Work

Vector autoregression framework applied in "Innate immune responsiveness predicts enhanced cellular immunity and symptomatic disease after controlled human influenza infection"

Year: 2026

Type: article

Abstract: Scripts for modeling conditional temporal dependencies among immune mediators during immune responses to H3N2 viral challenge. Data will be made available upon request to the corresponding author. Procedure 1. run `0_data_preprocess.R` to prepare data for downstream analyses2. run `1_fit_groupVAR.R` to infer the conditional temporal dependency among immune mediators using a group-level vector auto-regression (VAR) framework3. run `2_visual_network.R` to visualize coefficient matrices learned from the VAR framework and top edges4. run `3_in_vitro_analysis.R` to link the acute response measured *in vivo* to differential response to *in vitro* stimulation before and after H3N2 challenge

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.19698805

Authors: Huang, Ao, Papargyris, Loukas, Xu, Jiayun, Tsang, John S., Chiu, Christopher

Institutions: Yale University, University College London

Language: English

Topic: Influenza Virus Research Studies

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W7155220269

FWCI: 4.662

Cites:

Cited by: 1

Related to: 10