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Genome-wide nucleotide and amino acid sequences.

1. Download fasta files for cdna sequences:

  • Mus_musculus.GRCm39.cdna.all.fa.gz was downloaded from Ensemble
  • Homo_sapiens.GRCh38.cdna.all.fa.gz was downloaded from Ensemble

2. Extract nucleitide sequences from .fa files into dataframes (and saved as .csv files)

  • 00_get_seqs_mouse.ipynb
  • 00_get_seqs_human.ipynb

3. Use lookups with gget to get amino acid sequences using ensembl_ids

  • get_aa_seq_mouse.py
  • get_aa_seq_human.py

4. Merge and clean up the dataframes

  • 03_inspect_aa_seq_human.ipynb
  • 04_inspect_aa_seq.ipynb

The final dataframes are saved as

  • prot_nuc_seqs_mouse.csv
  • prot_nuc_seqs_human.csv

Example row:

gene_symbol ensg_id enst_id nuc_seq_length aa_seq_length nuc_aa_seq_ratio chromosome start end strand nuc_seq aa_seq
Gm20730 ENSMUSG00.. ENSMUST00 359 119.0 3.01 GRCm39:6 430 4305 -1.0 ATGAGGTGC MRCLAEFLR.

Embedding nucleotide sequences with Nucleotide Transformer

We used Nucleotide Transformer models to embed sequences with a maximum length of 5952 nucleotides. Sequences longer than 5952 nucleotides were truncated. Specifically, we used the 500M_human_ref and 500M_multi_species_v2 models for human and mouse respectively.

  • 04_nuc_nt_emb_mouse.ipynb
  • 05_nuc_nt_emb_human.ipynb

Embedding amino-acid sequences with ESM3 and MMIDAS joint clustering

Combining results for analysis and visualization

We performed Leiden clustering for nt-emb and esm3-emb, along with 2d umap projections. Results are merged with those from MMIDAS joint clustering for further visualization.

  • 06_make_df.ipynb
  • 07_static_plots.ipynb
  • 08_dynamic_plots.ipynb
  • 09_enrichr_vignettes.ipynb

Contact:

  • Rohan Gala
  • Yeganeh Marghi

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Notebooks and scripts used for the Nautilex Hackathon

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