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brainGraph 3.1.0

2024-04-03

Minor changes

brainGraph 3.0.3

2024-02-20

Bug fixes

Minor changes

brainGraph 3.0.2

2021-02-03

Bug fixes

brainGraph 3.0.1

2020-10-19

Bug fixes

brainGraph 3.0.0

2020-09-28

New functions/features

  1. There are a few dozen new S3 methods for bg_GLM objects. See methods(class='bg_GLM') for the full list. coeff_determ calculates the coefficient of determination. coeff_table returns the coefficients table (same as summary.lm(x)$coefficients) for each region.
  2. There are new GLM fitting functions (prefixed with fastLmBG) that are significantly faster and work with matrix/array inputs. You can see these with the code apropos('fastLm').
  3. New functions randomise and randomise_3d can be called directly (although not recommended), and the partition function is now exported. Each of these is for permutation-based analysis of linear models. Furthermore, there are new permutation methods (manly, draperStoneman, and stillWhite).
  4. New object brainGraphList for a collection of all graphs at a single density/threshold. There are multiple S3 methods for this object, including the creation method make_brainGraphList.
  5. make_brainGraph is now a S3 method.
  6. There are several new matrix utility functions. inv calculates the the “unscaled covariance” matrix used in linear models. pinv calculates the pseudoinverse. qr calculates the QR decomposition for each matrix in a 3D array. colMax, colMin, and colMaxAbs calculate the max, min, and max of the absolute value across matrix columns. is_binary determines if a matrix consists only of 0’s and 1’s. symmetrize is now a S3 method. symm_mean symmetrizes a matrix using the mean of off-diagonal elements.
  7. There are 4 new atlases: hcp_mmp1.0 (HCP multimodal atlas), power264, gordon333, and brainnetome
  8. New function sim.rand.graph.hqs generates random graphs from random covariance matrices for structural covariance networks using the HQS algorithm.
  9. New plotting function slicer plots multiple graphs in a single figure.
  10. Fewer package dependencies.
  11. mean_distance_wt calculates weighted shortest path lengths.

Removed/renamed functions

brainGraph 2.7.2

2019-10-20

Bug fix

brainGraph 2.7.1

2019-06-29

Bug fix

brainGraph 2.7.0

2018-12-15

New functions/features

Minor changes

brainGraph 2.6.1

2018-12-07

Bug fix

brainGraph 2.6.0

2018-09-04

Bug fix

New functions/features

Minor changes

brainGraph 2.5.0

2018-09-01

Bug fix

Minor changes

brainGraph 2.4.0

2018-07-21

New features

brainGraph 2.3.4

2018-07-06

Bug fix

New features

brainGraph 2.3.3

2018-06-25

Bug fix

brainGraph 2.3.2

2018-06-22

Bug fix

Minor change

brainGraph 2.3.1

2018-06-20

Bug fix

brainGraph 2.3.0

2018-06-20

Bug fix

New features

Lpv.wt <- distances(g)
Lpv.wt[is.infinite(Lpv.wt)] <- NA
g$Lp.wt <- mean(Lpv.wt[upper.tri(Lpv.wt)], na.rm=T)

Minor changes

brainGraph 2.2.0

2018-05-28

Minor changes

brainGraph 2.1.0

2018-05-03 (mostly changes to structural covariance network functionality)

Bug fix

New functions/features

Minor changes

brainGraph 2.0.4

2018-04-28

Bug fix

Minor changes

brainGraph 2.0.3

2018-04-26

Bug fix

brainGraph 2.0.2

2018-02-23

Release on CRAN; bugfix release.

Bug fix

brainGraph 2.0.1

2018-02-07

Bug fix

brainGraph 2.0.0

2018-02-05

2nd major release; 6th CRAN release. (The previous CRAN release was at v1.0.0)

For other updates and bug fixes, see the minor release notes below.

New functions/features

  1. Mediation analysis is now possible through brainGraph_mediate.
  2. I have introduced some simple S3 classes and methods. All of the classes have plot (except NBS) and summary methods. The classes and corresponding “creation functions” are:
Class Creation func. Description
brainGraph make_brainGraph Any graph with certain attributes
bg_GLM brainGraph_GLM Results of GLM analysis
NBS NBS Results of NBS analysis
mtpc mtpc Results of MTPC analysis
brainGraph_GLM make_glm_brainGraph Graphs from GLM analysis
brainGraph_NBS make_nbs_brainGraph Graphs from NBS analysis
brainGraph_mtpc make_glm_brainGraph Graphs from MTPC analysis
brainGraph_mediate make_mediate_brainGraph Graphs from mediation analysis
brainGraph_boot brainGraph_boot Results of bootstrap analysis
brainGraph_permute brainGraph_permute Results of permutation tests
brainGraph_resids get.resid Residuals for covariance networks
  1. Multiple contrasts (in the same function call), as well as F-contrasts, are now allowed in the GLM-based functions: brainGraph_GLM, mtpc, NBS, and get.resid.
  2. Designs with 3-way interactions (e.g., 2 x 2 x 2) are now allowed for GLM-based analyses.
  3. Permutations for GLM-based analyses are now done using the Freedman-Lane method (the same as in FSL’s randomise and in PALM).
  4. Plot the “diagnostics” from GLM analyses through the plot.bg_GLM method to the output of brainGraph_GLM.
  5. Plot the statistics from MTPC analyses through the plot.mtpc method for mtpc results.
  6. aop has a new argument control.value allowing you to specify the control group; all comparisons will be to that group.
  7. Most of the GLM-based functions have a new argument, long, which will not return all of the permutation results if long=FALSE.

Removed/renamed functions

Major changes

brainGraph 1.6.0

2017-09-14

Bug fix

Minor changes

brainGraph 1.5.0

2017-08-31

Bug fix

Major changes

New functions

Minor changes

brainGraph 1.4.0

2017-06-10

Bug fix

New functions

Minor changes

brainGraph 1.3.0

2017-04-30

Bug fix

Major changes

Minor changes

brainGraph 1.2.0

2017-04-29

Bug fix

Major changes

New functions

brainGraph 1.1.0

2017-04-22

Bug fix

New functions

Major changes

Minor changes

brainGraph 1.0.0

2017-04-10

First major release; Fifth CRAN release

Bug fix

Major changes

New functions

Minor changes

brainGraph 0.72.0

2016-10-10

Fourth CRAN release

Bug fix

Major changes

New functions

Minor changes

brainGraph 0.62.0

2016-04-22

Third CRAN release

Bug fix

for (i in seq_along(groups)) {
  for (j in seq_along(densities)) {
    max.deg <- max(V(g[[i]][[j]])$degree)
    phi.norm[[i]][[j]]$p <- sapply(seq_len(max.deg), function(x)
        sum(phi.norm[[i]][[j]]$phi.rand[, x] >= phi.norm[[i]][[j]]$phi.orig[x]) / N)
  }
}

where N is the number of random graphs generated. * dti_create_mats: there was a bug when sub.thresh equals 0; it would take matrix entries, even if they were below the mat.thresh values. This has been fixed. Argument checking has also been added.

Major changes

New functions

Minor changes

brainGraph 0.55.0

2015-12-24

Second CRAN release

New functions

Minor changes

brainGraph 0.48.0

2015-12-08

Initial CRAN release

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.