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IonCRAM: a reference-based compression tool for ion torrent sequence files
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Abstract
Background
Ion Torrent is one of the major next generation sequencing (NGS) technologies and it is frequently used in medical research and diagnosis. The built-in software for the Ion Torrent sequencing machines delivers the sequencing results in the BAM format. In addition to the usual SAM/BAM fields, the Ion Torrent BAM file includes technology-specific
flow signal
data. The flow signals occupy a big portion of the BAM file (about 75% for the human genome). Compressing SAM/BAM into CRAM format significantly reduces the space needed to store the NGS results. However, the tools for generating the CRAM formats are not designed to handle the flow signals. This missing feature has motivated us to develop a new program to improve the compression of the Ion Torrent files for long term archiving.
Results
In this paper, we present IonCRAM, the first reference-based compression tool to compress Ion Torrent BAM files for long term archiving. For the BAM files, IonCRAM could achieve a space saving of about 43%. This space saving is superior to what achieved with the CRAM format by about 8–9%.
Conclusions
Reducing the space consumption of NGS data reduces the cost of storage and data transfer. Therefore, developing efficient compression software for clinical NGS data goes beyond the computational interest; as it ultimately contributes to the overall cost reduction of the clinical test. The space saving achieved by our tool is a practical step in this direction. The tool is open source and available at Code Ocean, github, and
http://ioncram.saudigenomeproject.com
.
Title: IonCRAM: a reference-based compression tool for ion torrent sequence files
Description:
Abstract
Background
Ion Torrent is one of the major next generation sequencing (NGS) technologies and it is frequently used in medical research and diagnosis.
The built-in software for the Ion Torrent sequencing machines delivers the sequencing results in the BAM format.
In addition to the usual SAM/BAM fields, the Ion Torrent BAM file includes technology-specific
flow signal
data.
The flow signals occupy a big portion of the BAM file (about 75% for the human genome).
Compressing SAM/BAM into CRAM format significantly reduces the space needed to store the NGS results.
However, the tools for generating the CRAM formats are not designed to handle the flow signals.
This missing feature has motivated us to develop a new program to improve the compression of the Ion Torrent files for long term archiving.
Results
In this paper, we present IonCRAM, the first reference-based compression tool to compress Ion Torrent BAM files for long term archiving.
For the BAM files, IonCRAM could achieve a space saving of about 43%.
This space saving is superior to what achieved with the CRAM format by about 8–9%.
Conclusions
Reducing the space consumption of NGS data reduces the cost of storage and data transfer.
Therefore, developing efficient compression software for clinical NGS data goes beyond the computational interest; as it ultimately contributes to the overall cost reduction of the clinical test.
The space saving achieved by our tool is a practical step in this direction.
The tool is open source and available at Code Ocean, github, and
http://ioncram.
saudigenomeproject.
com
.
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