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Add more details about the output distogram format.

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PiperOrigin-RevId: 310134498
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Augustin Zidek
2020-05-06 13:41:49 +01:00
committed by Diego de Las Casas
parent 7bb484fffa
commit 6f14cb5983
1 changed files with 23 additions and 2 deletions
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alphafold_casp13/README.md
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@@ -154,8 +154,8 @@ When running `run_eval.sh` the output has the following directory structure:
* **distogram/**: Contains 4 subfolders, one for each replica. Each of these
contain the predicted ASA, secondary structure and a pickle file with the
distogram for each crop. It also contains an `ensemble` directory with the
ensembled distograms.
distogram for each crop (see below for more details). It also contains an
`ensemble` directory with the ensembled distograms.
* **background_distogram/**: Contains 4 subfolders, one for each replica. Each
of these contain a pickle file with the background distogram for each crop.
It also contains an `ensemble` directory with the ensembled background
@@ -170,6 +170,27 @@ When running `run_eval.sh` the output has the following directory structure:
**This is the final distogram that was used in the subsequent AlphaFold
folding pipeline in CASP13.**
### Distogram output format
The distogram is a Python pickle file with a dictionary containing the following
fields:
* `min_range`: The minimum range in Angstroms to consider in distograms.
* `max_range`: The range in Angstroms to consider in distograms, see
`num_bins` below for clarification. The upper end of the distogram is
`min_range + max_range`.
* `num_bins`: The number of bins in the distance histogram being predicted. We
divide the interval from `min_range` to `min_range + max_range` into this
many bins. The distograms were trained so that distances lower than
`min_range` were counted in the lowest bin and distances higher than
`min_range + max_range` were added to the final bin. The `num_bins - 1`
boundaries between bins are thus `np.linspace(0, max_range, num_bins + 1,
endpoint=True)[1:-1] + min_range`.
* `sequence`: The target sequence of amino acids of length `L`.
* `target`: The name of the target.
* `domain`: The name of the target including the domain name.
* `probs`: The distogram as a Numpy array of shape `[L, L, num_bins]`.
## Data splits
We used a version of [PDB](https://www.rcsb.org/) downloaded on 2018-03-15. The