Review



riboframe-processed  (Illumina Inc)


Bioz Verified Symbol Illumina Inc is a verified supplier  
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
    • 90
      Buy from Supplier

    Structured Review

    Illumina Inc riboframe-processed
    Scheme of the <t>riboFrame.</t> 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.”
    Riboframe Processed, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/riboframe-processed/riboframe+processed/pmc04646959-135-12-11
    Average 90 stars, based on 1 article reviews
    riboframe-processed - by Bioz Stars, 2026-09
    90/100 stars

    Images

    1) Product Images from "riboFrame: An Improved Method for Microbial Taxonomy Profiling from Non-Targeted Metagenomics"

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

    Journal: Frontiers in Genetics

    doi: 10.3389/fgene.2015.00329

    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.”
    Figure Legend 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.”

    Techniques Used: Next-Generation Sequencing

    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.
    Figure Legend 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.

    Techniques Used: Sequencing

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

    Techniques Used:

    Related Articles

    Next-Generation Sequencing:

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

    Sequencing:

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



    Similar Products

    riboframe-processed  (Illumina Inc)
    90
    Illumina Inc riboframe-processed
    Scheme of the <t>riboFrame.</t> 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.”
    Riboframe Processed, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/riboframe-processed/riboframe+processed/pmc04646959-135-12-11
    Average 90 stars, based on 1 article reviews
    riboframe-processed - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier
    illumina riboframe-processed reads  (Illumina Inc)
    90
    Illumina Inc illumina riboframe-processed reads
    Scheme of the <t>riboFrame.</t> 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.”
    Illumina Riboframe Processed Reads, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/riboframe-processed/illumina+riboframe+processed+reads/pmc04646959-135-8-11
    Average 90 stars, based on 1 article reviews
    illumina riboframe-processed reads - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    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.”

    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

    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.

    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

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

    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: