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LocScale

v2.3.1.post5Code (opens in a new tab)Paper (opens in a new tab)Docs

Physics-informed local sharpening for cryo-EM density maps.

Input

Unsharpened, unfiltered cryo-EM half-map.

Upload file or drag and dropMRC, MAP · up to 50 MB

Matching unsharpened, unfiltered cryo-EM half-map.

Upload file or drag and dropMRC, MAP · up to 50 MB
0 credits

Output

Configure inputs to begin

Set options on the left, then click “Submit job” — or start from an example.

TRPV1 half-maps — FSC-filtered local sharpening

β-galactosidase — full-map reference scaling

γ-secretase — masked and filtered full map

What is LocScale?

LocScale performs local density scaling for cryo-EM maps. It sharpens map regions according to local signal and reference information rather than applying one global B-factor across the whole volume.

ProteinIQ runs LocScale on uploaded MRC/MAP files and returns the sharpened map plus the processing log and generated map files. The first release focuses on the standard LocScale command for local sharpening with half-map or full-map inputs. Feature-enhanced maps, coordinate-model refinement, hybrid model completion, MPI runs, and PDF reports are tracked for future support.

Inputs

InputDescription
Half Map 1First unsharpened, unfiltered half-map in MRC or MAP format.
Half Map 2Second matching unsharpened, unfiltered half-map.
Cryo-EM MapFull unsharpened map for datasets without half-maps.
MaskOptional MRC/MAP mask. LocScale estimates an FDR mask when this is omitted.
Reference MapOptional MRC/MAP model map used directly as the LocScale reference.

Half-map input is recommended when available because LocScale can use the pair for FSC-based resolution estimation.

ProteinIQ accepts MRC/MAP uploads up to 50 MB per file for this service. This is a ProteinIQ upload limit, not a LocScale file-format limit.

Settings

The default settings match LocScale defaults for local sharpening: one CPU process, FDR threshold 0.01, averaging filter size 3, EMmerNet batch size 8, cube size 32, and no input filtering. Optional resolution, window-size, FDR-window, FDR pre-filter, mask-threshold, and reference-map-resolution fields are passed to the corresponding LocScale command-line options only when set.

Outputs

LocScale returns a primary sharpened MRC map. ProteinIQ also returns the LocScale log and generated processing files such as FDR masks or local-scaling diagnostic maps when LocScale writes them.

Open the returned MRC files in ChimeraX, Coot, or another cryo-EM map viewer for inspection.

LocScale examples

TRPV1 half-maps with FSC filtering

This example demonstrates the recommended paired-half-map workflow on a compact region of the Rattus norvegicus TRPV1 channel dataset EMD-5778. It uses matching unfiltered half-map subvolumes, a data-derived mask, and the corresponding deposited reconstruction as a direct reference map.

  • Inputs: Two 64 × 64 × 64 half-map subvolumes, matching mask, and reference map at 1.2156 Å per voxel
  • Non-default settings: CPU processes = 4, Resolution cutoff (A) = 3.4, Window size (pixels) = 24, and Apply FSC filter = enabled
LocScale Data output for the EMD-5778 TRPV1 half-map example, showing half-map input mode, a 64 by 64 by 64 grid, 1.2156 angstrom voxels, and four processing files
LocScale Data output for the EMD-5778 TRPV1 half-map example, showing half-map input mode, a 64 by 64 by 64 grid, 1.2156 angstrom voxels, and four processing files

The completed job returns locscale_output.mrc on the original 64 × 64 × 64 grid, together with the reconstructed unfiltered map, bfactor_map.mrc, qfit_map.mrc, and the processing log. The table confirms that LocScale used halfmaps mode and preserved the input voxel spacing. This result shows that the paired-map and FSC-filtering workflow completed; it does not by itself establish improved interpretability. Compare the output with the input half-maps in a cryo-EM viewer before using it for model building.

β-galactosidase full-map reference scaling

This EMD-2984 example shows full-map operation on a high-resolution region of Escherichia coli β-galactosidase. The input is an average of matching deposited half-map subvolumes, accompanied by a data-derived mask and the corresponding deposited reconstruction as the direct scaling reference.

  • Inputs: One 48 × 48 × 48 full-map subvolume, matching mask, and reference map at 0.637 Å per voxel
  • Non-default settings: Map input = Full map, CPU processes = 4, Resolution cutoff (A) = 2.2, and Window size (pixels) = 16
LocScale Data output for the EMD-2984 beta-galactosidase example, showing full-map input mode, a 48 by 48 by 48 grid, 0.637 angstrom voxels, and three processing files
LocScale Data output for the EMD-2984 beta-galactosidase example, showing full-map input mode, a 48 by 48 by 48 grid, 0.637 angstrom voxels, and three processing files

ProteinIQ returns a 48 × 48 × 48 sharpened MRC map at the same 0.637 Å voxel spacing, plus bfactor_map.mrc, qfit_map.mrc, and the LocScale log. The compact subvolume makes the reference-map workflow quick to inspect, but it is not a substitute for processing and evaluating the complete EMD-2984 reconstruction.

Masked and filtered γ-secretase full map

This example uses a compact region from the EMD-3061 human γ-secretase half-map pair to demonstrate full-map processing with both an explicit mask and input filtering. The supplied reference is the matching region from the deposited reconstruction.

  • Inputs: One 48 × 48 × 48 full-map subvolume, matching mask, and reference map at 1.4 Å per voxel
  • Non-default settings: Map input = Full map, CPU processes = 4, Resolution cutoff (A) = 3.4, Window size (pixels) = 24, and Filter input maps = enabled
LocScale Data output for the EMD-3061 gamma-secretase example, showing full-map input mode, a 48 by 48 by 48 grid, 1.4 angstrom voxels, and three processing files
LocScale Data output for the EMD-3061 gamma-secretase example, showing full-map input mode, a 48 by 48 by 48 grid, 1.4 angstrom voxels, and three processing files

The output table records the expected 48 × 48 × 48 grid, 1.4 Å voxel spacing, and three processing files. This confirms that LocScale completed the masked, filtered full-map workflow and returned its sharpened map and diagnostics. Whether filtering improves local density for a particular structural interpretation still requires direct comparison with the unfiltered input and independent validation against the half-maps.

Limitations

  • Inputs should be unsharpened and unfiltered. Pre-sharpened maps can produce misleading artifacts.
  • Coordinate-model and hybrid LocScale modes require additional REFMAC/CCP4 runtime support and are not enabled in this release.
  • Feature-enhanced maps and pVDDT confidence maps are not enabled in this release.
  • Point-group symmetry options are held at the LocScale default of C1 until symmetry-specific runtime checks are added.

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