This repository analyzes the mutational antigenic profiling data for a study of antibodies against HIV.

The citation for the final published study is Dingens et al (2018).

The mutational antigenic profiling experiments were performed by Adam Dingens in the Bloom lab and Overbaugh lab in the summer/autumn of 2017.

Briefly, we used mutational antigenic profiling to comprehensively map escape from N123-VRC34.01, 2712-vFP16.02, and 2716-vFP20.01 (abbreviated VRC34, FP16-02, and FP20-01) using BG505.T332N mutant Env virus libraries. The generation and characterization of the BG505 mutant virus libraires is described in detail in Haddox, Dingens et al. eLife 2018. The basic mutational antigenic profiling approach for HIV is described in Dingens et al. Cell Host & Microbe 2017.

The antibodies used here are described in Xu et al, bioRxiv, DOI 10.1101/306282.

Here we use dms_tools2 to analyze the data. Specifically, the Jupyter notebook analysis_notebook.ipynb does the complete analysis of the mutational antigenic profiling data. It downloads the deep sequencing data from the Sequence Read Archive, processes this data, and then analyzes the selection in the context of each antibody.

The general strategy for barcoded subamplicon Illumina sequencing approach is described here, and the computation of differential selection is described here.

The mutational antigenic profiling analysis is performed by the Jupyter notebook analysis_notebook.ipynb.

All the input data needed to run analysis_notebook.ipynb) are in the ./data/. These files are described in the iPython notebok when used.

All results are placed in a created directory named ./results/.