OAS-wrapper 1.1

Python package to parse Observed antibody sequence data for easy reporting, visualization, annotation and alignment.

OAS_wrapper

A wrapper to parse Observed Antibody Space (OAS) data for better visualization, annotation and comparison of sequence to germline.

Functionalities

The scripts include functionalities to:

1. Provide basic metrics and visualizations of sequences and their annotations

2. Provide original IMGT sequences for V, D and J calls made in OAS data using IMGT reference database

3. Align sequence and germline to highlight regions of mismatches, providing positional information e.g.,

Example Output:
Original Sequence 1: GAGGTGCAGCTGTTGGAGTCTGGGGGAGGCTTAGTACAGCCTGGGGGGTCCCTGAGACTCTCCTGTGTAGCCTCTGGATTCACCTTTAGCAGCTATGCCATGAGCTGGGTCCGCCAGGCTCCAGGGAAGGGGCTGGAGTGGGTCTCAGGTATTAGTGCTAGTGGTGCTAGCACATACTACGCAGACTCCGTGAAGGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAACCCCCAAATACGATGTTTGGAGTGGTTATTATACGTCCAATGCCTTTGATATCTGGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
Original Sequence 2: GAGGTGCAGCTGTTGGAGTCTGGGGGAGGCTTGGTACAGCCTGGGGGGTCCCTGAGACTCTCCTGTGCAGCCTCTGGATTCACCTTTAGCAGCTATGCCATGAGCTGGGTCCGCCAGGCTCCAGGGAAGGGGCTGGAGTGGGTCTCAGCTATTAGTGGTAGTGGTGGTAGCACATACTACGCAGACTCCGTGAAGGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAANNNNNNNNNTACGATTTTTGGAGTGGTTATTATACNNNNNATGCTTTTGATATCTGGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
Aligned and Highlighted Differences:
GAGGTGCAGCTGTTGGAGTCTGGGGGAGGCTTAGTACAGCCTGGGGGGTCCCTGAGACTCTCCTGTGTAGCCTCTGGATTCACCTTTAGCAGCTATGCCATGAGCTGGGTCCGCCAGGCTCCAGGGAAGGGGCTGGAGTGGGTCTCAGGTATTAGTGCTAGTGGTGCTAGCACATACTACGCAGACTCCGTGAAGGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAACCCCCAAATACGATGTTTGGAGTGGTTATTATACGTCCAATGCCTTTGATATCTGGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
GAGGTGCAGCTGTTGGAGTCTGGGGGAGGCTTGGTACAGCCTGGGGGGTCCCTGAGACTCTCCTGTGCAGCCTCTGGATTCACCTTTAGCAGCTATGCCATGAGCTGGGTCCGCCAGGCTCCAGGGAAGGGGCTGGAGTGGGTCTCAGCTATTAGTGGTAGTGGTGGTAGCACATACTACGCAGACTCCGTGAAGGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCCGAGGACACGGCCGTATATTACTGTGCGAAANNNNNNNNNTACGATTTTTGGAGTGGTTATTATACNNNNNATGCTTTTGATATCTGGGGCCAAGGGACAATGGTCACCGTCTCTTCAG
Indices of Differences: [32, 67, 148, 157, 166, 294, 295, 296, 297, 298, 299, 300, 301, 302, 309, 329, 330, 331, 332, 333, 338]
--------------------------------------------------

5. Group data by germline, to infer sequences that originate from germline, including providing information on V, D and J annotations

Example Output:
germline_alignment_heavy    CAGGTGCAGCTGCAGGAGTCGGGCCCAGGACTGGTGAAGCCTTCAC...
number_of_sequences                                                        16
sequence_heavy              GGGAGGGTCCTGCTCACATGGGAAATACTTTCTGAGAGTCCTGGAC...
j_call_heavy                                                         IGHJ4*02
v_call_heavy                                                      IGHV4-31*03
d_call_heavy                                                      IGHD3-10*01

7. Annotate sequence with CDRs and FWRs for easy inference of regions of interest

Example Output:  
'AGCTCTGAGAGAGGAGCCCAGCCCTGGGATTTTCAGGTGTTTTCATTTGGTGATCAGGACTGAACAGAGAGAACTCACCATGGAGTTTGGGCTGAGCTGGCTTTTTCTTGTGGCTATTTTAAAAGGTGTCCAGTGTGAGGTGCAGCTGTTGGAGTCTGGGGGAGGCTTAGTACAGCCTGGGGGGTCCCTGAGA(cdr1 170-193) CTCTCCTGTGTAGCCTCTGGATTCACCTTTAGCAGCTATGCCATGAGCTGGGTCCGCCAG(cdr2 245-253) GCTCCAGGGAAGGGGCTGGAGTGGGTCTCAGGTATTAGTGCTAGTGGTGCTAGCACATACTACGCAGACTCCGTGAAGGGCCGGTTCACCATCTCCAGAGACAATTCCAAGAACACGCTGTATCTGCAAATGAACAGCCTG(cdr3 362-394) AGAGCCGAGGACACGGCCGTATATTACTGTGCGAAAACCCCCAAATACGATGTTTGGAGTGGTTATTATACGTCCAATGCCTTTGATATCTGGGGCCAAGGGACAATGGTCACCGTCTCTTCAGGGAGTGCATCCGCCCCAACCCTTTTCCCCCTCGTCTCCTGTGAGAATTCCCCGTCGGATACGAGCAGCGTG'

Project Organization

├── LICENSE            <- Open-source license if one is chosen
├── README.md          <- The top-level README for developers using this project.
├── data 
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
└── src                <- Source code for use in this project.

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