Amplicon QTL

ASV calling from raw 16S reads in FASTQ format.

1. asv_16s.R

1. Put raw files in the directory ./reads_trimmed/, named like *_16S_R1.fq.gz and *_16S_R2.fq.gz for the forward and reverse reads.
2. Execute script like Rscript asv_16s.R.
3. Output files are:
   • asv_16s.csv, containing the raw ASVs, taxonomy, and counts per sample.
   • asv_16s_statistics.csv, containing read filtering statistics.

2. process_asv.R

1. Execute after running asv_16s.R, as it uses asv_16s.csv as an input file.
2. Execute script like Rscript asv_16s.R.
3. Output files are:
   • Figure showing separation between the core, flexible, and stochastic microbiome.
   • asv_taxonomy.rds, an R data file containing renumbered ASV-IDs and taxonomy.
   • TableS1_asv_raw.csv, raw counts ASV table with Chloroplast and non-bacteria taxa removed. ASV-IDs were renumbered.
   • TableS2_asv_css.csv, CSS-normalised and fitZIG filtered ASVs.
   • TableS3_asv_taxonomy.csv, ASV-IDs and related taxonomical lineages.
   • TableS4_asv_css_statistics_rhizosphere.csv, statistics calculated on TableS2 counts.
   • (yellow|pink)_(core|flexible).csv and (yellow|pink)_(core|flexible)_randomised.csv, containing ASV counts from a subset of samples and one where the order of counts in each column are randomised.

3. asv_qtl.R

1. Execute after running process_asv.R, as it uses asv_taxonomy.rds and an ASV table as an input file.
2. Also uses an sl23_control.yaml R/qtl2 control file. Is currently set up to use the supplied SL2.40 SNP map.
3. Execute script like Rscript asv_qtl.R INPUT_ASV_TABLE [RQTL_CONTROL_FILE].
4. Output files are:
   • *_lod.csv, containing the LOD scores of each supplied ASV.
   • *_peaks.csv, peaks identified using a cut-off score of LOD >= 2.5
   • *_lod.pdf, visualisation of LOD scores across the genome.