Hi,
I was expecting the following to yield the same results:
(1) fdr -i my-p-image -m my-mask -q 0.05 > fdr_thr.txt
Probability Threshold is:
my-fdr0.05-threshold
fslmaths my-p-image (-mul -1 -add 1) -[u]thr (1 -) my-fdr0.05-threshold
-mas my-mask thresh_(1_minus_)fdr-q0.05
-> here I have put the commands to get 1-fdr-thresholded (as opposed to
fdr-thresholded) values in parenthesis while to get fdr-thresholded values
I have to use the uthr command (u put in brackets)
(2)
This does not seem to produce the same results compare to
fdr -i my-p-image -m my-mask -a fdrp_LV
and checking the 0.05 thresholded results
Also using 1_minus_my-p-image and --oneminusp / --othresh does not lead
to results that match the above (which I expected).
Using --oneminusp / --othresh gets close to thresholding the above but
does still differs in the suprathreshold voxels.
Esentially, determining the fdr threshold by:
fdr -i my-p-image -m my-mask -q 0.05
and creating a 1-p image, thresholded that at 1-thresh for my
fdr-threshold and remasking, using fslmaths
DOES NOT produce the same result as using the -a or --oneminusp /
--othresh flags.
Any ideas?
Cheers,
Andreas
Von: "Anderson M. Winkler" <[log in to unmask]>
Antworten an: FSL - FMRIB's Software Library <[log in to unmask]>
Datum: Sonntag, 24. Mai 2015 12:16
An: <[log in to unmask]>
Betreff: Re: [FSL] interpreting covariate interactions across groups with
dual regression
Hi Alva,
The input for FDR (-i) has to be the image with the uncorrected p-values.
This goes for either for conventional voxelwise statistics (produced in
randomise with -x) or for TFCE (produced with -T or --T2). The corrected
p-values shouldn't be used with FDR, neither the statistics themselves.
To get the uncorrected p-values, use the --uncorrp option in randomise
then (just add it to the dual_regression script).
Consider using the option "-a" in FDR instead of the options -q and
--othresh, so that an image with all the adjusted p-values is produced.
This image you can then supply to the command cluster, with a threshold of
0.99 (and indeed, these are all 1-p).
All the best,
Anderson
On 24 May 2015 at 02:55, Alva Tang <[log in to unmask]> wrote:
Thanks for your explanations Anderson,
Following your second point to run FDR on the contrasts, I tried the
following:
fdr -i dr_stage3_ic0014_tstat1.nii.gz --oneminusp -q 0.01 -m
avg_mask.nii.gz --othresh=fdr_thresh_ic0014_tstat1_withmask -v
cluster -i fdr_thresh_ic0014_tstat1_withmask -t 0.99
I followed this thread,
https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1502&L=FSL&D=0&1=FSL&9=A&
I=-3&J=on&d=No+Match%3BMatch%3BMatches&z=4&P=211203 , but am not sure
about the first command. Stage 3 of the dual regression by default
derives 2 images for each contrast: ic#_tfce_corrp and ic#_tstat. Is the
input file the ic#_tstat or do I need to run randomise again with the
--uncorrp option? Also is the ic#_tstat a 1-p image, or would I have to
transform it? I am not sure, I read on the discussion board that
randomise gives 1-p images?
Sorry if this is repetitive and thank you for your help,
Alva
On Fri, May 22, 2015 at 4:34 AM, Anderson M. Winkler
<[log in to unmask]> wrote:
oops, there was a "Paste" issue and a sentence fell off place at the top
of the message, but it should be clear as you read down.
On 22 May 2015 at 09:19, Anderson M. Winkler <[log in to unmask]>
wrote:
Significant interaction without individual group effectsHi Alva,
Please, see below:
On 22 May 2015 at 01:09, Alva Tang <[log in to unmask]> wrote:
Dear FSL experts,
I am looking at differences in resting state networks using dual
regression to see whether connectivity differs across 3 groups as a
function of anxiety. After setting up the design matrix with the
mean-centered values of anxiety, I set up the contrasts below.
normal SGA AGA
Anxiety_norm Anxiety_SGA Anxiety_AGA
Slope normal > SGA 0 0 0 1 -1 0
Slope SGA > Slope norm 0 0 0 -1 1 0
Slope normal > slope AGA 0 0 0 1 0 -1
Slope AGA > slope normal 0 0 0 -1 0 1
Slope SGA > Slope AGA 0 0 0 0 1 -1
Slope AGA > Slope SGA 0 0 0 0 -1 1
1. If a region is statistically significant for the first contrast, does
it mean that region has increased connectivity for the normal > the SGA
group in relation to anxiety, such that, anxiety has different effects on
this region between groups?
Yes.
If this interpretation is correct, how do I visualize the direction of
this effect in the program (to see whether increases or decreases in
anxiety is related to the increased connectivity of this region); Is there
a way to plot the anxiety scores and the activity of that region and
across groups or would I extract these values then plot in another program?
There isn't a direct way to visualise. You'll have to run a few more
contrasts to check the direction of each interaction EV (as opposed to the
differences), and see if the signs of the statistics in the regions where
you found significance are positive or negative. There is a lengthy thread
in the mailing list discussing how it can be done, search for "Significant
interaction without individual group effects" to see all. The first in the
thread should be this one
<https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=FSL;3b4f778f.1311>.
2. To correct for multiple comparisons using false discovery rate,
there's a paper (Veer et al., 2010) that inputted the tfce_corrp
difference images and then spatially masked with the binary representation
of the pooled group main effects images. This was to decrease
susceptibility to type 1 errors. I am not understanding how the masking
here contributes to a more stringent threshold or which masks to select?
I just found the paper. They seem to have used TFCE-corrected for the main
group effects, and FDR for the between group-effects, and these were
masked after doing FDR. I'm not reading the full paper, and perhaps there
is justification for this somewhere. The way I would do is not test the
main group effects at all (these are known to be different than zero), and
test just the between-group differences, using then perhaps FDR. If
masking, I'd do it before FDR. Maybe the main group effects were tested in
order to produce a mask, which otherwise perhaps would haven't been
available, I'm not sure.
All the best,
Anderson
If you could please help me, that would be much appreciated. Thank you.
Alva
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