riboframe: an improved method for microbial taxonomy profiling from non-targeted metagenomics
Clicks: 236
ID: 147933
2015
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
236 views
24 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #186 of 264 articles by views in chemical record (new york, ny)
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 264 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Non-targeted metagenomics offers the unprecedented possibility of simultaneously investigate the microbial profile and the genetic capabilities of a sample by a direct analysis of its entire DNA content. The assessment of the microbial taxonomic composition is frequently obtained by mapping reads to genomic databases that, although growing, are still limited and biased. Here we present riboFrame, a novel procedure for microbial profiling based on the identification and classification of 16S rRNA sequences in non-targeted metagenomics datasets. Reads overlapping the 16S rRNA genes are identified using Hidden Markov Models and a taxonomic assignment is obtained by naïve Bayesian classification. All reads identified as ribosomal are coherently positioned in the 16S rRNA gene, allowing the use of the topology of the gene (i.e. the secondary structure and the location of variable regions) to guide the abundance analysis. We tested and verified the efficacy of our method on simulated ribosomal data, on simulated metagenomes and on a real dataset. riboFrame exploits the taxonomic potentialities of the 16S rRNA gene in the context of non-targeted metagenomics, giving an accurate perspective on the microbial profile in metagenomic samples.
| Reference Key |
eramazzotti2015frontiersriboframe:
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Matteo eRamazzotti;Luisa eBerná;Claudio eDonati;Duccio eCavalieri |
| Journal | chemical record (new york, ny) |
| Year | 2015 |
| DOI |
10.3389/fgene.2015.00329
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.