ASV calling from raw 16S reads in FASTQ format.
1. asv_16s.R
- Put raw files in the directory
./reads_trimmed/, named like*_16S_R1.fq.gzand*_16S_R2.fq.gzfor the forward and reverse reads. - Execute script like
Rscript asv_16s.R. - Output files are:
asv_16s.csv, containing the raw ASVs, taxonomy, and counts per sample.asv_16s_statistics.csv, containing read filtering statistics.
- Execute after running asv_16s.R, as it uses
asv_16s.csvas an input file. - Execute script like
Rscript asv_16s.R. - 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).csvand(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
- Execute after running process_asv.R, as it uses
asv_taxonomy.rdsand an ASV table as an input file. - Also uses an
sl23_control.yamlR/qtl2 control file. Is currently set up to use the supplied SL2.40 SNP map. - Execute script like
Rscript asv_qtl.R INPUT_ASV_TABLE [RQTL_CONTROL_FILE]. - Output files are:
*_lod.csv, containing the LOD scores of each supplied ASV.*_peaks.csv, peaks identified using a cut-off score ofLOD >= 2.5*_lod.pdf, visualisation of LOD scores across the genome.