequency;

[0084] A fixed extraction threshold calculation module for common droplets, used to calculate the average value of common droplet fluorescence extreme values ​​and the fixed extraction threshold of common droplets based on the droplet data in the droplet stabilization detection stage;

[0085] A droplet extraction module, used to determine whether the droplet to be detected is a common droplet according to the average value of the common droplet fluorescence extreme value, and if so, determine the extraction width of the droplet to be extracted according to the fixed extraction threshold of the common droplet;

[0086] If not, the dynamic extraction threshold of the current droplet to be extracted is calculated, and the extraction width of the current droplet to be extracted is determined according to the dynamic extraction threshold.

[0087] Among them, the normal droplet appearance stage judgment module is specifically used for:

[0088] According to the droplet fluorescence raw data of the two channels at the droplet fluorescence data background noise stage, the first fluorescence background noise average values ​​of the two channels are calculated respectively;

[0089] According to the first fluorescence background noise average value, the background noise thresholds of the two channels are respectively set;

[0090] The pulse images of the droplet fluorescence raw data in the two channels collected by the bioanalysis equipment are analyzed by the two-segment slope method. When the pulse peaks in the pulse images of the two channels are both greater than the corresponding background noise thresholds, and the pulses both show frequency changes, it is determined that the droplet fluorescence raw data has entered the droplet appearance stage.

[0091] When the pulse frequencies in the pulse images of the two channels are stable, it is determined that the droplet fluorescence raw data enters the droplet stability detection stage.

[0092] The fixed extraction threshold calculation module of ordinary droplets is specifically used to: screen out the droplet fluorescence raw data whose fluorescence background noise value is greater than the corresponding background noise threshold in the background noise stage of two channels, and calculate the second fluorescence background noise average value of the two channels according to the screened data;

[0093] Calculate the average value of the fluorescence extreme value of the first common droplet of 20,000 consecutive droplets in the droplet stabilization stage, screen out the fluorescent droplets in the current 20,000 data according to the average value threshold of the fluorescence extreme value of the first common droplet, and calculate the average value of the fluorescence extreme value of the common droplets based on the screened droplets;

[0094] The fixed extraction threshold of the common droplets is calculated according to the second fluorescence background noise average value and the fluorescence extreme value average value of the common droplets.

[0095] Wherein, judging whether the current droplet to be detected is a common droplet according to the average value of the common droplet fluorescence extreme value includes:

[0096] If the difference between the fluorescence extreme value of the droplet to be extracted and the average fluorescence extreme value of the common droplet exceeds a certain threshold, the droplet to be extracted is judged to be a fluorescent droplet, otherwise the droplet to be extracted is a common droplet.

[0097] Calculate the dynamic extraction threshold of the current droplet to be extracted, including:

[0098] The dynamic extraction threshold of the fluorescent droplets is determined according to the fluorescence extreme value of the fluorescent droplets in the dual channels, the average value of the second fluorescence background noise, and the average value of the fluorescence extreme value of the common droplets.

[0099] A dual-channel digital PCR droplet data screening device provided in an embodiment of the present invention can execute a dual-channel digital PCR droplet data screening method provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0100] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A dual-channel digital PCR droplet data screening method, characterized in that: include: S1, respectively calculating the first fluorescence background noise average of the droplet fluorescence raw data of the two channels in the background noise stage, determining the appearance time of the droplet according to the first fluorescence background noise average, and judging the droplet stable detection stage according to the droplet appearance frequency; S2, calculating the average value of the fluorescence extreme value of common droplets and the fixed extraction threshold of common droplets according to the droplet data in the droplet stabilization detection stage; Among them, CH1_AVG and CH2_AVG are the average values ​​of the second fluorescence background noise of the two channels CH1 and CH2 respectively; CH1_PT1_AVG1 and CH2_PT1_AVG1 are the average values ​​of the common droplet fluorescence extremes of the two channels CH1 and CH2, respectively; S3, judging whether the current droplet to be detected is a common droplet according to the average value of the common droplet fluorescence extreme value, and if so, determining the extraction width of the current droplet to be extracted according to the fixed extraction threshold of the common droplet; If not, then calculating the dynamic extraction threshold of the current droplet to be extracted, and determining the extraction width of the current droplet to be extracted according to the dynamic extraction threshold; CH1_WT / MT_F is the fluorescence extreme value of the droplet containing WT / MT in CH1, and CH2_WT / MT_F is the fluorescence extreme value of the droplet containing WT / MT in CH2.

2. The method according to claim 1, characterized in that The S1 specifically includes: According to the droplet fluorescence raw data of the two channels at the droplet fluorescence data background noise stage, the first fluorescence background noise average values ​​of the two channels are calculated respectively; According to the first fluorescence background noise average value, the background noise thresholds of the two channels are respectively set; The pulse images of the droplet fluorescence raw data in the two channels collected by the bioanalysis equipment are analyzed by the two-segment slope method. When the pulse peaks in the pulse images of the two channels are both greater than the corresponding background noise thresholds, and the pulses both show frequency changes, it is determined that the droplet fluorescence raw data has entered the droplet appearance stage. When the pulse frequencies in the pulse images of the two channels are stable, it is determined that the droplet fluorescence raw data enters the droplet stability detection stage.

3. The method according to claim 2, characterized in that The S2 includes: Screening out the droplet fluorescence raw data whose fluorescence background noise values ​​are greater than the corresponding background noise threshold in the background noise stage of the two channels, and calculating the average value of the second fluorescence background noise of the two channels based on the screened data; Calculate the average value of the fluorescence extreme value of the first common droplet of 20,000 consecutive droplets in the droplet stabilization stage, screen out the fluorescent droplets in the current 20,000 data according to the average value threshold of the fluorescence extreme value of the first common droplet, and calculate the average value of the fluorescence extreme value of the common droplets based on the screened droplets; The fixed extraction threshold of the common droplets is calculated according to the second fluorescence background noise average value and the fluorescence extreme value average value of the common droplets.

4. The method according to claim 3, characterized in that: Judging whether the current droplet to be detected is a common droplet according to the average value of the common droplet fluorescence extreme value includes: If the difference between the fluorescence extreme value of the droplet to be extracted and the average fluorescence extreme value of the common droplet exceeds a certain threshold, the droplet to be extracted is judged to be a fluorescent droplet, otherwise the droplet to be extracted is a common droplet.

5. The method according to claim 4, characterized in that Calculate the dynamic extraction threshold of the current droplet to be extracted, including: The dynamic extraction threshold of the fluorescent droplets is determined according to the fluorescence extreme value of the fluorescent droplets in the dual channels, the average value of the second fluorescence background noise, and the average value of the fluorescence extreme value of the common droplets.

6. A dual-channel digital PCR droplet data screening device, characterized in that: include: A normal droplet appearance stage judgment module is used to calculate the first fluorescence background noise average of the droplet fluorescence raw data of the two channels in the background noise stage, determine the droplet appearance time according to the first fluorescence background noise average, and judge the droplet stable detection stage according to the droplet appearance frequency; A fixed extraction threshold calculation module for common droplets, used to calculate the average value of common droplet fluorescence extreme values ​​and the fixed extraction threshold of common droplets based on the droplet data in the droplet stabilization detection stage; Among them, CH1_AVG and CH2_AVG are the average values ​​of the second fluorescence background noise of the two channels CH1 and CH2 respectively; CH1_PT1_AVG1 and CH2_PT1_AVG1 are the average values ​​of the common droplet fluorescence extremes of the two channels CH1 and CH2, respectively; A droplet extraction module, used to determine whether the droplet to be detected is a common droplet according to the average value of the common droplet fluorescence extreme value, and if so, determine the extraction width of the droplet to be extracted according to the fixed extraction threshold of the common droplet; CH1_WT / MT_F is the fluorescence extreme value of the droplet containing WT / MT in CH1, and CH2_WT / MT_F is the fluorescence extreme value of the droplet containing WT / MT in CH2 If not, the dynamic extraction threshold of the current droplet to be extracted is calculated, and the extraction width of the current droplet to be extracted is determined according to the dynamic extraction threshold.

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