Reference-based compression of short-read sequences using path encoding

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چکیده

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Reference-based compression of short-read sequences using path encoding

MOTIVATION Storing, transmitting and archiving data produced by next-generation sequencing is a significant computational burden. New compression techniques tailored to short-read sequence data are needed. RESULTS We present here an approach to compression that reduces the difficulty of managing large-scale sequencing data. Our novel approach sits between pure reference-based compression and ...

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Compression of short-read sequences using path encoding

Storing, transmitting, and archiving the amount of data produced by next generation sequencing is becoming a significant computational burden. For example, large-scale RNA-seq meta-analyses may now routinely process tens of terabytes of sequence. We present here an approach to biological sequence compression that reduces the difficulty associated with managing the data produced by large-scale t...

متن کامل

Compression of short-read sequences using path encoding

Storing, transmitting, and archiving the amount of data produced by next generation sequencing is becoming a significant computational burden. For example, large-scale RNA-seq meta-analyses may now routinely process tens of terabytes of sequence. We present here an approach to biological sequence compression that reduces the difficulty associated with managing the data produced by large-scale t...

متن کامل

Compression of short-read sequences using path encoding

Storing, transmitting, and archiving the amount of data produced by next generation sequencing is becoming a significant computational burden. For example, large-scale RNA-seq meta-analyses may now routinely process tens of terabytes of sequence. We present here an approach to biological sequence compression that reduces the difficulty associated with managing the data produced by large-scale t...

متن کامل

Compression of short-read sequences using path encoding

Storing, transmitting, and archiving the amount of data produced by next generation sequencing is becoming a significant computational burden. For example, large-scale RNA-seq meta-analyses may now routinely process tens of terabytes of sequence. We present here an approach to biological sequence compression that reduces the difficulty associated with managing the data produced by large-scale t...

متن کامل

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2015

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/btv071