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Related Experiment Video

Updated: Feb 8, 2026

Automated Gel Size Selection to Improve the Quality of Next-generation Sequencing Libraries Prepared from Environmental Water Samples

Automated Gel Size Selection to Improve the Quality of Next-generation Sequencing Libraries Prepared from Environmental Water Samples

Published on: April 17, 2015

Crumble: reference free lossy compression of sequence quality values.

James K Bonfield¹, Shane A McCarthy^1,2, Richard Durbin^1,2

¹DNA Pipelines, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.

Bioinformatics (Oxford, England)

|July 12, 2018

Summary

This summary is machine-generated.

A new tool, Crumble, significantly reduces the size of Next-Generation Sequencing (NGS) CRAM files by compressing quality scores. This method achieves substantial file size reduction without compromising variant calling accuracy.

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Area of Science:

Genomics
Bioinformatics
Data Compression

Background:

Next-Generation Sequencing (NGS) generates large CRAM files, with a significant portion of the storage occupied by per-base quality values.
Many of these quality values are redundant for variant calling, presenting an opportunity for data compression and storage optimization.

Purpose of the Study:

To develop and evaluate a method for reducing the storage space of CRAM files by selectively compressing quality score data.
To assess the impact of this compression on variant calling accuracy.

Main Methods:

Implementation of an open-source tool named Crumble for compressing quality data within CRAM files.
Testing the tool on the Syndip dataset to measure the reduction in quality storage and overall file size.
Evaluating variant calling accuracy after data compression.

Main Results:

Achieved a 17-fold reduction in the quality storage portion of CRAM files on the Syndip test set.
Observed overall CRAM file size reductions ranging from 2.2 to 7.4 fold, dependent on the file's non-quality content.
Maintained variant calling accuracy despite significant data compression.

Conclusions:

Crumble offers an effective strategy for reducing CRAM file sizes by optimizing the storage of quality values.
The tool provides substantial space savings without sacrificing the integrity of variant calling results.
This approach has the potential to alleviate storage burdens in large-scale genomics projects.