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These massive sequencing datasets demand high-performance computational resources, rapid data transfer, large-scale data storage, and competent data analysts.
On the bioinformatics end, assembling massive sequencing datasets is extremely demanding on computing cycles, memory usage, storage requirements, and for parallel programming implementations on communication traffic.
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The accompanying article [ 12] introduced a highly efficient tool, Tallymer, to analyze k-mers within the massive sequence datasets available from maize.
The advent of ultra-high-throughput sequencing has made it possible to obtain massive sequence datasets from experimentally challenging organisms - and even collections of intimately associated organisms - on a scale unimaginable even a few years ago.
However, it requires massive sequencing effort with considerable costs.
Massive sequencing data can be overwhelming to examine.
We had just entered the era of massive sequencing.
Actually, hundreds of thousands of DNA variants are detected in massive sequencing projects of genetic disorders.
The present result emphasizes the complementarities of both SuperSAGE and other massive sequencing approaches.
RNA-seq was performed at the Massive Sequencing Platform of Cantoblanco (CSIC-PCM, Madrid, Spain).
However, despite of massive sequencing, loss of rare transcripts is possible.
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