Journal: Journal of Dental Sciences

Article Title: Oral microbial profiles of extrinsic black tooth stain in primary dentition: A literature review

doi: 10.1016/j.jds.2024.02.028

Figure Lengend Snippet: Oral microbial profiles of the EBS in primary dentition.

Article Snippet: 2016 , China , 40 EBS; 26 HG , saliva plaque EBS , 454 pyrosequencing (V1–V3 regions,16SrRNA) , Relative abundance: • Plaque-EG vs. HG: Leptotrichia and Fusobacterium ( P < 0.05–0.001, EG↑) • Saliva-No significant difference.

Techniques: Sequencing

Journal: Frontiers in Genetics

Article Title: riboFrame: An Improved Method for Microbial Taxonomy Profiling from Non-Targeted Metagenomics

doi: 10.3389/fgene.2015.00329

Figure Lengend Snippet: Scheme of the riboFrame. After QC of next generation sequencing (NGS) reads, the hmmsearch (HMMER3) is used to identify 16S ribosomal reads in both bacteria and archaea, using HMMs developed in rRNAselector (step 1). The riboTrap program then filters out incongruent assignments and de-replicate multiple assignments in order to create a set of accurate 16S reads supplemented with positional information (step 2). 16S reads are then classified using RDPclassifier to obtain a full domain to genus classification (step 3). The riboMap program eventually filters reads according to rules specified by the user, with a flexible and intuitive scheme, and performs the final rank abundance analyses (step 4). For a detailed description see the section “Materials and Methods – Description of the riboFrame Procedures.”

Article Snippet: The correlation coefficient of abundance percent at the genus level in Illumina riboFrame-processed vs. pyrosequencing reads was 0.971 for the V1–V3 region and 0.942 for the V3–V5 region, confirming that riboFrame processing of non-targeted Illumina reads gives results comparable to those obtained with targeted pyrosequencing.

Techniques: Next-Generation Sequencing

Journal: Frontiers in Genetics

Article Title: riboFrame: An Improved Method for Microbial Taxonomy Profiling from Non-Targeted Metagenomics

doi: 10.3389/fgene.2015.00329

Figure Lengend Snippet: Comparison of microbial profiling between riboFrame and 16S rDNA pyrosequencing on HMP sample SRS011061. (Top) Barplots of genus-level abundance calculation on two 16S regions targeted by Illumina sequencing after the riboFrame processing. Left and right columns present results from 16S rDNA variable regions V1–V3 and V3–V5, respectively. Only genera accounting for at least 1% of the total classifiable reads are shown. (Bottom) Scatterplot depicting the full range of abundances % obtained with pyrosequencing ( x -axis) and with riboFrame-processed Illumina reads ( y -axis), along with a linear best fitting line (dashed). The Pearson correlation coefficient (R) of the two dataset is also present.

Article Snippet: The correlation coefficient of abundance percent at the genus level in Illumina riboFrame-processed vs. pyrosequencing reads was 0.971 for the V1–V3 region and 0.942 for the V3–V5 region, confirming that riboFrame processing of non-targeted Illumina reads gives results comparable to those obtained with targeted pyrosequencing.

Techniques: Sequencing

Journal: Frontiers in Genetics

Article Title: riboFrame: An Improved Method for Microbial Taxonomy Profiling from Non-Targeted Metagenomics

doi: 10.3389/fgene.2015.00329

Figure Lengend Snippet: Result of the extraction of ribosomal reads from the “Curated” ribosomal reads set (187000 reads) by various extractors.

Article Snippet: The correlation coefficient of abundance percent at the genus level in Illumina riboFrame-processed vs. pyrosequencing reads was 0.971 for the V1–V3 region and 0.942 for the V3–V5 region, confirming that riboFrame processing of non-targeted Illumina reads gives results comparable to those obtained with targeted pyrosequencing.

Techniques: