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--- eman2:e3make3d_point [2026/03/20 13:55] – steveludtke
+++ eman2:e3make3d_point [2026/03/20 17:45] (current) – steveludtke
@@ Line 1: / Line 1: @@
-===== Preview of e3_make3d_point for better 3-D reconstructions =====
+===== Preview of e3make3d_point for better 3-D reconstructions =====
+**THE METHOD DESCRIBED ON THIS PAGE IS NOT YET PUBLISHED, IT IS PROVIDED TO GIVE PEOPLE THE OPPORTUNITY TO TRY IT OUT AS WE MAKE FINAL IMPROVEMENTS**
+If you have any difficulties (or successes) with this method, please let us know, and feel free to ask questions (sludtke@bcm.edu).
 The under-development e3make3d_point.py can be used to produce reconstructions which:
@@ Line 13: / Line 16: @@
 ==== If you are starting with an EMAN2/3 project ====
-  * Run a standard e2spa_refine.py on your phase-flipped particle data
+  * Run a standard //e2spa_refine.py// on your phase-flipped particle data
-  * Run exactly the same command with the "--pointrecon 500" option added to the command-line, then compare the results of the 2 refinements.
+  * Run exactly the same command with the //--pointrecon 500// option added to the command-line, then compare the results of the 2 refinements.
   * 500 is the number of first-stage points to use in the reconstruction as described above.
@@ Line 22: / Line 25: @@
   * cd <folder where your STAR file is>
   * e3relion_convert.py <star file>
+    * This involves making a copy of your data (with compression). It is creating a complete EMAN2 project folder, so for a large project will take a little time.
   * cd eman3
-  * e3make3d_point.py sets/fromstar__ctf_flip.lst --volout fromstar.hdf:12 --gaussout fromstar.txt --volfiltlp 3 --initpoints 500 -v 2
+  * e3make3d_point.py sets/fromstar%%__%%ctf_flip.lst --volout fromstar.hdf:12 --gaussout fromstar.txt --volfiltlp 3 --initpoints 500 -v 2
-    * volfiltlp is the resolution in Å the final map will be (Gaussian) filtered to.
+    * volfiltlp is the resolution in Å the final map will be (Gaussian) filtered to. If you decide the map is over/under filtered the final volume can easily be recreated from the other output file.
+  * The output volume is fromstar.hdf, which can be opened with e2display.py or Chimera
+  * If you wish to generate even/odd maps for a GSFSC calculation, you can run the program twice with the --class 0 (even) option on the first run and the --class 1 (odd) option on the second run (with modified output filenames).
+  * Alternatively you could run an EMAN2 style iterative refinement with point-based reconstruction, eg:
+    * e2spa_refine.py --ptcl sets/fromstar%%__%%ctf_flip.lst --ref <starting model> --parallel thread:32:<fast scratch folder> --threads 32 --sym <symmetry> --res <start res> --niter 2 --tophat local --pointrecon 500 -v 1
+    * You may need to look at a full EMAN2 tutorial to pick specific options for your case. The only change is the addition of the --pointrecon option.
+==== If you are starting with a CryoSparc refinement ====
+You will need to export your metadata (as a .cs file) and corresponding particle stack from CryoSparc and have these stored together somewhere on your local computer.
+  * conda activate eman2
+  * cd <folder where your .cs file is>
+  * e3cryosparc_convert.py <exported.cs> --phaseflip -v 2
+    * This involves making a copy of your data (with compression). It is creating a complete EMAN2 project folder, so for a large project will take a little time.
+  * cd eman3
+  * e3make3d_point.py sets/fromcs%%__%%ctf_flip.lst --volout fromcs.hdf:12 --gaussout fromcs.txt --volfiltlp 3 --initpoints 500 -v 2
+    * volfiltlp is the resolution in Å the final map will be (Gaussian) filtered to. If you decide the map is over/under filtered the final volume can easily be recreated from the other output file.
+  * The output volume is fromcs.hdf, which can be opened with e2display.py or Chimera
+  * You can also test a standard EMAN2 style iterative refinement with point-based reconstruction, eg:
+    * e2spa_refine.py --ptcl sets/fromcs%%__%%ctf_flip.lst --ref <starting model> --parallel thread:32:<fast scratch folder> --threads 32 --sym <symmetry> --res <start res> --niter 2 --tophat local --pointrecon 500 -v 1
+    * You may need to look at a full EMAN2 tutorial to pick specific options for your case. The only change is the addition of the --pointrecon option.