The invention is suitable for the technical field of
biology, and provides a
giardia genome SNP bar code
typing method based on
machine learning optimization. According to the method,
typing is completed through
data acquisition and preprocessing, unsupervised group structure clustering,
machine learning
feature screening, bar code SNP panel construction, robustness evaluation and detection and interpretation. According to the method, an XGBoost model is trained by taking an
unsupervised clustering result as a
label, and 50 loci are screened in combination with an SHAP index to form an SNP bar code panel. The resolution ratio of the panel is close to that of whole
genome SNP
typing only by using a small number of sites, the performance of the panel is superior to that of MLST, and high accuracy is kept under low-
quality data such as 15X low depth. Detection
modes such as multiple PCR and the like and standardized reports are supported, the process adopts
modular design and can be realized in a computer readable storage medium, and an effective tool is provided for
giardia public health monitoring and cross-host
traceability.