sup45-ts_readthrough

Analysis pipeline, codes, and processed data for Mangkalaphiban et al., PLoS Genetics, 2021
DOI: https://doi.org/10.1371/journal.pgen.1009538
Preprint: https://doi.org/10.1101/2020.12.15.422930

Raw sequencing data generated in this study are deposited and available at Gene Expression Omnibus (GEO) under accession number GSE162780.
Numerical data underlying the plots and the R codes used to generate them are in the folder Figures

Analysis pipeline

1. Sequence alignment
   • Input:
     • Raw sequencing data used in this study and their associated SRR numbers are listed in Raw_data_SRR.csv
   • Transcriptome used for sequence alignment is available at https://github.com/Jacobson-Lab/yeast_transcriptome_v5
   • Output:
     • Transcript abundance files generated by RSEM are in the folder RSEM_results
     • bam files
2. Calculate read P-site using riboWaltz
   • scripts/read_p-site_riboWaltz.Rmd
   • riboWaltz: https://github.com/LabTranslationalArchitectomics/riboWaltz
   • Input:
     • bam files from step 1
     • annotation file (RData/genedf_riboWaltz_v5_CDS_corrected.txt)
     • files containing p-site offset for each read length (RData/(sample)_psite_offset_adj.txt)
   • Output:
     • RData/(dataset)/(sample)_reads_psite_list.txt.gz contains the following reads information: length of read, 5' & 3' ends + position of the read's P-site relative to the annotation provided in the annotation file. Distance from read's P-site to start and stop codons are calculated. The mRNA region (5'-UTR, CDS, or 3'-UTR) the P-site falls in is assigned.
3. Read count by mRNA region and readthrough efficiency calculation
   • scripts/rt_efficiency.R
   • Input:
     • reads_psite_list from step 2
     • RData/next_inframe_stop.txt
   • Output:
     • RData/rte_f0_cds_m3=33.Rdata
4. Random forest analyses
   • scripts/random_forest.Rmd
   • Input:
     • mRNA features (RData/feature_file.csv)
     • Readthrough efficiency calculated for each gene from step 3 (RData/rte_f0_cds_m3=33.Rdata)
   • Output:
     • Model accuracy
     • Feature importance