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================
This pipeline preprocesses Pfam-A.seed (multiple sequence alignments and
phylogenetic trees from Pfam v36.0) into training inputs for a pairHMM-based
model. The pipeline runs in five stages:
1. Initial cleaning -- filters MSAs: removes short/invalid peptides,
duplicate sequences (within and across families),
and prunes phylogenetic trees to match cleaned MSAs.
2. Split & cherry-pick -- partitions Pfam families into train splits and an
out-of-distribution (OOD) validation set (selected
by alignment width and gap fraction), then extracts
"cherries" (leaf pairs) from each tree.
3. Feature generation -- encodes aligned and unaligned sequences as numpy
arrays, paired with tree and alignment metadata.
4. Count precomputation -- uses JAX to batch-compute substitution, insertion,
deletion, and transition counts needed for pairHMM
inputs (this step can be slow on large datasets).
5. Concatenation & teardown -- concatenates per-part arrays into per-split
.npy files and .tsv metadata, moves all
outputs into DATA/ and intermediates.tar.gz.
Outputs:
--------
After the pipeline completes, two top-level directories are created:
DATA/
*_aligned_mats.npy -- alignments
*_seqs_unaligned.npy -- unaligned sequences
*_AAcounts.npy -- amino acid emission counts
*_AAcounts_subsOnly.npy -- emission counts from substitution columns only
*_subCounts.npy -- substitution counts
*_insCounts.npy -- insertion counts
*_delCounts.npy -- deletion counts
*_transCounts.npy -- M/I/D/S/E transition counts
*_metadata.tsv -- per-sample metadata
*_longest_alignment.txt -- length of the longest alignment in the split
*_longest_seqs.txt -- length of the longest unaligned seq in split
DATA/info/pfams_in_* -- list of Pfam families in each split
intermediates.tar.gz -- intermediate files (cherry folders, removal
logs, duplicate reports) compressed for audit
Requirements:
-------------
Databases / external tools:
- Pfam v36.0 seed file: ftp.ebi.ac.uk/pub/databases/Pfam/releases/Pfam36.0/
- FastTree 2.1.11 (No SSE3 build): used to impute missing phylogenetic trees
Python packages:
- Python 3.9.18
- JAX 0.4.28 -- batch computation of pairHMM transition/emission counts
- Biopython 1.81 -- parsing and pruning phylogenetic trees
Arguement for clean_data.py:
----------------------------
Required:
-pfam_seed_file Path to the Pfam-A.seed file (or example seed file)
-tree_dir Directory containing per-family .tree files
Optional:
-num_splits Number of training splits (default: 10)
-topk1_valid Number of widest Pfam families held out for OOD valid
(default: 3; set to 0 to skip)
-topk2_valid Number of gappiest Pfam families held out for OOD valid
(default: 8; set to 0 to skip)
-rand_key Random seed for split assignment (default: 6)
-metadata_header Header string added to output stats file (default: metadata)
-alphabet_size Amino acid alphabet size (default: 20)
-max_len Maximum sequence length for padding (default: 5000)
-batch_size Batch size for count precomputation (default: 1000)
Quickstart:
-----------
Unzip EXAMPLE_INPUTS.zip, then run:
python clean_data.py \
-pfam_seed_file EXAMPLE_INPUTS/EXAMPLE_Pfam-A.seed \
-tree_dir EXAMPLE_INPUTS/trees/ \
-num_splits 2 \
-topk1_valid 0 \
-topk2_valid 0
The example uses -topk1_valid 0 and -topk2_valid 0 because the example dataset
is too small to hold out families for OOD validation.
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