A method for evaluating the quality of genome assembly without reference based on sequencing depth distribution characteristics

Abstract

The application discloses a method for evaluating the quality of reference-free genome assembly based on sequencing depth distribution characteristics, which comprises the following steps: S1, sequence re-alignment and dynamic binning; S2, depth anomaly detection based on a Gaussian distribution theory model; S3, structure consistency screening based on alignment mode analysis; and S4, comprehensive evaluation and quality value derivation.

Description

Technical Field

[0001] This invention belongs to the fields of bioinformatics and genomics, specifically relating to a reference-free genome assembly quality assessment method based on sequencing depth distribution characteristics. This method does not rely on an external reference genome and uses its own sequencing data to back-compare features for refined evaluation of genome assembly quality and calculation of quality values. Background Technology

[0002] With the rapid development of high-throughput sequencing technologies, especially the widespread application of high-precision sequencing platforms such as PacBio HiFi and Illumina, the quality of genome assembly has been significantly improved. However, even with high-precision long-read sequencing technologies, various errors inevitably occur during genome assembly, including sequence collapse, duplication, misassembly, local deletion, and complex structural anomalies. These errors directly affect the accuracy of gene structure annotation, variant detection, and subsequent functional genomics analysis. Therefore, establishing an accurate, reliable, and reference-genome-free method for assessing assembly quality is of great significance for new genome construction and genomics research.

[0003] Currently, genome assembly quality assessment methods are mainly divided into two categories: reference genome-based assessment methods and reference genome-free assessment methods. Reference genome-based methods typically analyze structural consistency through sequence alignment, such as using a reference genome to identify structural variations and assembly errors. However, these methods heavily rely on high-quality reference genomes, making them difficult to apply to genomes of novel species or those with high structural variation, and may underestimate true structural differences due to reference bias.

[0004] Evaluation methods for genomes without a reference mainly include k-mer consistency-based evaluations (such as Merqury), single-copy conserved gene integrity-based evaluations (such as BUSCO), and sequencing read alignment statistics-based evaluations. While these methods can reflect assembly integrity and base accuracy to some extent, they still have significant limitations. For example, the k-mer method mainly reflects overall consistency and struggles to pinpoint local assembly errors; BUSCO is based on a limited number of conserved genes and cannot comprehensively assess the quality of the whole genome structure; and existing alignment depth-based evaluation methods often employ fixed windows or simple threshold strategies, lacking rigorous statistical model support, making it difficult to accurately distinguish between normal depth fluctuations and true assembly anomalies, and their limited spatial resolution makes it difficult to identify minute local structural anomalies.

[0005] Theoretically, under ideal assembly conditions, after sequencing data is aligned back to the correctly assembled sequence, its sequencing depth should follow a statistical distribution centered on the average sequencing depth, typically approximating a continuous Gaussian or Poisson distribution. When the assembled sequence collapses, multiple copies are incorrectly merged, leading to a significant increase in alignment depth in that region; conversely, redundant splicing or local deletions result in decreased depth. Furthermore, misaligned splicing regions are often accompanied by anomalous alignment patterns, such as split alignments or inconsistent alignments. Therefore, the characteristics of sequencing depth distribution and alignment patterns provide an important statistical basis and theoretical foundation for identifying assembly errors under reference-less conditions.

[0006] However, current technologies lack a reference-free assembly quality assessment method that can simultaneously combine high spatial resolution sequencing depth statistical models with alignment structural pattern analysis. In particular, there is a lack of a comprehensive assessment method that can establish a genome-wide deep anomaly detection model based on rigorous statistical distribution theory, combine alignment structural consistency analysis to systematically identify assembly errors, and further quantify the assembly error rate and derive a standardized quality value (QV).

[0007] Therefore, there is an urgent need to develop a reference-free genome assembly quality assessment method based on the joint analysis of sequencing depth distribution characteristics and alignment structural patterns, so as to achieve high-sensitivity detection of assembly errors, high spatial resolution localization, and quantitative assessment of overall quality, thereby providing reliable technical support for genome assembly optimization and genome quality control. Summary of the Invention

[0008] This invention provides a reference-free genome assembly quality assessment method based on sequencing depth distribution characteristics to solve the technical problems existing in the prior art.

[0009] To achieve the above objectives, this invention provides a reference-free genome assembly quality assessment method based on sequencing depth distribution characteristics, comprising:

[0010] S1: Sequence overlap alignment and dynamic binning;

[0011] S2: Deep anomaly detection based on Gaussian distribution theory model;

[0012] S3: Structural consistency screening based on comparative pattern analysis;

[0013] S4: Comprehensive evaluation and quality value derivation.

[0014] In one embodiment of the present invention, step S1 may optionally include:

[0015] S11: Align the raw PacBio HiFi or Illumina paired-end sequencing data back to the assembled sequence to be evaluated;

[0016] S12: Divide the genome into a large number of continuous and non-overlapping windows: The window length is set to 50 bp to obtain high spatial resolution while ensuring statistical stability and to capture local anomalous signals.

[0017] In one embodiment of the present invention, step S2 may optionally include:

[0018] S21: Calculate the average alignment depth of each window using the mosdepth software;

[0019] S22: Construct a theoretical Gaussian distribution model at the whole genome level, and use the 3 sigma criterion to perform statistical tests on the window depth values;

[0020] S23: Identify windows that significantly deviate from the two ends of the theoretical distribution as "deep anomaly windows," which correspond to the identification of assembly problems such as sequence collapse, redundant splicing, or local missing parts.

[0021] In one embodiment of the present invention, step S3 may optionally include:

[0022] S31: After excluding windows with abnormal depth, perform a comparative pattern depth analysis on the remaining windows with normal depth;

[0023] S32: Focus on identifying regions rich in split sequences or inconsistent alignment signals, defined as "structural anomaly windows," used to capture misaligned splicing or minor structural anomalies.

[0024] In one embodiment of the present invention, optionally, step S4 includes: combining all the abnormal windows identified in the above steps, calculating the overall assembly error rate in combination with the total number of genome windows, and deriving the corresponding genome quality value accordingly.

[0025] The reference-free genome assembly quality assessment method based on sequencing depth distribution characteristics provided by this invention has the following beneficial technical effects:

[0026] (1) High independence: It can achieve autonomous evaluation of newly assembled genomes without relying on external reference genomes.

[0027] (2) High resolution: The 50 bp window setting enables it to sensitively capture local micro-anomalies that are difficult to detect by traditional methods.

[0028] (3) Multi-dimensional coverage: Through deep distribution detection and comparison pattern screening, assembly errors at both the sequence level (collapse / redundancy) and the structural level (misalignment / distortion) can be identified simultaneously.

[0029] (4) Quantitative precision: It provides a standardized calculation path from local anomalies to overall quality values, serving as an important supplement to traditional evaluation indicators. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a flowchart of a reference-free genome assembly quality assessment method based on sequencing depth distribution characteristics, according to an embodiment of the present invention. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] This invention aims to address the problems of existing genome assembly quality assessment methods, such as strong dependence on external reference genomes, coarse assessment granularity, and difficulty in accurately quantifying local assembly errors (e.g., sequence collapse, redundant splicing, misaligned splicing). This invention provides a more independent assessment scheme with higher spatial resolution (up to 50 bp), enabling refined measurement of assembly quality.

[0034] Figure 1 This is a flowchart of a reference-free genome assembly quality assessment method based on sequencing depth distribution characteristics according to an embodiment of the present invention, as shown below. Figure 1 As shown, this invention provides a reference-free genome assembly quality assessment method based on sequencing depth distribution characteristics, which includes:

[0035] S1: Sequence overlap alignment and dynamic binning;

[0036] S2: Deep anomaly detection based on Gaussian distribution theory model;

[0037] S3: Structural consistency screening based on comparative pattern analysis;

[0038] S4: Comprehensive evaluation and quality value derivation.

[0039] In one embodiment of the present invention, step S1 may optionally include:

[0040] S11: Align the raw PacBio HiFi or Illumina paired-end sequencing data back to the assembled sequence to be evaluated;

[0041] S12: Divide the genome into a large number of continuous and non-overlapping windows (Bins): The window length is set to 50 bp (adjustable) to obtain high spatial resolution while ensuring statistical stability and to capture local anomalous signals.

[0042] In one embodiment of the present invention, step S2 may optionally include:

[0043] S21: Calculate the average alignment depth of each window using the mosdepth software;

[0044] S22: Construct a theoretical Gaussian distribution model at the whole genome level, and use the 3 sigma criterion to perform statistical tests on the window depth values;

[0045] S23: Identify windows that significantly deviate from the two ends of the theoretical distribution as "deep anomaly windows," which correspond to the identification of assembly problems such as sequence collapse, redundant splicing, or local missing parts.

[0046] In one embodiment of the present invention, step S3 may optionally include:

[0047] S31: After excluding windows with abnormal depth, perform a comparative pattern depth analysis on the remaining windows with normal depth;

[0048] S32: Focus on identifying regions rich in split sequences or inconsistent alignment signals, defined as "structural anomaly windows," used to capture misaligned splicing or minor structural anomalies.

[0049] In one embodiment of the present invention, optionally, step S4 includes: combining all the abnormal windows identified in the above steps, calculating the overall assembly error rate in combination with the total number of genome windows, and deriving the corresponding genome quality value accordingly.

[0050] The reference-free genome assembly quality assessment method based on sequencing depth distribution characteristics provided by this invention has the following beneficial technical effects:

[0051] (1) High independence: It can achieve autonomous evaluation of newly assembled genomes without relying on external reference genomes.

[0052] (2) High resolution: The 50 bp window setting enables it to sensitively capture local micro-anomalies that are difficult to detect by traditional methods.

[0053] (3) Multi-dimensional coverage: Through deep distribution detection and comparison pattern screening, assembly errors at both the sequence level (collapse / redundancy) and the structural level (misalignment / distortion) can be identified simultaneously.

[0054] (4) Quantitative precision: It provides a standardized calculation path from local anomalies to overall quality values, serving as an important supplement to traditional evaluation indicators.

[0055] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of one embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing the present invention.

[0056] Those skilled in the art will understand that the modules in the apparatus of the embodiments can be distributed in the apparatus of the embodiments as described in the embodiments, or they can be located in one or more devices different from this embodiment with corresponding changes. The modules of the above embodiments can be combined into one module, or they can be further divided into multiple sub-modules.

[0057] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for assessing the quality of a reference-free genome assembly based on sequencing depth distribution characteristics, characterized in that, include: S1: Sequence overlap alignment and dynamic binning; S2: Deep anomaly detection based on Gaussian distribution theory model; S3: Structural consistency screening based on comparative pattern analysis; S4: Comprehensive evaluation and quality value derivation.

2. The method for assessing the quality of reference-free genome assembly based on sequencing depth distribution characteristics according to claim 1, characterized in that, Step S1 includes: S11: Align the raw PacBio HiFi or Illumina paired-end sequencing data back to the assembled sequence to be evaluated; S12: Divide the genome into a large number of continuous and non-overlapping windows: The window length is set to 50 bp to obtain high spatial resolution while ensuring statistical stability and to capture local anomalous signals.

3. The method for assessing the quality of reference-free genome assembly based on sequencing depth distribution characteristics according to claim 1, characterized in that, Step S2 includes: S21: Calculate the average alignment depth of each window using the mosdepth software; S22: Construct a theoretical Gaussian distribution model at the whole genome level, and use the 3 sigma criterion to perform statistical tests on the window depth values; S23: Identify windows that significantly deviate from the two ends of the theoretical distribution as "deep anomaly windows," which correspond to the identification of assembly problems such as sequence collapse, redundant splicing, or local missing parts.

4. The method for assessing the quality of reference-free genome assembly based on sequencing depth distribution characteristics according to claim 1, characterized in that, Step S3 includes: S31: After excluding windows with abnormal depth, perform a comparative pattern depth analysis on the remaining windows with normal depth; S32: Focus on identifying regions rich in split sequences or inconsistent alignment signals, defined as "structural anomaly windows," used to capture misaligned splices or minor structural anomalies.

5. The method for assessing the quality of reference-free genome assembly based on sequencing depth distribution characteristics according to claim 1, characterized in that, Step S4 includes: combining all the abnormal windows identified in the above steps, calculating the overall assembly error rate based on the total number of genome windows, and deriving the corresponding genome quality value accordingly.

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