Paper Info
Title
PARTIE: a partition engine to separate metagenomic and amplicon projects in the Sequence Read Archive.
Abstract
Motivation: The Sequence Read Archive (SRA) contains raw data from many different types of sequence projects. As of 2017, the SRA contained approximately ten petabases of DNA sequence (10(16) bp). Annotations of the data are provided by the submitter, and mining the data in the SRA is complicated by both the amount of data and the detail within those annotations. Here, we introduce PARTIE, a partition engine optimized to differentiate sequence read data into metagenomic (random) and amplicon (targeted) sequence data sets. Results: PARTIE subsamples reads from the sequencing file and calculates four different statistics: k-mer frequency, 16S abundance, prokaryotic- and viral-read abundance. These metrics are used to create a RandomForest decision tree to classify the sequencing data, and PARTIE provides mechanisms for both supervised and unsupervised classification. We demonstrate the accuracy of PARTIE for classifying SRA data, discuss the probable error rates in the SRA annotations and introduce a resource assessing SRA data.
Year
DOI
Venue
2017
10.1093/bioinformatics/btx184
BIOINFORMATICS
Field
DocType
Volume
Computer science,Amplicon,Metagenomics,Bioinformatics,Partition (number theory)
Journal
33
Issue
ISSN
Citations 
15
1367-4803
0
PageRank 
References 
Authors
0.34
5
3
Name
Order
Citations
PageRank
Pedro J. Torres1177.08
Robert Edwards218618.91
Katelyn McNair321.07