CM_16S_cross-sectionalF245

Data processing and analysis of cross-sectional microbiome

Monzó et al., Dietary restriction mitigates the age-associated decline in mouse B cell receptor repertoire diversity, Cell Reports (2023), https://doi.org/10.1016/j.celrep.2023.112722

Running cutadapt file:

slurm cmd_fastq_trimm.sh

Running general dada2 pipeline

It calls to R script "dada2_F245.Rmd".
This script runs the dada2 pipeline until taxa annotation, generating intermediate files for later analysis, QC and processing comparisons.

Rscript dada2_F245.Rmd

Running general QC

jupyter notebook depth_plotting_F2.ipynb

Generating alpha and beta diversity tables for analysis

Script "dada2_F1_abphylo.R" calculates basic tables for analysis of alpha and beta diversity

Rscript dada2_F2_abphylo.R --path ~/workspace/16S_final/CM_16S_cross-sectionalF245/ --nochim ../analysis/seqtab_merge3/CLEAN_merged_seqtabNochim_20210215.rds --taxa ../analysis/seqtab_merge3/CLEAN_taxonomy_merged_20210215.rds --metadata ../metadata/metadata_ready2.csv --count_tab ../analysis/seqtab_merge3/mergedQC/CLEAN_ASVs_counts_merged_20210215.tsv

Plotting and general analysis of alpha and beta diversity

Alpha and beta diversity plotting and basic per-timepoint stats are run as ipythons, as it makes it easier to keep track of the plots as they are being generated.

jupyter notebook alpha_diversity_F2.ipynb  
jupyter notebook beta_diversity_F2.ipynb

Running DESeq2 in each timepoint for comparisons

Rscript deseq_timepoints.Rmd

Comparing numbers of differentially abundant ASVs

jupyter notebook Num_DiffAb_ASVs.ipynb