Code for "Within-host dynamics and risk factors for persistent SARS-CoV-2 infections"
Link to paper: To be added
The presented code aims to reproduce the analyses from "Within-host dynamics and risk factors for persistent SARS-CoV-2 infections". In brief, the goal of the code is to identify persistent infections, identify risk factors for persistent infections, analyze associated mutational patterns, and link health conditions to accelerated selective genetic changes in the virus.
case_control_code: Code used for preparing data and running the case control study.defining_snp_thresholds: Contains code to identify the false-positive rates at different rare SNP thresholds.figures: Contains code that leads to the three main figures in the article.identifying_persistent_infections: Code used to identify persistent infections from the full set of sequences.identifying_substitutions_and_mutations: Code used to identify the placement of mutations and non-synonymous changes, as well as analyzing the associaiton between different risk factors and diagnoses with the rate of (non)synonymous change.rebounding: Code to analysze the occurrence fo rebounding among persitent infections.recurrent_mutations: Code to identify independently-occurring and recurrent mutations among persistent infections.
All code is numbered in the intended order of use.
Due to the sensitive nature of the data, we cannot provide individual-level metadata or further metadata for the sequences.
FASTA files can be found here: X. Note that all sequences are de-identified due to privacy reasons.
R (4.2.3), Python (3.10.10), brms (2.20.3), Guppy, Medaka, iVar (1.4.3), BCFtools (1.18), VADR, Trim Galore (0.6.10).
- Mark Khurana (mark.khurana@sund.ku.dk)
- Alexandros Katsiferis (alexandros.katsiferis@sund.ku.dk)
- Neil Scheidwasser (neil.clow@sund.ku.dk)
Apache 2.0 License
To be added.