Evidence map›Paper›PMID 28369246›Full record

ArticleBioinformatics (Oxford, England)2017

PARTIE: a partition engine to separate metagenomic and amplicon projects in the Sequence Read Archive.

Pedro J Torres, Robert A Edwards, Katelyn A McNair

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Analysis of metagenomic data.Nature reviews. Methods primers · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Pedro J TorresDepartment of Biology.
Robert A EdwardsDepartment of Biology.
Katelyn A McNairComputational Science Research Center.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationThe 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.

resultsPARTIE 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. AVAILABILITY AND IMPLEMENTATION: PARTIE and reclassified metagenome SRA entries are available from https://github.com/linsalrob/partie. CONTACT: redwards@mail.sdsu.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

SoftwareBacteriaHumansMetagenomeMetagenomicsMicrobiotaMolecular Sequence AnnotationSequence Analysis, DNAViruses

Identifiers

PMID28369246
PMCPMC5860118

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.