SjorsUsefulScripts

From Xmipp to 3D-variance in Spider

This recipe allows to use (a simplistic version of) Pawel Penzeck's 3D-variance routines in Spider, starting from images aligned in Xmipp (with the adequate angles in the image headers). This recipe does not include reconstructions from noise-only images, nor does it exclude images with large differences with the re-projections of the volume. This means that the absolute values of the resulting 3D-variance may not be meaningful, but probably the 3D-variance map serves equally well to detect heterogeneity. Anyway, the part of preparing the Xmipp-aligned images would also serve for the complete 3D-variance calculation.

Prepare the Xmipp images:

#!/use/bin/env csh
xmipp_applygeo -i images.sel -oext app
xmipp_adapt_for_spider extract_angles -i imagesapp.sel -o angles.spi -order psi tilt rot
set nn=`wc -l imagesapp.sel | awk '{print $1}'`
xmipp_adapt_for_spider generate_count -max ${nn} -o select.spi
xmipp_adapt_for_spider rename -i imagesapp.sel -o out.sel -oroot img -oext spi
mkdir imgs
xmipp_mvsel out.sel imgs/

And then run Spider (the now free version for linux):

 
mkdir VOLS
spider var/spi b92
spider fil/spi b75

Where b92.var is:

MD
VB OFF

VA 3Q
imgs/img*****
select
angles
*
1000 ; Number of reconstructions
VOLS/vol*****
1
EN D

And b75.fil is:

X40=1000 ; Number of reconstructions
MS
_8@
(63,63,63) ; Reconstruction dimensions
X40

do lb1 x21=1,X40
FQ NP
VOLS/vol{*****x21}
_8@{****X21}
(7)
(0.07,0.15) ; Filter parameters 
lb1

VA 3R
_8@*****
(1-X40)
VOLS/G1  ; Average reconstruction
VOLS/G2  ; 3D variance
VOLS/G3
EN D