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config.yaml
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# =============================================================================
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# config.yaml — Genome Dataset Pre-processing Configuration
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# =============================================================================
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# Root directory containing all species folders.
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# Expected layout: {data_root}/{species}/{assembly}/{species}_{annotation}_genomic.fna
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# {species}_{annotation}.gff3
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data_root: /share/kuleshov/emm392/mammal_genomes/
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# Where to write the final HuggingFace DatasetDict (saved with save_to_disk).
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output_dir: "./output"
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# Where to cache processed annotation files
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cache_dir: ".cache"
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# ---------------------------------------------------------------------------
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# Sliding-window parameters
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# ---------------------------------------------------------------------------
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chunk_size: 12_000 # Length of each sequence chunk in base pairs
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stride: 12_000 # Step size between consecutive chunks (256 = 50% overlap for chunk of 512)
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# Set stride == chunk_size for non-overlapping chunks
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# ---------------------------------------------------------------------------
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# CDS flanking regions
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# ---------------------------------------------------------------------------
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# Extra bases to include BEFORE the CDS start (upstream, on the feature strand)
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flank_upstream_bp: 10_000
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# Extra bases to include AFTER the CDS end (downstream, on the feature strand)
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flank_downstream_bp: 10_000
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# max percentage of N's allowed in a given sequence
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max_n_perc: 0.25
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# ---------------------------------------------------------------------------
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# Species selection & validation split
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# ---------------------------------------------------------------------------
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# Only species listed here are processed — everything else in data_root is
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# ignored. Each entry requires:
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# - name : matches the directory name exactly under data_root
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# - val_chromosome: contig/chromosome ID to hold out for validation.
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# Must match the FASTA header exactly (first word after ">").
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# Tip: grep "^>" your_file.fna | head to list available IDs.
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#
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# train species — ALL chromosomes go to train except val_chromosome
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# validation species — same rule applies; val_chromosome goes to validation,
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# remaining chromosomes go to train
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#
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# If you want a species to contribute ONLY to train (no val chrom), set
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# val_chromosome to null.
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species:
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train:
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- name: "Homo_sapiens"
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val_chromosome: "NC_000008.11" # hold out chr8
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- name: "Mus_musculus"
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val_chromosome: "NC_000070.7" # hold out chr3
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- name: "Pan_troglodytes"
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val_chromosome: "NC_072404.2" # hold out chr6
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# Add more training species here:
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# - name: "rattus_norvegicus"
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# val_chromosome: "NC_005100.4"
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validation:
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# Species listed here follow the same rule: val_chromosome → validation,
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# all other chromosomes → train. Use this section if you want to keep
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# certain species exclusively (or primarily) for evaluation bookkeeping.
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# Most users will leave this empty and rely on val_chromosome above.
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#
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# - name: "danio_rerio"
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# val_chromosome: "NC_007112.7"
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# ---------------------------------------------------------------------------
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# Misc
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# ---------------------------------------------------------------------------
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shuffle: False # Shuffle the training set after building
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seed: 42
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