Genomic Data Clustering on FPGAs for Compression

Petraglio, Enrico (School of Management and Engineering Vaud, HES-SO // University of Applied Sciences Western Switzerland) ; Wertenbroek, Rick (School of Management and Engineering Vaud, HES-SO // University of Applied Sciences Western Switzerland) ; Capitao, Flavio (School of Management and Engineering Vaud, HES-SO // University of Applied Sciences Western Switzerland) ; Guex, Nicolas (Vital-IT, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland) ; Iseli, Christian (Vital-IT, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland) ; Thoma, Yann (School of Management and Engineering Vaud, HES-SO // University of Applied Sciences Western Switzerland)

Current sequencing machine technology generates very large and redundant volumes of genomic data for each biological sample. Today data and associated metadata are formatted in very large text file assemblies called FASTQ carrying the information of billions of genome fragments referred to as “reads” and composed of strings of nucleotide bases with lengths in the range of a few tenths to a few hundreds bases. Compressing such data is definitely required in order to manage the sheer amount of data soon to be generated. Doing so implies finding redundant information in the raw sequences. While most of it can be mapped onto the human reference genome and fits well for compression, about 10% of it usually does not map to any reference . For these orphan sequences, finding redundancy will help compression. Doing so requires clustering these reads, a very time consuming process. Within this context this paper presents a FPGA implementation of a clustering algorithm for genomic reads, implemented on Pico Computing EX-700 AC-510 hard-ware, offering more than a 1000×speed up over a CPU implementation while reducing power consumption by a 700 factor.


Conference Type:
full paper
Faculty:
Ingénierie et Architecture
School:
HEIG-VD
Institute:
ReDS - Reconfigurable & embedded Digital Systems
Subject(s):
Ingénierie
Publisher:
Delft, The Netherlands, 3-7 April 2017
Date:
2017-03
Delft, The Netherlands
3-7 April 2017
Pagination:
12 p.
Published in:
Lecture Notes in Computer Science ; Proceedings of Applied reconfigurable computing, 13th International Symposium, ARC 2017, 3-7 April 2017, Delft, The Netherlands
DOI:
ISSN:
0302-9743
ISBN:
978-3-319-56257-5
External resources:
Appears in Collection:

Note: The status of this file is: restricted


 Record created 2019-04-23, last modified 2019-04-23

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