Tomatula

Katerina Boufea; I.N. Athanasiadis

Tomatula

Katerina Boufea (Developer), I.N. Athanasiadis (Developer)

Research output: Non-textual form › Software › Other research output

Abstract

Tomatula is an application that uses Apache Hadoop and Apache Spark to store and query big Variant Calling datasets. It introduces a columnar storage format instead of the flat VCF format for storing the Variant Calling data and storing them across the Hadoop Distributed File System.

Original language	English
Place of Publication	Wageningen
Publisher	BigDataWUR
Media of output	Online
Publication status	Published - 2017

Access to Document

https://github.com/BigDataWUR/tomatulaLicence: GNU GPL

1 Chapter

Managing Variant Calling Files the Big Data Way: Using HDFS and Apache Parquet
Boufea, A., Finkers, H. J., van Kaauwen, M. P. W., Kramer, M. R. & Athanasiadis, I. N., 2017, BDCAT '17 Proceedings of the Fourth IEEE/ACM International Conference on Big Data Computing, Applications and Technologies. ACM, p. 219-226
Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

Open Access
2 Citations (Scopus)

Experimental results of "Managing variant calling datasets the big data way"
Boufea, K. (Creator) & Athanasiadis, I. (Creator), Zenodo, 22 May 2017
DOI: 10.5281/zenodo.582145
Dataset

Cite this

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title = "Tomatula",

abstract = "Tomatula is an application that uses Apache Hadoop and Apache Spark to store and query big Variant Calling datasets. It introduces a columnar storage format instead of the flat VCF format for storing the Variant Calling data and storing them across the Hadoop Distributed File System.",

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Tomatula

Abstract

Access to Document

Managing Variant Calling Files the Big Data Way: Using HDFS and Apache Parquet

Experimental results of "Managing variant calling datasets the big data way"

Cite this