notebooks

Notes:

• This directory contains Jupyter and Rstudio notebooks used in the publication.

• If you are interested in analysing wastewater samples, you should refer to repository COWWID.

  It contains a detailed description of the latest up-to-date procedure used to generate the plots visible on the dashboard Surveillance of SARS-CoV-2 genomic variants in wastewater and displayed on CoV-Spectrum.

Signature_mutations_in_patient_samples.ipynb

Notebook to assess the prevalence of signature mutation defining the lineages B.1.1.7 and 501.V2 in all 5758 non-B.1.1.7 and non-501.V2 consensus sequences from clinical samples collected in Switzerland before December 24.

snv_count_wastewater3.ipynb

ShoRAH normally calls SNV by combining the results of three overlapping local windows. Given the nature of our sample, we are lucky if a single windows can cover our mutations. So this Notebook instead calls mutation based on the local haplotype on single ShoRAH windows. We lose some confidence by only using a single windows per SVN, but because variants of concern are detected based on multiple mutations simultaneously.

mut-table.ipynb

Combines a list of SNV from the precedent Notebook with a reads counts, so we can also estimate mutation frequency.

ww_smoothing.ipynb

Produce smoothed curves of B.1.1.7 frequency for wastewater and clinical samples.

ww_modelling.ipynb

Produce fitted logistic growth curves of B.1.1.7 frequency for wastewater and clinical samples. Produce online estimates of fitness advantage.

ww_delta.ipynb

Produce plots of Delta prevalence in clinical samples and cojac detections in wastewater.