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Biostatistics and Imaging Genomics analysis lab – Statistics & Signal

Software

BIG-S2 GitHub

  1. TS2WM: integration of brain tumor segmentation and GBM tumor impact on the WM integrity
  2. FHFRM: Functional Hybrid Factor Regression Model
  3. keras-gnm: Keras implementation of the Graph-based joint model with Nonignorable Missingness (GNM)
  4. L2RM: Low-rank Linear Regression Model
  5. BSOINN: Bayesian Scalar on Image Regression with Non-ignorable Non-response
  6. SDM: Statistical Disease Mapping
  7. GFPLVCM: Generalized Functional Partial Linear Varying-Coefficient Model for asynchronous longitudinal data
  8. D-CCA: A Decomposition-based Canonical Correlation Analysis for High-dimensional Datasets
  9. SVCM: Spatially Varying Coefficient Model, for association between massive imaging data and a set of covariates of interest
  10. FSEM: Functional Structural Equation Models for Twin Functional Data
  11. PSC: simultaneously characterize a large number of white matter bundles within and across different subjects for group analysis [link2]
  12. MonFuncReg: Monotone Nonparametric Regression for Functional/Longitudinal Data
  13. SMAC: Spatial Multi-category Angle-based Classifier
  14. MILFM: Multiple-Index Latent Factor Model for clinical outcome prediction based on massive features
  15. SSPM: Spatial Statistical Parametric Mapping (includes MAGEE, FADTTS and FMPM)
  16. MGLREG: analysis of secondary phenotypes collected in multiple group association studies
  17. FGWAS: Functional Genome Wide Association analysiS for imaging genetic analysis
  18. TPRM: Tensor Partition Regression Models with applications in imaging biomarker detection
  19. MFSDA: association testing between the multivariate shape measurements and demographic/clinical variables [python version]
  20. L2R2: Bayesian longitudinal low-rank regression models for imaging genetic data from longitudinal studies [R version]
  21. SpatialACE: estimate the spatial additive genetic, common environmental, and unique environmental model for cortical surface data
  22. BLGRM: Bayesian Row-rank Graph Regression Models for matrix response data
  23. MWPCR: Multiscale Weighted Principal Component Regression
  24. BCor-SIS: Ball Correlation Sure Independence Screening
  25. RMRSS: Regression Models on Riemannian Symmetric Spaces
  26. SCD: Perturbation and Scaled Cook’s Distance
  27. SSEM: Bayesian Lasso for Semiparametric Structural Equation Models Toolkit
  28. HECD: Pipeline for H&E image preprocessing and cell detection
  29. MARM: DTI-Statistics “multiscale adaptive regression model (MARM)” Toolkit
  30. MAGEE-SSPM: Multiscale Adaptive Generalized Estimating Equation – Spatial Statistical Parametric Mapping
  31. GENV: Groupwise Envelope model
  32. GHMM: Diseased Region Detection of Longitudinal Knee Magnetic Resonance Imaging Data
  33. FVGWAS: Fast Voxelwise Genome Wide Association Analysis
  34. LocalSPD: Local Polynomial Regression for Symmetric Positive Definite Matrices
  35. FADTTS: DTI-Statistics functional analysis pipeline Toolkit
  36. VCDF: Varying Coefficient Model For Modeling Diffusion Tensors Along White Matter Tracts
  37. SCALNET: Scalable network estimation with L0 penalty for ultra-large Gaussian graphical models
  38. MONFP: Clustering High-Dimensional Landmark-Based Two-Dimensional Shape Data
  39. FMPM: Functional Mixed Processes Models
  40. FRESMEM: Fixed and Random Effects Selection in Mixed Effects Toolkit
  41. FRATS: Functional Regression Analysis of DTI Tract Statistics
  42. PRM-MIP: Projection Regression Models for Multivariate Imaging Phenotype