Pinned Repositories
Breast_cancer-5-year-survival-prediction
version1 for brca
Budd-Chiari-syndrom
Background: Budd-Chiari syndrome (BCS) is characterized by hepatic venous outflow obstruction and in severe cases, is even life-threatening. In the past few decades, the risk factors related to BCS, including inherited and acquired hypercoagulable states or other predisposing factors, have been reported. However, a large number of patients have no identifiable etiological factors. And, there are different causes for BCS in the West and East. In China, segmental or membranous inferior vena cava obstruction is the main manifestation of BCS. The prevalence of prothrombotic disorders seems to be relatively low. Methods: In this study, 500 BCS patients and 696 normal individuals were recruited for whole-exome sequencing. We carried out whole-exome sequencing and developed polygenic risk scoring (PRS) model based on the PLINK, LASSOSUM, BLUP, and BayesA method. We further performed the BCS risk prediction by intersecting the BCS PRS model with the venous thromboembolism and vascular malformations model. Results: BCS-related mutations, such as rs1042331, rs34370305, and rs73739662, were discovered by BCS genome-wide association studies. By comparing different polygenic risk scoring algorithms, the optimal model produced by the BayesA algorithm was determined. By testing additionally recruited experimental samples, it was found that area under the ROC curve>0.9. Conclusion: Further interpretation of the model also provides new insights to explain the difference in genetic risk for BCS between China and the West. In addition, we also found that BCS, venous thromboembolism, and vascular malformations might share some common genetic risks, which might provide new insights into the pathogenesis of BCS.
PRS-myopia
We have constructed various algorithmic prediction models for ophthalmic diseases using data from 500,000 individuals in the UK Biobank, such as C+T, blup, LDpred, lassosum, PRS-CS, and bayesA. Through these models, you can explore any dataset you want to analyze and predict diseases.
VThunter
VThunter
jxs1996's Repositories
jxs1996/Breast_cancer-5-year-survival-prediction
version1 for brca
jxs1996/Budd-Chiari-syndrom
Background: Budd-Chiari syndrome (BCS) is characterized by hepatic venous outflow obstruction and in severe cases, is even life-threatening. In the past few decades, the risk factors related to BCS, including inherited and acquired hypercoagulable states or other predisposing factors, have been reported. However, a large number of patients have no identifiable etiological factors. And, there are different causes for BCS in the West and East. In China, segmental or membranous inferior vena cava obstruction is the main manifestation of BCS. The prevalence of prothrombotic disorders seems to be relatively low. Methods: In this study, 500 BCS patients and 696 normal individuals were recruited for whole-exome sequencing. We carried out whole-exome sequencing and developed polygenic risk scoring (PRS) model based on the PLINK, LASSOSUM, BLUP, and BayesA method. We further performed the BCS risk prediction by intersecting the BCS PRS model with the venous thromboembolism and vascular malformations model. Results: BCS-related mutations, such as rs1042331, rs34370305, and rs73739662, were discovered by BCS genome-wide association studies. By comparing different polygenic risk scoring algorithms, the optimal model produced by the BayesA algorithm was determined. By testing additionally recruited experimental samples, it was found that area under the ROC curve>0.9. Conclusion: Further interpretation of the model also provides new insights to explain the difference in genetic risk for BCS between China and the West. In addition, we also found that BCS, venous thromboembolism, and vascular malformations might share some common genetic risks, which might provide new insights into the pathogenesis of BCS.
jxs1996/PRS-myopia
We have constructed various algorithmic prediction models for ophthalmic diseases using data from 500,000 individuals in the UK Biobank, such as C+T, blup, LDpred, lassosum, PRS-CS, and bayesA. Through these models, you can explore any dataset you want to analyze and predict diseases.
jxs1996/VThunter
VThunter