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MetaPathways v2.5: quantitative functional, taxonomic and usability improvements.

Konwar KM, Hanson NW, Bhatia MP, Kim D, Wu SJ, Hahn AS, Morgan-Lang C, Cheung HK, Hallam SJ - Bioinformatics (2015)

Bottom Line: We specifically address pathway prediction hazards through integration of a weighted taxonomic distance and enable quantitative comparison of assembled annotations through a normalized read-mapping measure.Additionally, we improve LAST homology searches through BLAST-equivalent E-values and output formats that are natively compatible with prevailing software applications.Finally, an updated graphical user interface allows for keyword annotation query and projection onto user-defined functional gene hierarchies, including the Carbohydrate-Active Enzyme database.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology & Immunology, University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC, Canada.

No MeSH data available.


Related in: MedlinePlus

Quantitative functional and taxonomic improvements. (a) WTD provides a measure of taxonomic agreement between observed RefSeq Lowest common ancestor (LCA) taxonomy and the expected taxonomic range of predicted MetaCyc pathways, separated into the ‘High’ (Red), ‘Medium’ (Orange) and ‘Low’ (Green) taxonomic hazard classes based on negative quartile order statistics. Positive distances represent taxa found within a pathways expected taxonomic range and so have a hazard class of ‘None’ (Grey). (b) The LAST and BLAST homology search algorithms are highly correlated in terms of E-value (, P < 0.01). (c) ORF Count and the RPKM measure show a linear relationship (R2 = 0.816, P < 0.01). Ninety percent of prediction intervals, displayed as a pair of thin blue lines about the fitted line, capture ∼96.7 and 91.3% of observed points in (b) and (c), respectively. Analysis code can be found in the Supplementary information
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btv361-F1: Quantitative functional and taxonomic improvements. (a) WTD provides a measure of taxonomic agreement between observed RefSeq Lowest common ancestor (LCA) taxonomy and the expected taxonomic range of predicted MetaCyc pathways, separated into the ‘High’ (Red), ‘Medium’ (Orange) and ‘Low’ (Green) taxonomic hazard classes based on negative quartile order statistics. Positive distances represent taxa found within a pathways expected taxonomic range and so have a hazard class of ‘None’ (Grey). (b) The LAST and BLAST homology search algorithms are highly correlated in terms of E-value (, P < 0.01). (c) ORF Count and the RPKM measure show a linear relationship (R2 = 0.816, P < 0.01). Ninety percent of prediction intervals, displayed as a pair of thin blue lines about the fitted line, capture ∼96.7 and 91.3% of observed points in (b) and (c), respectively. Analysis code can be found in the Supplementary information

Mentions: We benchmarked the implemented improvements described earlier using Illumina-sequenced marine metagenomic samples. (Joint Genome Institute: ‘Marine microbial communities from Expanding Oxygen minimum zones project’ (JGI Project IDs: 4093112, 4093113, 4093125, 4093127–4093132, 4093144–4093149, 4096364–4096371, 4096373, 4096375, 4096377–4096379, 4096381–4096383, 4096385–4096387, 4096389–4096396, 4096398–4096406 and 4096409–4096453)). The WTD distribution can be used as an informative tool to place pathways into different taxonomic hazard classes based on their order statistics (Fig. 1a). Protein annotations of BLAST and LAST are highly correlated in terms of E-value (Fig. 1b), suggesting roughly equivalent results, but with LAST being significantly faster. Although there is a positive correlation between RPKM score and ORF count, variance about the regression line indicates RPKM makes a correction in many instances (Fig. 1c).Fig. 1.


MetaPathways v2.5: quantitative functional, taxonomic and usability improvements.

Konwar KM, Hanson NW, Bhatia MP, Kim D, Wu SJ, Hahn AS, Morgan-Lang C, Cheung HK, Hallam SJ - Bioinformatics (2015)

Quantitative functional and taxonomic improvements. (a) WTD provides a measure of taxonomic agreement between observed RefSeq Lowest common ancestor (LCA) taxonomy and the expected taxonomic range of predicted MetaCyc pathways, separated into the ‘High’ (Red), ‘Medium’ (Orange) and ‘Low’ (Green) taxonomic hazard classes based on negative quartile order statistics. Positive distances represent taxa found within a pathways expected taxonomic range and so have a hazard class of ‘None’ (Grey). (b) The LAST and BLAST homology search algorithms are highly correlated in terms of E-value (, P < 0.01). (c) ORF Count and the RPKM measure show a linear relationship (R2 = 0.816, P < 0.01). Ninety percent of prediction intervals, displayed as a pair of thin blue lines about the fitted line, capture ∼96.7 and 91.3% of observed points in (b) and (c), respectively. Analysis code can be found in the Supplementary information
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
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getmorefigures.php?uid=PMC4595896&req=5

btv361-F1: Quantitative functional and taxonomic improvements. (a) WTD provides a measure of taxonomic agreement between observed RefSeq Lowest common ancestor (LCA) taxonomy and the expected taxonomic range of predicted MetaCyc pathways, separated into the ‘High’ (Red), ‘Medium’ (Orange) and ‘Low’ (Green) taxonomic hazard classes based on negative quartile order statistics. Positive distances represent taxa found within a pathways expected taxonomic range and so have a hazard class of ‘None’ (Grey). (b) The LAST and BLAST homology search algorithms are highly correlated in terms of E-value (, P < 0.01). (c) ORF Count and the RPKM measure show a linear relationship (R2 = 0.816, P < 0.01). Ninety percent of prediction intervals, displayed as a pair of thin blue lines about the fitted line, capture ∼96.7 and 91.3% of observed points in (b) and (c), respectively. Analysis code can be found in the Supplementary information
Mentions: We benchmarked the implemented improvements described earlier using Illumina-sequenced marine metagenomic samples. (Joint Genome Institute: ‘Marine microbial communities from Expanding Oxygen minimum zones project’ (JGI Project IDs: 4093112, 4093113, 4093125, 4093127–4093132, 4093144–4093149, 4096364–4096371, 4096373, 4096375, 4096377–4096379, 4096381–4096383, 4096385–4096387, 4096389–4096396, 4096398–4096406 and 4096409–4096453)). The WTD distribution can be used as an informative tool to place pathways into different taxonomic hazard classes based on their order statistics (Fig. 1a). Protein annotations of BLAST and LAST are highly correlated in terms of E-value (Fig. 1b), suggesting roughly equivalent results, but with LAST being significantly faster. Although there is a positive correlation between RPKM score and ORF count, variance about the regression line indicates RPKM makes a correction in many instances (Fig. 1c).Fig. 1.

Bottom Line: We specifically address pathway prediction hazards through integration of a weighted taxonomic distance and enable quantitative comparison of assembled annotations through a normalized read-mapping measure.Additionally, we improve LAST homology searches through BLAST-equivalent E-values and output formats that are natively compatible with prevailing software applications.Finally, an updated graphical user interface allows for keyword annotation query and projection onto user-defined functional gene hierarchies, including the Carbohydrate-Active Enzyme database.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology & Immunology, University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC, Canada.

No MeSH data available.


Related in: MedlinePlus