5PSeq Explorer Data

The data input for 5PSeq Explorer is provided as a data freeze hosted on the Swedish National Data Service (DOI pending). You may run the Standard Web version, which accesses data on the fly hosted on our laboratory server. Alternatively, the Local (plug-and-play) 5PSeq Explorer can be used with the data freeze or your own 5PSeq data, processed using the FivePSeq pipeline.

This document provides essential information for dataset reuse.

Data Freeze Contents

This data freeze contains raw count files of 5PSeq data in tabular format. A metadata and RNA composition file are included as Excel files.

Dataset Organization

This data freeze accompanies, and is compatible with, 5PSeq Explorer.

The data freeze contains:

  • Metadata and RNA composition Excel files

  • 5PSeq raw counts (.txt) for yeast and bacteria

Folder Structure

Yeast (yeast/)

  • Contains 315 ‘Sample’ subdirectories (e.g., SM_AA_t30_rep1)

  • Each sample subdirectory contains a protein_coding/ folder with 30 files of raw processed counts

Bacteria (bacteria/)

  • Contains 384 ‘Sample’ subdirectories (e.g., acac_g30_fecul-B_5fu-t05_r1_fc_r_v13_S11_R1)

  • Each sample subdirectory contains a protein_coding/ folder with the same 30 files

Example structure:

5PSeq_processed_data/
├── yeast/
│   └── CSM_AA_t30_rep1/
│       └── protein_coding/
│           ├── amino_acid_pauses.txt
│           ├── canonical_transcript_index.txt
│           ├── codon_pauses.txt
│           ├── count_distribution.txt
│           ├── counts_START.txt
│           ├── counts_TERM.txt
│           ├── data_summary.txt
│           ├── dicodon_pauses.txt
│           ├── dipeptide_pauses.txt
│           ├── fft_signals_start.txt
│           ├── fft_signals_term.txt
│           ├── fft_stats.txt
│           ├── frame_counts_START.txt
│           ├── frame_counts_TERM.txt
│           ├── frame_stats.txt
│           ├── meta_count_peaks_START.txt
│           ├── meta_count_peaks_TERM.txt
│           ├── meta_counts_START.txt
│           ├── meta_counts_TERM.txt
│           ├── outlier_lower.txt
│           ├── outliers_df.txt
│           ├── start_codon_dict.txt
│           ├── term_codon_dict.txt
│           ├── transcript_assembly.txt
│           ├── transcript_descriptors.txt
│           ├── transcript_fft.txt
│           ├── transcript_frame_prefs.txt
│           ├── tricodon_pauses.txt
│           └── tripeptide_pauses.txt
└── bacteria/
    └── acac_g30_fecul-B_5fu-t05_r1_fc_r_v13_S11_R1/
        └── protein_coding/
            ├── amino_acid_pauses.txt
            ├── canonical_transcript_index.txt
            ├── codon_pauses.txt
            ├── count_distribution.txt
            ├── counts_START.txt
            ├── counts_TERM.txt
            ├── data_summary.txt
            ├── dicodon_pauses.txt
            ├── dipeptide_pauses.txt
            ├── fft_signals_start.txt
            ├── fft_signals_term.txt
            ├── fft_stats.txt
            ├── frame_counts_START.txt
            ├── frame_counts_TERM.txt
            ├── frame_stats.txt
            ├── meta_count_peaks_START.txt
            ├── meta_count_peaks_TERM.txt
            ├── meta_counts_START.txt
            ├── meta_counts_TERM.txt
            ├── outlier_lower.txt
            ├── outliers_df.txt
            ├── start_codon_dict.txt
            ├── term_codon_dict.txt
            ├── transcript_assembly.txt
            ├── transcript_descriptors.txt
            ├── transcript_fft.txt
            ├── transcript_frame_prefs.txt
            ├── tricodon_pauses.txt
            └── tripeptide_pauses.txt
metadata_v2.xls  
rna_stats_v2.xls

The metadata.xls file contains a Sample column that matches the names of each ‘Sample’ subdirectory. Additional sample information (SRA/GEO ID, PMID, publication record) is included.

Datafile Descriptions

Each ‘Sample’ subdirectory contains 30 files of raw counts and statistics produced using the FivePSeq pipeline (PMID: 33575643).

For detailed information about the contents of each file, please refer to the FivePSeq documentation.

Reference Information

  1. Pelechano, V., Wei, W., & Steinmetz, L. M. (2015). Widespread Co-translational RNA Decay Reveals Ribosome Dynamics. Cell, 161(6), 1400–1412.

  2. Nersisyan, L., Ropat, M., & Pelechano, V. (2020). Improved computational analysis of ribosome dynamics from 5’P degradome data using fivepseq. NAR Genomics and Bioinformatics, 2(4), lqaa099.