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Efficient storage and analysis of quantitative genomics data with the Dense Depth Data Dump (D4) format and d4tools

Hao Hou, Brent Pedersen, Aaron Quinlan
doi: https://doi.org/10.1101/2020.10.23.352567
Hao Hou
1Department of Human Genetics, University of Utah, Salt Lake City, UT
2Utah Center for Genetic Discovery, University of Utah, Salt Lake City, UT
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Brent Pedersen
1Department of Human Genetics, University of Utah, Salt Lake City, UT
2Utah Center for Genetic Discovery, University of Utah, Salt Lake City, UT
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Aaron Quinlan
1Department of Human Genetics, University of Utah, Salt Lake City, UT
2Utah Center for Genetic Discovery, University of Utah, Salt Lake City, UT
3Department of Biomedical Informatics, University of Utah, Salt Lake City, UT
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  • For correspondence: aaronquinlan@gmail.com
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Abstract

Modern DNA sequencing is used as a readout for diverse assays, with the count of aligned sequences, or “read depth”, serving as the quantitative signal for many underlying cellular phenomena. Despite wide use and thousands of datasets, existing formats used for the storage and analysis of read depths are limited with respect to both file size and analysis speed. For example, it is faster to recalculate sequencing depth from an alignment file than it is to analyze the text output from that calculation. We sought to improve on existing formats such as BigWig and compressed BED files by creating the Dense Depth Data Dump (D4) format and tool suite. The D4 format is adaptive in that it profiles a random sample of aligned sequence depth from the input BAM or CRAM file to determine an optimal encoding that often affords reductions in file size, while also enabling fast data access. We show that D4 uses less storage for both RNA-Seq and whole-genome sequencing and offers 3 to 440-fold speed improvements over existing formats for random access, aggregation and summarization. This performance enables scalable downstream analyses that would be otherwise difficult. The D4 tool suite (d4tools) is freely available under an MIT license at: https://github.com/38/d4-format.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/38/d4-format

  • https://github.com/38/pyd4

  • https://docs.rs/d4

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted October 26, 2020.
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Efficient storage and analysis of quantitative genomics data with the Dense Depth Data Dump (D4) format and d4tools
Hao Hou, Brent Pedersen, Aaron Quinlan
bioRxiv 2020.10.23.352567; doi: https://doi.org/10.1101/2020.10.23.352567
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Efficient storage and analysis of quantitative genomics data with the Dense Depth Data Dump (D4) format and d4tools
Hao Hou, Brent Pedersen, Aaron Quinlan
bioRxiv 2020.10.23.352567; doi: https://doi.org/10.1101/2020.10.23.352567

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