Software

dyna-LOCUS:  A Low-Rank Decomposition of Brain Connectivity Matrices with Uniform Sparsity for Dynamic Functional Connectivity

https://github.com/Emory-CBIS/dynaLOCUS

• Ran, J.†, Wang, Y. and Guo, Y.  (2024). Unveiling hidden sources of dynamic functional connectome through a novel regularized blind source separation approach. Imaging Neuroscience, 2, pp.1-30. Open Access

BSPBSS: Bayesian Spatial Blind Source Separation

https://cran.r-project.org/web/packages/BSPBSS/index.html

• Wu, B., Guo, Y. and Kang, J. (2022). Bayesian Spatial Blind Source Separation via the Thresholded Gaussian Process. Journal of the American Statistical Association (JASA) Theory and Methods, pp1-12. 

LOCUS:  A Low-Rank Decomposition of Brain Connectivity Matrices with Uniform Sparsity

https://cran.r-project.org/web/packages/LOCUS/index.html

• Wang, Y.† and Guo, Y. (2023).   LOCUS: A Novel Decomposition Method for Brain Network Connectivity Matrices using Low-rank Structure with Uniform Sparsity. Annals of Applied Statistics, 17(2): 1307-1332. 

MMM:  A Multimodal Multilevel Model for fusing fMRI and dMRI

 https://github.com/Emory-CBIS/MMM

•  Hu, Y.†, Zeydabadinezhad, M., Li, L. and Guo,Y. (2022).  A multimodal multilevel neuroimaging model for investigating brain connectome development. Journal of the American Statistical Association (JASA).  Open Access.

DICA:  Distributional ICA. 

   https://github.com/Emory-CBIS/DICA

•  Wu,B. †, Pal, S., Kang,K. and Guo,Y.  (2021).  Distributional Independent Component Analysis for Diverse Neuroimaging Modalities.  Biometrics.  Open Access.

DDT: A Matlab toolbox for the Difference Degree Test. 

      https://github.com/Emory-CBIS/DDT 

•  Higgins, IA†, Kundu, S., Choi, KS., Mayberg, H., Guo, Y (2019), A Differential Degree Test for Comparing Brain Networks. Human Brain  Mapping, 1-19. https://doi.org/10.1002/hbm.24718. 

 HINT : A Matlab GUI-based Hierarchical INdependent component analysis Toolbox. 

      Downloading:  HINT 2.0  at https://github.com/Emory-CBIS/HINT  

      A video tutorial by Josh Lukemire on Youtube:   https://www.youtube.com/watch?v=tRl9UFbT3R4&t=723s 

• Wang, Y., and Guo, Y. (2019). A hierarchical independent component analysis model for longitudinal neuroimaging studies. NeuroImage, 189, 380-400. https://doi.org/10.1016/j.neuroimage.2018.12.024

• Lukemire, J.† , Wang, Y., Verma, A. and Guo, Y (2020).  HINT: A Hierarchical Independent Component Analysis Toolbox for Investigating Brain Functional Networks using Neuroimaging Data. Journal of Neuroscience Methods. 341: 108726. DOI.   arXiv  

• Shi, R and Guo, Y . (2016). Investigating differences in brain functional networks using hierarchical covariate-adjusted independent component analysis. Annals of Applied Statistics. 10(4): 1930-1957. 

DensParcorr: an R package for Dens-Based Method for Partial Correlation Estimation in Large Scale Brain Networks. 

     https://cran.r-project.org/web/packages/DensParcorr/index.html.

• Wang, Y, Kang J, Kemmer, PB and Guo, Y. (2016). An efficient and reliable statistical method for estimating functional connectivity in large-scale brain networks using partial correlation.  Frontiers in Neuroscience. 10:123. 

siGGM: an R package for structurally informed Gaussian Graphical Model. 

     https://github.com/Emory-CBIS/siGGM 

• Higgins, IA†, Kundu, S. and Guo, Y., (2018). Integrative Bayesian Analysis of Brain Functional Networks Incorporating  Anatomical Knowledge. NeuroImage, 181: 263-278. 

NIRStat:  an R package for Studying Near-Infrared Spectroscopy (NIRS) Time Series 

     https://cran.r-project.org/web/packages/NIRStat/index.html

•  Guo, Y, Wang Y., Marin, T., Easley, K., Patel, R.M., Josephson, C.D. (2018). Statistical Methods for Characterizing transfusion-related changes in regional oxygenation using Near-infrared spectroscopy (NIRS) in preterm infants. Statistical Methods in Medical Research.  https://doi.org/10.1177/0962280218786302.   PubMed

CCPD: a Matlab toolbox for Connectivity Change Point Detection. 

     https://github.com/Emory-CBIS/CCPD 

• Kundu, S., Ming, J., Pierce, J. McDowell, J. and Guo, Y , (2018), Estimating Dynamic Brain Functional Networks Using Multi-subject fMRI Data, NeuroImage, 183: 635-649.

nonpar.ccc.est: an R package for nonparametric estimation of Lin's concordance correlation coefficient (CCC) in the presence of censored observations. 

    http://web1.sph.emory.edu/users/yguo2/software.html

• Guo Y and Manatunga AK (2007). Nonparametric estimation of the concordance correlation coefficient under univariate censoring. Biometrics, 63(1): 164-172.