Meta-analysis of EBV GWAS of NPC. by Ka Wo Wong (18625847)

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Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

Performance metrics of 28 and 9 SNPs in predicting NPC. by Ka Wo Wong (18625847)

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Effective cluster radius from Ripley’s H-function for the NPC dataset. by Daniel F. Nino (9745709)

Python-based Monte Carlo Simulation Tool by Yangfan Jiang (9372782)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

“…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

“…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…”

Distribution of cases and controls in the nine clusters. by Ka Wo Wong (18625847)

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Number of samples carrying the nine high risk SNPs in each cluster. by Ka Wo Wong (18625847)

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Genotyping rate and sequencing depth of 507 EBV genomes. by Ka Wo Wong (18625847)

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Degree of linkage disequilibrium against p-values of meta-analysis. by Ka Wo Wong (18625847)

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Characteristics of 507 samples included in the current meta-analysis. by Ka Wo Wong (18625847)

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Variants that passed the permuted p-value cut-off in the meta-analysis of GWAS. by Ka Wo Wong (18625847)

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Summary statistics for sequencing and variant calling for 507 samples. by Ka Wo Wong (18625847)

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Number of samples in each cluster carrying the 9 SNPs shared by the high-risk lineage only. by Ka Wo Wong (18625847)

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Genotypes of 38 SNPs that characterized the high-risk EBV lineage. by Ka Wo Wong (18625847)

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Distribution of samples carrying the risk alleles identified previously. by Ka Wo Wong (18625847)

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Sliding window analysis with a window size of 1000 nucleotides and a step size of one base-pair. by Ka Wo Wong (18625847)

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Percentage of genotype call missingness along the EBV genome. by Ka Wo Wong (18625847)

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Logistic regression of disease states on haplotypes constructed from 56 variants that passed p-value threshold in the meta-analysis, with age and sex as covariates. by Ka Wo Wong (18625847)

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