Dear Warp community,
I'm working on a subtomogram averaging workflow and encountering an issue during the integration of Warp, PyTom, and Relion5. Below is a description of my current pipeline and the problem I’m facing.
Tomogram Reconstruction:
I reconstructed a single tomogram using Warp.
Template Matching (PyTom):
I used PyTom to perform template matching for ribosomes with the following command:
pytom_extract_candidates.py -j results/MGS001_T1_ts_001_13.51Apx_job.json --cut-off 0.15 -n 1000**I have also used the --relion5-compat version but the end result is the same.
Exporting Particles (WarpTools):
I attempted to export the matched particles using WarpTools ts_export_particles:
WarpTools ts_export_particles \
--settings warp_tiltseries.settings \
--input_star PyTom/results/MGS001_T1_ts_001_13.51Apx_particles.star \
--output_star relion/matching.star \
--output_angpix 13.508 \
--coords_angpix 13.508 \
--box 64 \
--diameter 300 \
--relative_output_paths \
--2dInitially, this failed until I set the _rlnTomoName values to match the name of the corresponding .tomostar file from Warp in the .star file.
After making these changes, the ts_export_particles command ran successfully and generated matching.star and matching_tomograms.star.
Subtomogram Extraction:
In Relion5, I used an Extract Subtomos job with: matching.star as the input particle set and matching_tomograms.star as the input tomogram set
And this is a photo of the Reconstruct tab.
When I run the extraction job in Relion5, I get this and the extraction doesn’t work. I have also tried different box sizes
The particles are removed because they were too close to the edges.
The unbinned dimensions of the tomogram are 11520x8184x3000 with a pixel size of 1.689.
How can I solve this problem and is the way I am trying to integrate Warp and Relion correct or is there a better way?
Any help or insights would be greatly appreciated! Thank you.
Best regards,
Kareem