Update curated README documentation: data/embeddings/rnafm_full_transcript/README.md

data/embeddings/rnafm_full_transcript/README.md

@@ -1,69 +1,106 @@
-# rnafm_full_transcript_v1_1
+# Embedding name: RNA-FM-full-transcript
 
-Embedding ID: `rnafm_full_transcript`
-
-Former processing ID: `rnafm_full_transcript_v1_1`
+- Modality: RNA/mRNA sequence / full mature transcript language-model embedding
+- Algorithm: Transformer RNA language model
+- Embedding source URL: Local generation from Ensembl release 114 GRCh38 mature RNA transcript sequences and master_gene_table.csv
+- Original model/code URL: https://github.com/ml4bio/RNA-FM
 
 ## Public files
 
 - `embeddings.npz`: compressed NumPy archive containing the embedding matrix under key `embeddings`.
 - `genes.tsv`: row metadata table. Row order matches the embedding matrix.
 - `metadata.json`: machine-readable provenance and processing metadata.
-- `README.md`: this per-embedding documentation file.
 
 ## Matrix
 
 - Shape: `19976 genes × 640 dimensions`
 - Dtype: `float32`
-- NPZ array key: `embeddings`
-
-The row order is authoritative:
-
-```text
-embeddings.npz['embeddings'][i, :]  corresponds to  genes.tsv row i
-```
 
-## Loading example
 
-```python
-import numpy as np
-import pandas as pd
-
-with np.load('embeddings.npz') as z:
-    X = z['embeddings']
-
-genes = pd.read_csv('genes.tsv', sep='\t')
-assert X.shape[0] == len(genes)
-```
 
 ## genes.tsv columns
 
 | Column | Non-empty values | Unique values | Example values | Meaning |
 |---|---:|---:|---|---|
 | `ensembl_gene_id` | 19976 | 19976 | ENSG00000000003<br>ENSG00000000005<br>ENSG00000000419<br>ENSG00000000457 | Ensembl gene identifier; main stable identifier used to align genes across embeddings. |
-| `rnafm_sequence_length` | 19976 | 7597 | 3768<br>1205<br>1054<br>6308 | TODO: define this source-specific column during manual curation. |
+| `rnafm_sequence_length` | 19976 | 7597 | 3768<br>1205<br>1054<br>6308 | Length in nucleotides of the mature raw RNA transcript sequence used as RNA-FM input for this gene. |
 | `num_chunks` | 19976 | 37 | 5<br>2<br>8<br>3 | Number of chunks/windows used when the input was too long. |
 | `transcript_id` | 19976 | 19976 | ENST00000373020<br>ENST00000373031<br>ENST00000371588<br>ENST00000367771 | Transcript identifier used for sequence-based processing. |
 
-## Basic metadata
 
-| Field | Value |
-|---|---|
-| `status` | processed_qc_passed |
-| `embedding_name` | rnafm_full_transcript_v1_1 |
-| `model_checkpoint` | /local/home/dtabares/data/raw_embeddings/rnafm_full_transcript_v1_1/hf_model/RNA-FM_pretrained.pth |
-| `pooling_strategy` | Final layer 12 mean token pooling over real RNA tokens only; BOS/EOS excluded; long transcripts split into chunks and chunk means length-weighted |
 
 ## Detailed processing notes
 
-TODO: manually paste and curate the processing explanation for this embedding from the central project README.
+### Source and interpretation
+
+This embedding is a gene-level mature RNA transcript representation derived from RNA-FM. It was generated locally from the mature transcript sequence universe prepared from Ensembl release 114 GRCh38 cDNA sequences and the canonical transcript IDs in master_gene_table.csv.
+
+The model used was RNA-FM / `rna_fm_t12` with the official pretrained checkpoint `RNA-FM_pretrained.pth`. For each matched gene, the mature transcript sequence was represented as raw RNA sequence. No Helix-specific `E` codon-start markers were inserted. RNA-FM final layer 12 token representations were extracted, BOS/EOS tokens were excluded, token embeddings were mean-pooled within each chunk, and long transcripts were combined by sequence-length weighted mean pooling across chunks.
+
+This embedding should therefore be interpreted as a full mature transcript RNA language-model representation. It differs from Helix-mRNA because it uses raw RNA sequence without CDS-aware `E` markers, and it differs from CDS-only DNA embeddings because it includes UTR sequence from the mature transcript.
+
+### Provenance fields
+
+    source_name: RNA-FM full mature transcript
+    original_model_or_method: RNA-FM / rna_fm_t12 RNA language model
+    input_sequence_type: mature RNA full transcript
+    input_sequence_source: Ensembl release 114 GRCh38 cDNA-derived mature RNA sequences and master_gene_table.csv canonical transcript IDs
+    genome_build: GRCh38
+    sequence_reference: Ensembl release 114
+    model_checkpoint: RNA-FM_pretrained.pth
+    model_checkpoint_sha256: 5b5d7d87b37c291ef42c140ef9edf7aea29f255fa2a4fd435f776c52e93d5e99
+    model_code_url: https://github.com/ml4bio/RNA-FM
+    model_interface: fm.pretrained.rna_fm_t12()
+    model_output_dimension: 640
+    final_layer_used: 12
+    chunk_len: 900
+    min_chunk_len: 0
+    batch_size: 1
+    pooling_strategy: mean pooling over final layer 12 token embeddings, excluding BOS/EOS tokens, with sequence-length weighted mean across chunks
+    training_or_finetuning: none
+
+### Sequence and transcript decisions
+
+The source gene set came from master_gene_table.csv. Canonical transcript IDs from the master table were used to select one mature transcript sequence per gene from the Ensembl release 114 GRCh38 cDNA FASTA.
+
+RNA-FM reused the raw mature RNA sequence universe prepared during the Helix-mRNA workflow. However, it used the raw RNA FASTA without Helix `E` codon-start markers. This decision prevents Helix-specific input formatting from contaminating the RNA-FM representation.
+
+Genes without a matched mature transcript sequence, without a matched CDS sequence from the shared preparation workflow, or where sequence preparation failed were excluded from this embedding.
+
+### Processing workflow
+
+For each gene in the mature RNA transcript table:
+
+    1. Read the canonical transcript ID from master_gene_table.csv.
+    2. Reuse the mature transcript sequence table prepared from Ensembl release 114 GRCh38 cDNA.
+    3. Convert mature cDNA-derived sequence to raw RNA sequence.
+    4. Use the raw RNA sequence without Helix E markers.
+    5. Load RNA-FM / rna_fm_t12 from the local checkpoint cache.
+    6. Split long transcript sequences into 900 nt chunks.
+    7. Run RNA-FM with batch_size=1.
+    8. Extract final layer 12 token representations.
+    9. Exclude BOS/EOS tokens from pooling.
+    10. Mean-pool token embeddings within each chunk.
+    11. Combine chunk vectors with sequence-length weighted mean pooling.
+    12. Save the final matrix as float32.
+
+### Important implementation decisions
+
+The standard RNA-FM loader attempted to use an external CUHK checkpoint URL that could return 403. The final workflow copied the HuggingFace snapshot checkpoint into the torch hub checkpoint cache so `fm.pretrained.rna_fm_t12()` could load the official checkpoint locally and reproducibly.
+
+The final run used `chunk_len=900` and `min_chunk_len=0`. An earlier test with `min_chunk_len=200` could merge a short final chunk into the previous chunk and exceed RNA-FM's effective position limit. Setting `min_chunk_len=0` kept every chunk safely within the tested token length.
+
+No model training or fine-tuning was performed. The final matrix was generated only by local inference from the official pretrained checkpoint.
 
-Please include, when relevant:
+### Summary of final mapping:
 
-- original source/model/checkpoint;
-- whether the embedding was downloaded or generated locally;
-- input data used;
-- identifier mapping and filtering decisions;
-- pooling, aggregation, PCA, or normalization method;
-- coverage and important caveats;
-- license or redistribution notes.
+    Source identifiers / mature transcript sequences: 19,976
+    Dimensions: 640
+    Rows generated before duplicate collapse: 19,976
+    Missing/failed sequence genes: 121
+    Unmapped source rows: 0
+    Ambiguous source rows: 0
+    Final mapped genes: 19,976
+    Master table rows: 20,097
+    Master coverage: 99.398%
+    Duplicate final mappings averaged: 0