Here we will step through some of the new visualization tools built into RMINC 1.3. So, let’s start with getting a dataset ready - we’ll look at sex differences in the brain.

# load libraries
library(RMINC)
## Warning in rgl.init(initValue, onlyNULL): RGL: unable to open X11 display
## Warning: 'rgl_init' failed, running with rgl.useNULL = TRUE
library(plotrix) # for legends

# some weirdness potentially particular to my mac. Images are flipped, so fix that:
options(RMINC_flip_image=TRUE)

# load an existing dataset
load("~/data/CREB/CREB-analyses/wtonly.RData")
table(gfwt$Sex)
## 
##  F  M 
## 38 42
mask <- "/Users/jason/data/CREB/mask.mnc"

Let’s start by running a linear model testing the effect of sex on local brain volume.

vs <- mincLm(relJac02 ~ Sex, gfwt, mask=mask)
## Method: lm
## Number of volumes: 80
## Volume sizes: 201 439 298
## N: 80 P: 2
## In slice 
##  0  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90  91  92  93  94  95  96  97  98  99  100  101  102  103  104  105  106  107  108  109  110  111  112  113  114  115  116  117  118  119  120  121  122  123  124  125  126  127  128  129  130  131  132  133  134  135  136  137  138  139  140  141  142  143  144  145  146  147  148  149  150  151  152  153  154  155  156  157  158  159  160  161  162  163  164  165  166  167  168  169  170  171  172  173  174  175  176  177  178  179  180  181  182  183  184  185  186  187  188  189  190  191  192  193  194  195  196  197  198  199  200 
## Done

And we take a look

# first step - load the background anatomy
anatVol <- mincGetVolume("/Users/jason/data/CREB/21aug15_est_conserv-nlin-3.mnc")
## Start: 0 0 0
## Count: 201 439 298
# and a series of slices through the brain
mincPlotSliceSeries(mincArray(anatVol),           # the anatomical volume
                    mincArray(vs, "tvalue-SexM"), # pull out one column of the stats
                    anatLow=700, anatHigh=1400,   # set anatomy thresholds
                    low=2.5, high=10,             # set stats thresholds
                    symmetric=T)                  # show separate upper and lower