For a fully reproducible analysis starting from raw sequencing files R script have to be executed in numerical order (starting with a "\d_"; e.g. 0_, 1_, ..), scripts prefixed with X_ are currently not used.

We follow one simple convention for executing the scripts: Your R session should run in the repository folder directly (in the folder that you cloned, not in 'input_data/', 'intermediate_data' or 'R/').

At the beginning of each script we test for the availability of the required data (in a potentially interactive R session) and either recompute it executing ('sourcing') the previous scripts (recompute = TRUE) or read it from 'intermediate_data'.

For coauthors, here is how this was migrated from the Dropbox folder and how the data flows through the pipeline and analyses:

Dropbox/Project_Canid_Metabarcoding/5_scripts/Extract_EnvirCovariates_BE_BB_20200903.Rmd (by Cedric Scherer)

-> 0_Extract_Einvir_Covariates.R

The input raw (layer) files this is based on are in: input_data/tifs/*.tif

This unlike data for previous (pre-mid-2021) versions of the manuscript now allows us analysis of landscape variables for both Berlin and Brandenburg.

The script reads data on the sampled foxes from "input_data/Fox_data.csv', appends environmental variables (x, y, v) for each fox and writes them (together with the 'basic data') to 'intermediate_data/Fox_data_envir.RDS'.

We (Victor Jarquin-Diaz and Emanuel Heitlinger) process the raw sequencing data in 1_Fox_general_MA.R based on matching of the primer sequences in 'input_data/primer_file_foxes.csv'. We are using the MultiAmplicon wrapper of the dada2 package to produce amplified sequence variant (ASV) abundances for each fox.

The sequencing data is most easiely available on the compute server of the Heitlinger group ([email protected]). The script could alternatively be run on the sequencing data after download from NCBI-SRA/ or ENA (ADD LINK HERE) (for full reproducibilty; sequencing data is to large for storage on github).

The script also adds the environmenal covariates (from intermediate_data/Fox_data_envir.RDS produced in 0_Extract_Einvir_Covariates.R) to the central "phyloseq" object of the pipeline. The environmental covariates are stored as "sample_data" in this object.

The script stores intermediate data on our server and is in the present not executable anywhere else. You can continue with it's output object.

We store output as a phyloseq object in 'intermediate_data/PhyloSeqCombi.Rds'

At this point we have all data to perform diversity analysis in 'R/2_iNEXT_fox.R'

We look at three differen masures for alpha (species [q=0], Shannon diversity [q=1] and Simpson diversity [q=2]), beta (jaccard centroid distances) and gamma diversity (rarefied diversity by fox individual).

Caro Scholz compiled helminth traits in Dropbox/Project_Canid_Metabarcoding/6_processed_data/traits_grouped.RDS

-> input_data/helminth_traits.csv

This manual input data can be edited directly. It still contains many NAs we might want to add missing information as we progress with analysis/publication.

AT THIS POINT WE HAVE ALL THE DATA collected and processed (in the phloseq object and the traits table) and the remaining two scripts are only analysing this.

JSDM_parasites_helminths_AP_20200828.Rmd (by Aimara Planillo).

-> 3_JSDM_helminths.R

Runs the model, the model check and shows the results

Dropbox/Project_Canid_Metabarcoding/5_scripts/PCA_CS_20200903_1946

-> 4_CommunityComposition.R