Second-generation sequencing correction method and system

Abstract

According to the second-generation sequencing correction method and system, the second-generation sequencing data are subjected to optical correction and then chemical correction, the process is small in complexity and interference and high in robustness, and meanwhile the higher correction effect can be achieved for chemical correction of different platforms. Furthermore, based on the method disclosed by the invention, the lagrunon coefficient can be found out more accurately, so that the influence caused by lagrunon is removed. The error rate is reduced, and the number of available reads is increased.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a second-generation sequencing correction method and system. Background Art

[0002] The second-generation sequencing technology uses high-resolution microscopic imaging to obtain the signal of fluorescent molecules, and obtains the base sequence by decoding the image signal. Sequencing while synthesizing is the core idea of ​​the second-generation sequencing. In the process of sequencing while synthesizing, one base will be synthesized in each cycle. However, due to incomplete removal of the dye, there will be a cycle that synthesizes zero or two or more bases (also known as lag, runon). This situation seriously affects the length of the read, because any DNB may be affected by lagrunon, resulting in the emission of fluorescence in addition to the light emitted by the bases synthesized in this cycle, as well as the light emitted by the bases in the previous cycle or the next cycle. Therefore, the luminescence intensity will become weaker, and multiple channels will emit light. Lagrunon appears as a tilt or bifurcation of the arm on the scatter plot. In order to reduce the situation of arm separation, the data needs to be corrected for lagrunon.

[0003] The existing lagrunon correction method mainly uses Illumina's Bustard tool. This tool independently calculates the lag and runon coefficients based on the first few cycles of sequencing. The calculated coefficients are used as a matrix to correct the fluorescence signal.

[0004] However, the tool has problems with insufficient robustness and anti-interference capabilities for different test platforms. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides a second-generation sequencing correction method and system to solve the problems of poor versatility, insufficient robustness for different test platforms, and insufficient anti-interference ability of existing correction algorithms.

[0006] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0007] A first aspect of an embodiment of the present invention discloses a second-generation sequencing correction method, the method comprising:

[0008] Obtain next-generation sequencing data;

[0009] Processing the second generation sequencing data to obtain brightness values ​​divided according to luminous intensity;

[0010] Selecting a first brightness value group whose luminous intensity meets the lag coefficient correction requirement, and calculating the lag coefficient based on the first brightness value group to obtain a corresponding lag coefficient;

[0011] Selecting a second brightness value group whose luminous intensity meets the runon coefficient correction requirement, and calculating the runon coefficient based on the second brightness data group to obtain a corresponding runon coefficient;

[0012] Perform linear fitting on all obtained lag coefficients and runon coefficients, and use the obtained fitting values ​​as the lagrunon values ​​of all cycles;

[0013] The brightness values ​​of all cycles are corrected based on the lagrunon value to obtain corrected second-generation sequencing data.

[0014] Optionally, the second generation sequencing data is processed to obtain brightness values ​​divided according to luminous intensity, including:

[0015] If four fluorescent reagents are used for sequencing, a density distribution diagram containing the brightness values ​​of each channel of all cycles is obtained based on the second-generation sequencing data;

[0016] Perform an initial classification based on the brightness values ​​to obtain brightness values ​​divided from large to small according to the luminous intensity.

[0017] Optionally, the second generation sequencing data is processed to obtain brightness values ​​divided according to luminous intensity, including:

[0018] If two fluorescent reagents are used for sequencing, a density distribution diagram containing the brightness values ​​of each channel of all cycles is obtained based on the second-generation sequencing data;

[0019] Determine the local maximum brightness value and the local minimum brightness value on the density distribution map to determine the initial clustering parameters;

[0020] The brightness values ​​are divided based on the initial clustering parameters to obtain brightness values ​​divided according to luminous intensity.

[0021] Optionally, the brightness values ​​are divided based on the initial clustering parameters to obtain brightness values ​​divided according to luminous intensity, including:

[0022] Based on the initial clustering parameters, select The brightness value of

[0023] Sort the selected brightness values ​​according to luminous intensity;

[0024] Among them, P (1，1) Refers to the value of the quantile in channel 1 at 1%, P (2，1) It refers to the value of 1% of the quantile on channel 2; R 30 is the initial clustering parameter, which indicates one third of the distance between the 98% value and the 1% brightness value of the channel 1 and 2 quantiles.

[0025] Optionally, the brightness values ​​are divided based on the initial clustering parameters to obtain brightness values ​​divided according to luminous intensity, including:

[0026] The brightness values ​​are divided based on the initial clustering parameters, and the values ​​that meet The brightness value of

[0027] Sort the selected brightness values ​​according to luminous intensity;

[0028] Among them, P (1，1) Refers to the value of the quantile in channel 1 at 1%, P (2，1) It refers to the value of 1% of the quantile on channel 2; R 50 is the initial clustering parameter, which indicates half of the distance between the 98% value and the 1% brightness value of the 1 and 2 quantiles of channels.

[0029] Optionally, selecting a first brightness value group whose luminous intensity meets the lag coefficient correction requirement, and calculating the lag coefficient based on the first brightness value group to obtain a corresponding lag coefficient includes:

[0030] For all cycles, select the brightness values ​​corresponding to the points that emit light in the previous cycle and the points that do not emit light in the current cycle to form a first brightness value group whose luminous intensity meets the lag coefficient correction requirement;

[0031] The lag coefficient is calculated based on the first brightness value group to obtain the corresponding lag coefficient.

[0032] Optionally, selecting a second brightness value group whose luminous intensity meets the runon coefficient correction requirement, and calculating the runon coefficient based on the second brightness data group, includes:

[0033] For all cycles, the brightness values ​​corresponding to the current cycle and the next cycle are selected to form a second brightness value group whose luminous intensity meets the runon coefficient correction requirement;

[0034] A runon coefficient is calculated based on the second brightness value group to obtain a corresponding runon coefficient.

[0035] Optionally, the brightness values ​​of all cycles are corrected based on the lagrunon value to obtain corrected second-generation sequencing data, including:

[0036] For the brightness value of each cycle, the lagging part of the brightness value of the previous cycle and the runon part of the brightness value of the next cycle are removed using the lagrunon value to obtain the corrected second-generation sequencing data.

[0037] Optionally, after obtaining the second generation sequencing data, the method further includes:

[0038] The second-generation sequencing data is normalized to obtain normalized second-generation sequencing data.

[0039] A second aspect of an embodiment of the present invention discloses a second generation sequencing correction system, the system comprising:

[0040] An optical correction module is used to obtain second-generation sequencing data; process the second-generation sequencing data to obtain brightness values ​​divided according to luminous intensity; select a first brightness value group whose luminous intensity meets the lag coefficient correction requirement, and calculate the lag coefficient based on the first brightness value group to obtain a corresponding lag coefficient; select a second brightness value group whose luminous intensity meets the runon coefficient correction requirement, and calculate the runon coefficient based on the second brightness data group to obtain a corresponding runon coefficient; perform linear fitting on all the obtained lag coefficients and runon coefficients, and use the obtained fitting values ​​as the lagrunon values ​​of all cycles;

[0041] The chemical correction module is used to correct the brightness values ​​of all cycles based on the lagrunon value to obtain corrected second-generation sequencing data.

[0042] Based on the above-mentioned embodiment of the present invention, a second-generation sequencing correction method and system are provided. The method obtains second-generation sequencing data; processes the second-generation sequencing data to obtain brightness values ​​divided according to luminous intensity; selects a first brightness value group whose luminous intensity meets the lag coefficient correction requirements, and calculates the lag coefficient based on the first brightness value group to obtain the corresponding lag coefficient; selects a second brightness value group whose luminous intensity meets the runon coefficient correction requirements, and calculates the runon coefficient based on the second brightness data group to obtain the corresponding runon coefficient; linear fitting is performed for all obtained lag coefficients and runon coefficients, and the obtained fitting values ​​are used as the lagrunon values ​​of all cycles; based on the lagrunon value, the brightness values ​​of all cycles are corrected to obtain the corrected second-generation sequencing data. In an embodiment of the present invention, after optical correction of the second-generation sequencing data, chemical correction is performed. The process has low complexity, low interference, and high robustness. At the same time, chemical correction for different platforms can achieve a higher correction effect. Further, based on the method disclosed in the present invention, the lagrunon coefficient can be found more accurately, thereby removing the influence caused by lagrunon. Reduce the error rate and increase the number of available reads. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0044] Figure 1 Schematic diagram of the biochemical principle of lagrunon;

[0045] Figure 2 A flowchart of a second-generation sequencing correction method disclosed in an embodiment of the present invention;

[0046] Figure 3 A flowchart of another second-generation sequencing correction method disclosed in an embodiment of the present invention;

[0047] Figure 4 The brightness value distribution of the four groups of ACGT in the 2-color sequencing disclosed in the embodiment of the present invention;

[0048] Figure 5 A brightness value density map of a single channel disclosed in an embodiment of the present invention;

[0049] Figure 6 It is a schematic diagram of obtaining the front and back brightness values ​​of channel 1 disclosed in an embodiment of the present invention;

[0050] Figure 7 The embodiment of the present invention discloses Figure 5 Schematic diagram after correction;

[0051] Figure 8 A crosstalk diagram of the brightness values ​​of the front and rear cycles without lagrunon correction disclosed in an embodiment of the present invention;

[0052] Fig. 9 This is a schematic diagram of crosstalk after lagrunon correction disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] In this application, the terms "comprises", "comprising" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element.

[0055] As can be seen from the background technology, existing correction tools for second-generation sequencing have problems such as poor versatility, insufficient robustness for different test platforms, and insufficient anti-interference ability.

[0056] Figure 1 Schematic diagram of the biochemical principle of lagrunon, in which the biochemical reaction appears ahead or behind during the sequencing process (A is base lagging, lagging behind the reaction, and B is runon, ahead of the reaction).

[0057] In a base cluster, the leading or lagging base will not only weaken the brightness value of its own cycle fluorescence signal, but also cause some signal interference. The base with a delayed reaction will react in the next cycle and have a signal value in this channel. The lag and advance of this base are related to the biochemical reaction. Under different biochemical conditions, the probability of lagrunon is different, and in probability, once a lagrunon occurs, the possibility of recovery is very small. Therefore, the proportion of lagrunon is accumulated as the cycle increases. In the correction of Lagrunon, the proportion of lagrunon should be calculated based on the data of the current cycle, the previous cycle, and the next cycle. There will be no lag in the first cycle, and there will be no runon in the last cycle. These two values ​​are zero in the first and last cycles.

[0058] Based on this, the embodiment of the present invention discloses a highly robust second-generation sequencing correction method applicable to different test platforms. The main process is to first perform optical correction on the second-generation sequencing data, and then perform chemical correction.

[0059] First, optical correction is performed on all channels, including:

[0060] 1. Perform preliminary classification on the second-generation sequencing data and select the brightness values ​​of points with high classification accuracy.

[0061] 2. Select different cycles to calculate lag or runon. To calculate lag, the previous cycle and the current cycle are used; to calculate runon, the current cycle and the next cycle are used.

[0062] 3. Calculate the ratio of the slope values ​​of all selected points to the brightness values ​​in different cycles and perform linear fitting.

[0063] 4. Calculate the mean of the lagrunon coefficient.

[0064] Then chemical correction is carried out.

[0065] When performing chemical correction, the obtained lagrunon coefficient is calculated to remove the lag of the brightness of the previous cycle and the runon of the brightness of the next cycle for the brightness value of this cycle, and finally complete the second-generation sequencing correction.

[0066] In an embodiment of the present invention, after optical correction is performed on the second-generation sequencing data, chemical correction is performed. This process has low complexity, low interference, and high robustness. At the same time, chemical correction for different platforms can achieve a high correction effect.

[0067] like Figure 2 As shown, a second-generation sequencing correction method disclosed in an embodiment of the present invention mainly includes the following steps:

[0068] S201: Obtain second-generation sequencing data.

[0069] During the execution of S201, the second generation sequencing data of all the cycles of all the channels are obtained.

[0070] Assume that a set of SE100 data in 2-color sequencing mode is being processed (including channel 1, 2, a total of 100 cycle values, and the number of points in each cycle is assumed to be 1 million).

[0071] It should be noted that after obtaining the second-generation sequencing data, the method further includes: normalizing the second-generation sequencing data to obtain the normalized second-generation sequencing data.

[0072] S202: Process the second-generation sequencing data to obtain brightness values ​​divided according to luminous intensity.

[0073] In S202, under four fluorescent reagents, the four groups of ACGT brightness value data (or the two groups of H and L brightness value data) are normalized to one scale, and the number of lagrunon base clusters is greater than 0. The clustering method is based on the luminescence intensity of each base in its corresponding channel. The strongest signal value in the four channels of ACGT can be used to represent the result of the initial classification.

[0074] In one embodiment of the present invention, if four fluorescent reagents are used for sequencing, the second generation sequencing data is processed to obtain brightness values ​​divided according to luminous intensity, specifically including:

[0075] First, a density distribution diagram containing the brightness values ​​of each channel of all cycles is obtained based on the second-generation sequencing data.

[0076] Secondly, an initial classification is performed according to the brightness value, and the brightness values ​​are obtained according to the luminous intensity from large to small.

[0077] In S202, when only two fluorescent reagents are used, also known as 2-color sequencing, the four groups of ACGT brightness value data (or the two groups of H and L brightness value data) are normalized to one scale, and the number of lagrunon base clusters is greater than 0. The clustering method is to judge based on the luminescence intensity of each base in its corresponding channel. The strongest signal value in the four channels of ACGT can be used to represent the result of the initial clustering.

[0078] It should be noted that preliminary clustering is required in the 2-color sequencing mode.

[0079] In one embodiment of the present invention, if two fluorescent reagents are used for sequencing, the second generation sequencing data is processed to obtain brightness values ​​divided according to luminous intensity, specifically including:

[0080] First, a density distribution diagram containing the brightness values ​​of each channel of all cycles is obtained based on the second-generation sequencing data.

[0081] Secondly, the local maximum brightness value and the local minimum brightness value on the density distribution map are determined to determine the initial clustering parameters.

[0082] Finally, the brightness values ​​are divided based on the initial clustering parameters to obtain brightness values ​​divided according to luminous intensity.

[0083] In one embodiment of the present invention, the brightness values ​​are divided based on the initial clustering parameters to obtain brightness values ​​divided according to luminous intensity, including:

[0084] Based on the initial clustering parameters, a brightness value satisfying formula (1) is selected.

[0085]

[0086] Sort by luminous intensity for the selected brightness value.

[0087] Among them, P (1，1) Refers to the value of the quantile in channel 1 at 1%, P (2，1) It refers to the value of 1% of the quantile on channel 2; R 30 is the initial clustering parameter, which indicates one third of the distance between the 98% value and the 1% brightness value of channel 1 and 2 quantiles. As shown in formula (2):

[0088]

[0089] In one embodiment of the present invention, the brightness values ​​are divided based on the initial clustering parameters to obtain brightness values ​​divided according to luminous intensity, including:

[0090] The brightness values ​​are divided based on the initial clustering parameters, and the brightness values ​​that satisfy formula (3) are selected.

[0091]

[0092] Sort the selected brightness values ​​according to luminous intensity;

[0093] Among them, P (1，1) Refers to the value of the quantile in channel 1 at 1%, P (2，1) It refers to the value of 1% of the quantile on channel 2; R 50 is the initial clustering parameter, which indicates half of the distance between the 98% value and the 1% brightness value of the 1 and 2 quantiles of channels.

[0094] S203: Select a first brightness value group whose luminous intensity meets the lag coefficient correction requirement, and calculate the lag coefficient based on the first brightness value group to obtain a corresponding lag coefficient.

[0095] In S203, the data selection is different according to the different calculated coefficients. Taking the calculation of lagging value as an example, taking a single channel as an example, the data selected are the points where the channel is luminous in the previous cycle and the points where the channel is not luminous in the next cycle, and the slope of the brightness value is calculated. The above regression is performed for all cycles except the first and last cycles.

[0096] In one embodiment of the present invention, a first brightness value group whose luminous intensity meets the lag coefficient correction requirement is selected, and the lag coefficient is calculated based on the first brightness value group to obtain the corresponding lag coefficient, specifically including:

[0097] First, for all cycles, the brightness values ​​corresponding to the points that emit light in the previous cycle and the points that do not emit light in the current cycle are selected to form a first brightness value group whose luminous intensity meets the lag coefficient correction requirement;

[0098] Secondly, the lag coefficient is calculated based on the first brightness value group to obtain the corresponding lag coefficient.

[0099] S204: Select a second brightness value group whose luminous intensity meets the runon coefficient correction requirement, and calculate the runon coefficient based on the second brightness data group to obtain a corresponding runon coefficient.

[0100] In S204, the data selection is different according to the calculated coefficients. Taking the calculation of the runon value as an example, taking a single channel as an example, select the point where the channel is luminous in the current cycle and the point where the channel is not luminous in the next cycle, and calculate the slope of the brightness value. Perform the above regression for all cycles except the first and last cycles.

[0101] In one embodiment of the present invention, selecting a second brightness value group whose luminous intensity meets the runon coefficient correction requirement, and calculating the runon coefficient based on the second brightness data group specifically includes:

[0102] First, for all cycles, the brightness values ​​corresponding to the current cycle and the next cycle are selected to form a second brightness value group whose luminous intensity meets the runon coefficient correction requirement;

[0103] Secondly, the runon coefficient is calculated based on the second brightness value group to obtain the corresponding runon coefficient.

[0104] S205: Perform linear fitting on all obtained lag coefficients and runon coefficients, and use the obtained fitting values ​​as the lagrunon values ​​of all cycles.

[0105] S206: Correcting the brightness values ​​of all cycles based on the lagrunon value to obtain corrected second-generation sequencing data.

[0106] In one embodiment of the present invention, the brightness values ​​of all cycles are corrected based on the lagrunon value to obtain corrected second-generation sequencing data, including:

[0107] For the brightness value of each cycle, the lagging part of the brightness value of the previous cycle and the runon part of the brightness value of the next cycle are removed using the lagrunon value to obtain the corrected second-generation sequencing data.

[0108] In the embodiment of the present invention, after optical correction of the second generation sequencing data, chemical correction is performed. The process has low complexity, low interference, and high robustness. At the same time, chemical correction for different platforms can achieve a high correction effect. Furthermore, based on the method disclosed in the present invention, the lagrunon coefficient can be found more accurately, thereby removing the influence caused by lagrunon, reducing the error rate, and increasing the number of available reads.

[0109] Based on the second generation sequencing correction method disclosed in the above embodiment of the present invention, Figure 3 Let’s take an example. Figure 3 As shown in the figure, the four groups of brightness value data of A, C, G, and T (or two groups of H and L, when only two fluorescent reagents are used, also known as 2-color sequencing) are all on the same scale after normalization. The number of lagrunon base clusters is greater than 0. The clustering method is to judge based on the luminescence intensity of each base in its corresponding channel. The strongest signal value in the four channels of ACGT can be used to represent the result of the initial classification (in the 2-color sequencing mode, clustering is required, such as Figure 4 ). After the data is classified, some data is selected for calculating the lagrunon value. Depending on the coefficients of the calculation, the data selection is different. Taking the calculation of the lagging value as an example, taking a single channel as an example, the data selected is the point where the channel emits light in the previous cycle and does not emit light in the next cycle. Calculate the slope of the brightness value (Ints) and perform linear regression of all slope values. The calculation of runon is the same as the calculation of lagging, but the current cycle and the next cycle are selected when selecting points. Perform the above regression for all cycles except the first and last cycles to calculate the lagging and runon values. Perform a linear fit on all cycle lagrunon values, and the resulting slope is the lagrunon value of all cycles.

[0110] Based on the second generation sequencing correction method disclosed in the above embodiment of the present invention, the following example is used to illustrate, assuming that a set of SE100 data in a 2-color sequencing mode is processed (including channel 1, 2, a total of 100 cycle values, and the number of points in each cycle is assumed to be 1 million). After normalization, initial clustering, point selection and correction are performed, specifically as follows:

[0111] 1. Initial clustering:

[0112] Get the brightness value density map of the two channels and find the local maximum and minimum values ​​on the density distribution map (for example Figure 4 and Figure 5 As shown) define the initial clustering parameter R 30, assign initial clustering results to the points that meet the conditions (Formula (1)).

[0113] Figure 4 This is the brightness value distribution of the four groups ACGT in 2-color sequencing.

[0114] G bases are located near the origin. In the initial clustering, the brightness values ​​of each channel are sorted, and only the values ​​in the quantile range from 1% to 98% are used. The brightness values ​​that meet the conditions of formula (1) are marked as G.

[0115]

[0116] Among them, P (1，1) Refers to the value of the quantile in channel 1 at 1%, P (2，1) It refers to the value of 1% of the quantile on channel 2; R 30 is the initial clustering parameter, which indicates one third of the distance between the 98% value and the 1% brightness value of the channel 1 and 2 quantiles.

[0117] Similarly, the clustering of ACT satisfies formula (3).

[0118]

[0119] Among them, P (1，1) Refers to the value of the quantile in channel 1 at 1%, P (2，1) It refers to the value of 1% of the quantile on channel 2; R 50 is the initial clustering parameter, which indicates half of the distance between the 98% value and the 1% brightness value of the 1 and 2 quantiles of channels.

[0120] The further classification of ACT clusters also requires the slope value, which is calculated as shown in formula (4):

[0121] S=(I1-cy) / (I2-cx) (4)

[0122] Where (cx, cy) is the coordinate of the center of the G group. The slope of the brightness value is plotted on the histogram. The two local minimum values ​​are set as S1 and S2, and the relationship is as shown in formula (5):

[0123] 0<S1<S m , S m <S2<∞ (5)

[0124] Among them, S m is the middle value.

[0125] According to S1 and S2, the brightness value is divided into three groups of ACT. That is to say, if the brightness value satisfies:

[0126]

[0127] If S<S1, it is determined to be a T base (luminescence in only one channel).

[0128] If S1<S<S2, it is A base (both A channels emit light).

[0129] If S>S2, it is a C base (emitting light in only one channel).

[0130] Figure 5 Shown is a single channel brightness value density map, which can be seen as Figure 4 The projection of the brightness value in one direction in crosstalk. This is the basis for initial clustering (this method is suitable for 2-color sequencing with two fluorescent markers. For sequencing with four fluorescent reagents, it is only necessary to make initial classification based on the brightness value without clustering). Figure 4 The brightness value distribution has a background value peak and a signal value peak. The background value and the signal value are divided by a solid line. This value is Figure 3 Medium R 30 When doing initial clustering, avoid selecting R 30 The brightness values ​​near the dotted line (signal value or background value peak) are between the background value and the signal value, and should not be included in the initial clustering. The clustering result is accurate if the points close to the dotted line (signal value or background value peak) are selected.

[0131] 2. Select the location:

[0132] The data selection is different according to the different calculated coefficients. The first cycle does not perform lag correction, the last cycle does not perform runon correction, and the remaining cycles need to select the previous and next cycles to calculate lag and runon respectively.

[0133] Specifically, taking the lag of channel 1 as an example, select the point where channel 1 emits light in the previous cycle and the point where channel 1 does not emit light in the current cycle, calculate the slope (current cycle Int / previous cycle Int) value, and perform linear regression of the slope value y=kx+b, where k is the lag coefficient of the current cycle (see Figure 6 and Figure 7 ).

[0134] Similarly, the calculation of runon is to select the brightness value of the point that emits light in channel 1 of the current cycle and the point that does not emit light in the next cycle, and calculate the runon coefficient.

[0135] 3. Correction:

[0136] After the lagrunon coefficients of the current cycle are calculated, the lag is corrected according to formula (6):

[0137] I (1，cur) =I (1，cur) --I (1，pre) *k (6)

[0138] Among them, I (1，cur) is the brightness value of the current cycle, I (1，pre) It is the brightness value of the previous cycle. After multiplying it by the lag coefficient, it is the residual brightness value of the previous cycle in the current cycle, which should be subtracted from the current cycle.

[0139] The same applies to the correction of runon.

[0140] To sum up, lag describes the impact of the previous cycle on the next cycle, and for each cycle we assume that the number of copies that affects the next cycle is a constant, which makes it convenient to fit the lag value using linear regression. Figure 5 This is a schematic diagram of the brightness values ​​before and after channel 1. It can be seen that the tilt of the arm means that the brightness value of channel 1 in the previous cycle is projected to the next cycle at a certain ratio. A linear fit of the slope value is made. The fitting function can be expressed as y=kx+b. The correction function is based on the slope k, minus the brightness value of the previous cycle, as shown in formula (6). The point diagram after correction is as follows Figure 6 The correction of runon is similar to lag, but the cycles looked at are the current cycle and the next cycle.

[0141] Figure 8 It is a crosstalk diagram of the brightness values ​​of the previous and next cycles. There are four cases according to the luminescence situation: neither the previous and next cycles emit light (the group at the origin), the previous cycle emits light, and the next cycle does not emit light (the arm close to the x-axis), the previous cycle does not emit light, and the next cycle emits light (the arm close to the y-axis), and both the previous and next cycles emit light (the arm at a 45-degree angle in the middle). Before correcting lag and runon, the TCG group will have an obvious tilt. Because of the existence of lagrunon, the retained brightness value of the previous cycle will be in the next cycle, so the arm will rise.

[0142] Fig. 9 This is the image after lagrunon correction. The arms of the x-axis and y-axis are close to 0 degrees and 90 degrees, the residual brightness value is removed, and the correction is completed.

[0143] In the embodiment of the present invention, after optical correction of the second generation sequencing data, chemical correction is performed. The process has low complexity, low interference, and high robustness. At the same time, chemical correction for different platforms can achieve a high correction effect. Furthermore, based on the method disclosed in the present invention, the lagrunon coefficient can be found more accurately, thereby removing the influence caused by lagrunon, reducing the error rate, and increasing the number of available reads.

[0144] Based on the second-generation sequencing correction method disclosed in the above embodiment of the present invention, the embodiment of the present invention also discloses a second-generation sequencing correction system, which includes:

[0145] An optical correction module is used to obtain second-generation sequencing data; process the second-generation sequencing data to obtain brightness values ​​divided according to luminous intensity; select a first brightness value group whose luminous intensity meets the lag coefficient correction requirement, and calculate the lag coefficient based on the first brightness value group to obtain a corresponding lag coefficient; select a second brightness value group whose luminous intensity meets the runon coefficient correction requirement, and calculate the runon coefficient based on the second brightness data group to obtain a corresponding runon coefficient; perform linear fitting on all the obtained lag coefficients and runon coefficients, and use the obtained fitting values ​​as the lagrunon values ​​of all cycles;

[0146] The chemical correction module is used to correct the brightness values ​​of all cycles based on the lagrunon value to obtain corrected second-generation sequencing data.

[0147] It should be noted that the optical correction module can execute the above-mentioned specific technical solution for optical correction, and the chemical correction module can execute the above-mentioned specific technical solution for chemical correction.

[0148] In the embodiment of the present invention, after optical correction of the second generation sequencing data, chemical correction is performed. The process has low complexity, low interference, and high robustness. At the same time, chemical correction for different platforms can achieve a high correction effect. Furthermore, based on the method disclosed in the present invention, the lagrunon coefficient can be found more accurately, thereby removing the influence caused by lagrunon, reducing the error rate, and increasing the number of available reads.

[0149] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.

[0150] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0151] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A second generation sequencing correction method, characterized in that: The method comprises: Obtain next-generation sequencing data; Processing the second generation sequencing data to obtain brightness values ​​divided according to luminous intensity; Selecting a first brightness value group whose luminous intensity meets the lag coefficient correction requirement, and calculating the lag coefficient based on the first brightness value group to obtain a corresponding lag coefficient; Selecting a second brightness value group whose luminous intensity meets the runon coefficient correction requirement, and calculating the runon coefficient based on the second brightness data group to obtain a corresponding runon coefficient; Perform linear fitting on all obtained lag coefficients and runon coefficients, and use the obtained fitting values ​​as the lagrunon values ​​of all cycles; The brightness values ​​of all cycles are corrected based on the lagrunon value to obtain corrected second-generation sequencing data.

2. The method according to claim 1, characterized in that: The second generation sequencing data is processed to obtain brightness values ​​divided according to luminous intensity, including: If four fluorescent reagents are used for sequencing, a density distribution diagram containing the brightness values ​​of each channel of all cycles is obtained based on the second-generation sequencing data; Perform an initial classification based on the brightness values ​​to obtain brightness values ​​divided from large to small according to the luminous intensity.

3. The method according to claim 1, characterized in that The second generation sequencing data is processed to obtain brightness values ​​divided according to luminous intensity, including: If two fluorescent reagents are used for sequencing, a density distribution diagram containing the brightness values ​​of each channel of all cycles is obtained based on the second-generation sequencing data; Determine the local maximum brightness value and the local minimum brightness value on the density distribution map to determine the initial clustering parameters; The brightness values ​​are divided based on the initial clustering parameters to obtain brightness values ​​divided according to luminous intensity.

4. The method according to claim 3, characterized in that The brightness values ​​are divided based on the initial clustering parameters to obtain brightness values ​​divided according to luminous intensity, including: Based on the initial clustering parameters, select The brightness value of Sort the selected brightness values ​​according to luminous intensity; Among them, P (1,1) Refers to the value of the quantile in channel 1 at 1%, P (2,1) It refers to the value of 1% of the quantile on channel 2; R 30 is the initial clustering parameter, which indicates one third of the distance between the 98% value and the 1% brightness value of the channel 1 and 2 quantiles.

5. The method according to claim 3, characterized in that: The brightness values ​​are divided based on the initial clustering parameters to obtain brightness values ​​divided according to luminous intensity, including: The brightness values ​​are divided based on the initial clustering parameters, and the values ​​that meet The brightness value of Sort the selected brightness values ​​according to luminous intensity; Among them, P (1,1) Refers to the value of the quantile in channel 1 at 1%, P (2,1) It refers to the value of 1% of the quantile on channel 2; R 50 is the initial clustering parameter, which indicates half of the distance between the 98% value and the 1% brightness value of the 1 and 2 quantiles of channels.

6. The method according to claim 1, characterized in that Selecting a first brightness value group whose luminous intensity meets the lag coefficient correction requirement, and calculating the lag coefficient based on the first brightness value group to obtain a corresponding lag coefficient, including: For all cycles, select the brightness values ​​corresponding to the points that emit light in the previous cycle and the points that do not emit light in the current cycle to form a first brightness value group whose luminous intensity meets the lag coefficient correction requirement; The lag coefficient is calculated based on the first brightness value group to obtain the corresponding lag coefficient.

7. The method according to claim 1, characterized in that: Selecting a second brightness value group whose luminous intensity meets the runon coefficient correction requirement, and calculating the runon coefficient based on the second brightness data group, including: For all cycles, the brightness values ​​corresponding to the current cycle and the next cycle are selected to form a second brightness value group whose luminous intensity meets the runon coefficient correction requirement; A runon coefficient is calculated based on the second brightness value group to obtain a corresponding runon coefficient.

8. The method according to any one of claims 1 to 7, characterized in that Based on the lagrunon value, the brightness values ​​of all cycles are corrected to obtain corrected second-generation sequencing data, including: For the brightness value of each cycle, the lagging part of the brightness value of the previous cycle and the runon part of the brightness value of the next cycle are removed using the lagrunon value to obtain the corrected second-generation sequencing data.

9. The method according to any one of claims 1 to 7, characterized in that After obtaining the second generation sequencing data, the method further includes: The second-generation sequencing data is normalized to obtain normalized second-generation sequencing data.

10. A second generation sequencing correction system, characterized in that: The system comprises: An optical correction module is used to obtain second-generation sequencing data; process the second-generation sequencing data to obtain brightness values ​​divided according to luminous intensity; select a first brightness value group whose luminous intensity meets the lag coefficient correction requirement, and calculate the lag coefficient based on the first brightness value group to obtain a corresponding lag coefficient; select a second brightness value group whose luminous intensity meets the runon coefficient correction requirement, and calculate the runon coefficient based on the second brightness data group to obtain a corresponding runon coefficient; perform linear fitting on all the obtained lag coefficients and runon coefficients, and use the obtained fitting values ​​as the lagrunon values ​​of all cycles; The chemical correction module is used to correct the brightness values ​​of all cycles based on the lagrunon value to obtain corrected second-generation sequencing data.

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