SRA Quanto

SRA Quanto is a project to calculate quantitative information of high-throughput sequencing data archived in sequence read archive (SRA) to enhance reuse of the publc sequencing data. This repository contains the code to calculate statistics using FastQC, summarize using biogem bio-fastqc, and visualize by R.

Summarized data

Calculated and summarized quality statistics is available at Figshare in tabular format including submitter's metadata such as sequencing methods and sample organisms. Statistics for each sequencing run is available in RDF format, and NBDC RDF Portal is providing summary of RDF data, SPARQL endpoint, and example queries here.

Requirement for data calculation

• Ruby (2.3.0)
  • bundler
• Univa Grid Engine (8.4.0) for parallelized FastQC execution
• R (ver. 3.2.3) and ggplot2 (ver. 2.1.0) for visualization

Usage

Setup rubygems

$ git clone https://github.com/inutano/sra-quanto
$ cd sra-quanto
$ bundle install --path=vendor/bundle
# show rake tasks
$ bundle exe rake -T
rake quanto:available  # option: workdir, fastqc_dir, sra_metadata_dir, biosample_metadata_dir
rake quanto:exec       # option: workdir, fastqc_dir
rake quanto:plot       # option: data (default: tables/summary/quanto.annotated.tsv)
rake quanto:summarize  # option: workdir, sra_metadata_dir, summary_outdir, overwrite, format

Calculate statistics

# Create list of available sequencing runs
$ bundle exe rake quanto:available workdir=/path/to/working_directory fastqc_dir=/path/to/dir_to_save_fastqc_result
# Start calculation, it may take very long time.
$ bundle exe rake quanto:execute
# Summarize in tsv
$ bundle exe rake quanto:summarize workdir=/path/to/working_directory format=tsv

Visualization

$ bundle exe rake quanto:plot data=/path/to/summarized_tsv

Citation

Paper

• Ohta, T., Nakazato, T., & Bono, H. (2017). Calculating quality of public high-throughput sequencing data to obtain suitable subset for reanalysis from the Sequence Read Archive. GigaScience.
  • https://doi.org/10.1093/gigascience/gix029

Data

• Figshare
  • Ohta, Tazro A summary of sequencing quality of data archived in Sequence Read Archive Quality information of sequencing data archived in Sequence Read Archive calculated by FastQC Sequencing quality 2017-01-05 http://dx.doi.org/10.6084/m9.figshare.4498907.v2
• GigaDB
  • Ohta, T; Nakazato, T; Bono, H (2017): Supporting data for "Calculating quality of public high-throughput sequencing data to obtain suitable subset for reanalysis from the Sequence Read Archive" GigaScience Database. http://dx.doi.org/10.5524/100304

Copyright

Copyright (c) 2015 Tazro Inutano Ohta. See LICENSE.txt for further details.