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VENNTURE--a novel Venn diagram investigational tool for multiple pharmacological dataset analysis.

Martin B, Chadwick W, Yi T, Park SS, Lu D, Ni B, Gadkaree S, Farhang K, Becker KG, Maudsley S - PLoS ONE (2012)

Bottom Line: An improved appreciation of the connectivity between multiple, highly-complex datasets is crucial for the next generation of data analysis of genomic and proteomic data streams.Applied to complex pharmacological datasets, VENNTURE's improved features and ease of analysis are much improved over currently available Venn diagram programs.This study highlights the potential for such a program in fields such as pharmacology, genomics, and bioinformatics.

View Article: PubMed Central - PubMed

Affiliation: Metabolism Unit, Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America.

ABSTRACT
As pharmacological data sets become increasingly large and complex, new visual analysis and filtering programs are needed to aid their appreciation. One of the most commonly used methods for visualizing biological data is the Venn diagram. Currently used Venn analysis software often presents multiple problems to biological scientists, in that only a limited number of simultaneous data sets can be analyzed. An improved appreciation of the connectivity between multiple, highly-complex datasets is crucial for the next generation of data analysis of genomic and proteomic data streams. We describe the development of VENNTURE, a program that facilitates visualization of up to six datasets in a user-friendly manner. This program includes versatile output features, where grouped data points can be easily exported into a spreadsheet. To demonstrate its unique experimental utility we applied VENNTURE to a highly complex parallel paradigm, i.e. comparison of multiple G protein-coupled receptor drug dose phosphoproteomic data, in multiple cellular physiological contexts. VENNTURE was able to reliably and simply dissect six complex data sets into easily identifiable groups for straightforward analysis and data output. Applied to complex pharmacological datasets, VENNTURE's improved features and ease of analysis are much improved over currently available Venn diagram programs. VENNTURE enabled the delineation of highly complex patterns of dose-dependent G protein-coupled receptor activity and its dependence on physiological cellular contexts. This study highlights the potential for such a program in fields such as pharmacology, genomics, and bioinformatics.

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VENNTURE analysis of log dose-response ligand data in diverse cellular contexts.VENNTURE Venn diagram set distribution analysis (1–63 set intersections) of extracted phosphoproteins in the stimulated or non-stimulated SH-SY5Y cells in the control state (‘Control’ - A) or peroxide-treated state (‘CMP’ - B). Specific column color coding is as follows: blue - phosphoproteins unique to non-stimulated state only, red – phosphoproteins unique to a specific MeCh stimulation dose only; grey – phosphoproteins common to multiple MeCh doses but not present in the non-stimulated set; black – phosphoproteins common to multiple MeCh doses also present in the non-stimulated set; green – phosphoproteins common to all doses and the non-stimulated set. GO term enrichment analysis was performed using the initial phosphoprotein sets from cells in the control or CMP-treated states. The significantly enriched (p≤0.05) GO term groups for each non-stimulated or MeCh-stimulated set were then separated using VENNTURE in a similar manner to the actual phosphoprotein identifications. VENNTURE Venn diagram set distribution analysis of GO term groups significantly populated by the extracted phosphoproteins in the control state (C) or CMP-state (D) cells is depicted. Color-coding of the histogram is as described previously. Canonical signaling pathway enrichment analysis was also performed using the initial phosphoprotein sets from cells in the control or CMP-treated states. The significantly enriched (p≤0.05) canonical signaling pathways for each non-stimulated or MeCh-stimulated set were then separated using VENNTURE in a similar manner to the actual phosphoprotein identifications. VENNTURE Venn diagram set distribution analysis of the canonical signaling pathways significantly populated by the extracted phosphoproteins in the control state (E) or CMP-state (F) cells is depicted.
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pone-0036911-g005: VENNTURE analysis of log dose-response ligand data in diverse cellular contexts.VENNTURE Venn diagram set distribution analysis (1–63 set intersections) of extracted phosphoproteins in the stimulated or non-stimulated SH-SY5Y cells in the control state (‘Control’ - A) or peroxide-treated state (‘CMP’ - B). Specific column color coding is as follows: blue - phosphoproteins unique to non-stimulated state only, red – phosphoproteins unique to a specific MeCh stimulation dose only; grey – phosphoproteins common to multiple MeCh doses but not present in the non-stimulated set; black – phosphoproteins common to multiple MeCh doses also present in the non-stimulated set; green – phosphoproteins common to all doses and the non-stimulated set. GO term enrichment analysis was performed using the initial phosphoprotein sets from cells in the control or CMP-treated states. The significantly enriched (p≤0.05) GO term groups for each non-stimulated or MeCh-stimulated set were then separated using VENNTURE in a similar manner to the actual phosphoprotein identifications. VENNTURE Venn diagram set distribution analysis of GO term groups significantly populated by the extracted phosphoproteins in the control state (C) or CMP-state (D) cells is depicted. Color-coding of the histogram is as described previously. Canonical signaling pathway enrichment analysis was also performed using the initial phosphoprotein sets from cells in the control or CMP-treated states. The significantly enriched (p≤0.05) canonical signaling pathways for each non-stimulated or MeCh-stimulated set were then separated using VENNTURE in a similar manner to the actual phosphoprotein identifications. VENNTURE Venn diagram set distribution analysis of the canonical signaling pathways significantly populated by the extracted phosphoproteins in the control state (E) or CMP-state (F) cells is depicted.

Mentions: VENNTURE was used to rapidly separate and identify the multiple subsections of the TiO2-enriched phosphoproteomic data. The two input six-set phosphoprotein lists that we employed for this assessment (using official human protein symbols) are represented in Table S13 (control) and Table S14 (CMP). Using VENNTURE we were able to differentiate the highly-complex, dose-dependent phosphoproteomic effects of MeCh treatment, in both the control- and peroxide-treated (CMP) state cells (Figure 5). In both cases when using VENNTURE to separate out the specific subsets of phosphoproteins, it became evident that different MeCh ligand doses, in both cellular contexts employed (control- or CMP-state), produced complex and largely ‘dose-unique’ phosphoproteomic lists (Figure 5, control-state 5A, CMP-state 5B). Hence, many of the MeCh-stimulated phosphoproteins were unique to a specific log dose of the ligand (‘dose-unique’ protein sets are listed in Table S15 (control) and Table S16 (CMP)). Such ‘dose-unique’ activity may suggest that these large differences in applied MeCh dose interact preferentially with different stable ‘sub-states’ of the same receptor [8], [23]–[26]. However it is also possible that these specific signaling profiles may also be influenced by the differential availability of downstream signaling molecules, the progressive activation of distinct stimulatory and autoregulatory signaling events as well as micro temporal or kinetic variances in ligand-receptor interactions induced by the different ligand doses. Even with these potential complexities of receptor signaling, using the unique capacities of VENNTURE, we have shown that different doses of a single ligand, stimulating a unitary target receptor, can activate largely distinct pools of phosphoproteins across a log-dose response series. While phosphorylation is potentially an important process in the alteration of individual protein function, this information in itself may not be specifically indicative of a given functional activity, as most physiological actions involve interactions between multiple associated proteins. We therefore applied Gene Ontology (GO) term analysis (WebGestalt: http://bioinfo.vanderbilt.edu/webgestalt/[27], [28]) and canonical signaling pathway analysis (Ingenuity Pathway Analysis: http://www.ingenuity.com/) to generate a higher order of appreciation of the functional connections between our protein sets, allowing us to further investigate the ‘dose-unique’ behavior observed at the phosphoprotein level (Figure 5A, B). Data lists of significantly populated GO term groups (n≥2 proteins per group, probability (p)≤0.05) were created for each non-stimulated, or MeCh-stimulated dose state (Tables S17, S18, S19, S20, S21, S22 (control state) and Tables S23, S24, S25, S26, S27, S28 (CMP state)). For simple VENNTURE input, these dose-dependent tables were then summarized (Table S29 (control) and Table S30 (CMP)), and then subjected to six-way VENNTURE separation (Figure 5C-control state, 5D-CMP state). In an analogous manner to the phosphoprotein VENNTURE separations, we noticed a strong ‘dose-specific’ allocation of the different GO-term groups for MeCh treatment of control and peroxide-treated cells. This may suggest that with the relatively specific dose-dependent protein phosphorylation, there is also a dose-dependent variation in the activation of various functional groups of proteins. The ‘dose-unique’ groups of significantly enriched GO terms, for each cellular context, are listed in Table S31 (control state) and Table S32 (CMP-state). Significantly populated canonical signaling pathway matrices (n≥2 proteins per signaling pathway, p≤0.05) were next created for each non-stimulated, or MeCh-stimulated dose state in both cellular contexts (Table S33 (control state) and Table S34 (CMP-state)). The signaling pathway analysis was then subjected to six-way VENNTURE separation. In a manner reminiscent to the phosphoprotein and GO-term VENNTURE separations, we noticed a strong dose-unique allocation of the different canonical signaling pathways for MeCh treatment of control or peroxide-treated CMP cells (Figure 5E and 5F respectively). The ‘dose-unique’ groups of significantly enriched canonical signaling pathways for each cellular context are listed in Table S35 (control-state) and Table S36 (CMP-state).


VENNTURE--a novel Venn diagram investigational tool for multiple pharmacological dataset analysis.

Martin B, Chadwick W, Yi T, Park SS, Lu D, Ni B, Gadkaree S, Farhang K, Becker KG, Maudsley S - PLoS ONE (2012)

VENNTURE analysis of log dose-response ligand data in diverse cellular contexts.VENNTURE Venn diagram set distribution analysis (1–63 set intersections) of extracted phosphoproteins in the stimulated or non-stimulated SH-SY5Y cells in the control state (‘Control’ - A) or peroxide-treated state (‘CMP’ - B). Specific column color coding is as follows: blue - phosphoproteins unique to non-stimulated state only, red – phosphoproteins unique to a specific MeCh stimulation dose only; grey – phosphoproteins common to multiple MeCh doses but not present in the non-stimulated set; black – phosphoproteins common to multiple MeCh doses also present in the non-stimulated set; green – phosphoproteins common to all doses and the non-stimulated set. GO term enrichment analysis was performed using the initial phosphoprotein sets from cells in the control or CMP-treated states. The significantly enriched (p≤0.05) GO term groups for each non-stimulated or MeCh-stimulated set were then separated using VENNTURE in a similar manner to the actual phosphoprotein identifications. VENNTURE Venn diagram set distribution analysis of GO term groups significantly populated by the extracted phosphoproteins in the control state (C) or CMP-state (D) cells is depicted. Color-coding of the histogram is as described previously. Canonical signaling pathway enrichment analysis was also performed using the initial phosphoprotein sets from cells in the control or CMP-treated states. The significantly enriched (p≤0.05) canonical signaling pathways for each non-stimulated or MeCh-stimulated set were then separated using VENNTURE in a similar manner to the actual phosphoprotein identifications. VENNTURE Venn diagram set distribution analysis of the canonical signaling pathways significantly populated by the extracted phosphoproteins in the control state (E) or CMP-state (F) cells is depicted.
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Related In: Results  -  Collection

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pone-0036911-g005: VENNTURE analysis of log dose-response ligand data in diverse cellular contexts.VENNTURE Venn diagram set distribution analysis (1–63 set intersections) of extracted phosphoproteins in the stimulated or non-stimulated SH-SY5Y cells in the control state (‘Control’ - A) or peroxide-treated state (‘CMP’ - B). Specific column color coding is as follows: blue - phosphoproteins unique to non-stimulated state only, red – phosphoproteins unique to a specific MeCh stimulation dose only; grey – phosphoproteins common to multiple MeCh doses but not present in the non-stimulated set; black – phosphoproteins common to multiple MeCh doses also present in the non-stimulated set; green – phosphoproteins common to all doses and the non-stimulated set. GO term enrichment analysis was performed using the initial phosphoprotein sets from cells in the control or CMP-treated states. The significantly enriched (p≤0.05) GO term groups for each non-stimulated or MeCh-stimulated set were then separated using VENNTURE in a similar manner to the actual phosphoprotein identifications. VENNTURE Venn diagram set distribution analysis of GO term groups significantly populated by the extracted phosphoproteins in the control state (C) or CMP-state (D) cells is depicted. Color-coding of the histogram is as described previously. Canonical signaling pathway enrichment analysis was also performed using the initial phosphoprotein sets from cells in the control or CMP-treated states. The significantly enriched (p≤0.05) canonical signaling pathways for each non-stimulated or MeCh-stimulated set were then separated using VENNTURE in a similar manner to the actual phosphoprotein identifications. VENNTURE Venn diagram set distribution analysis of the canonical signaling pathways significantly populated by the extracted phosphoproteins in the control state (E) or CMP-state (F) cells is depicted.
Mentions: VENNTURE was used to rapidly separate and identify the multiple subsections of the TiO2-enriched phosphoproteomic data. The two input six-set phosphoprotein lists that we employed for this assessment (using official human protein symbols) are represented in Table S13 (control) and Table S14 (CMP). Using VENNTURE we were able to differentiate the highly-complex, dose-dependent phosphoproteomic effects of MeCh treatment, in both the control- and peroxide-treated (CMP) state cells (Figure 5). In both cases when using VENNTURE to separate out the specific subsets of phosphoproteins, it became evident that different MeCh ligand doses, in both cellular contexts employed (control- or CMP-state), produced complex and largely ‘dose-unique’ phosphoproteomic lists (Figure 5, control-state 5A, CMP-state 5B). Hence, many of the MeCh-stimulated phosphoproteins were unique to a specific log dose of the ligand (‘dose-unique’ protein sets are listed in Table S15 (control) and Table S16 (CMP)). Such ‘dose-unique’ activity may suggest that these large differences in applied MeCh dose interact preferentially with different stable ‘sub-states’ of the same receptor [8], [23]–[26]. However it is also possible that these specific signaling profiles may also be influenced by the differential availability of downstream signaling molecules, the progressive activation of distinct stimulatory and autoregulatory signaling events as well as micro temporal or kinetic variances in ligand-receptor interactions induced by the different ligand doses. Even with these potential complexities of receptor signaling, using the unique capacities of VENNTURE, we have shown that different doses of a single ligand, stimulating a unitary target receptor, can activate largely distinct pools of phosphoproteins across a log-dose response series. While phosphorylation is potentially an important process in the alteration of individual protein function, this information in itself may not be specifically indicative of a given functional activity, as most physiological actions involve interactions between multiple associated proteins. We therefore applied Gene Ontology (GO) term analysis (WebGestalt: http://bioinfo.vanderbilt.edu/webgestalt/[27], [28]) and canonical signaling pathway analysis (Ingenuity Pathway Analysis: http://www.ingenuity.com/) to generate a higher order of appreciation of the functional connections between our protein sets, allowing us to further investigate the ‘dose-unique’ behavior observed at the phosphoprotein level (Figure 5A, B). Data lists of significantly populated GO term groups (n≥2 proteins per group, probability (p)≤0.05) were created for each non-stimulated, or MeCh-stimulated dose state (Tables S17, S18, S19, S20, S21, S22 (control state) and Tables S23, S24, S25, S26, S27, S28 (CMP state)). For simple VENNTURE input, these dose-dependent tables were then summarized (Table S29 (control) and Table S30 (CMP)), and then subjected to six-way VENNTURE separation (Figure 5C-control state, 5D-CMP state). In an analogous manner to the phosphoprotein VENNTURE separations, we noticed a strong ‘dose-specific’ allocation of the different GO-term groups for MeCh treatment of control and peroxide-treated cells. This may suggest that with the relatively specific dose-dependent protein phosphorylation, there is also a dose-dependent variation in the activation of various functional groups of proteins. The ‘dose-unique’ groups of significantly enriched GO terms, for each cellular context, are listed in Table S31 (control state) and Table S32 (CMP-state). Significantly populated canonical signaling pathway matrices (n≥2 proteins per signaling pathway, p≤0.05) were next created for each non-stimulated, or MeCh-stimulated dose state in both cellular contexts (Table S33 (control state) and Table S34 (CMP-state)). The signaling pathway analysis was then subjected to six-way VENNTURE separation. In a manner reminiscent to the phosphoprotein and GO-term VENNTURE separations, we noticed a strong dose-unique allocation of the different canonical signaling pathways for MeCh treatment of control or peroxide-treated CMP cells (Figure 5E and 5F respectively). The ‘dose-unique’ groups of significantly enriched canonical signaling pathways for each cellular context are listed in Table S35 (control-state) and Table S36 (CMP-state).

Bottom Line: An improved appreciation of the connectivity between multiple, highly-complex datasets is crucial for the next generation of data analysis of genomic and proteomic data streams.Applied to complex pharmacological datasets, VENNTURE's improved features and ease of analysis are much improved over currently available Venn diagram programs.This study highlights the potential for such a program in fields such as pharmacology, genomics, and bioinformatics.

View Article: PubMed Central - PubMed

Affiliation: Metabolism Unit, Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America.

ABSTRACT
As pharmacological data sets become increasingly large and complex, new visual analysis and filtering programs are needed to aid their appreciation. One of the most commonly used methods for visualizing biological data is the Venn diagram. Currently used Venn analysis software often presents multiple problems to biological scientists, in that only a limited number of simultaneous data sets can be analyzed. An improved appreciation of the connectivity between multiple, highly-complex datasets is crucial for the next generation of data analysis of genomic and proteomic data streams. We describe the development of VENNTURE, a program that facilitates visualization of up to six datasets in a user-friendly manner. This program includes versatile output features, where grouped data points can be easily exported into a spreadsheet. To demonstrate its unique experimental utility we applied VENNTURE to a highly complex parallel paradigm, i.e. comparison of multiple G protein-coupled receptor drug dose phosphoproteomic data, in multiple cellular physiological contexts. VENNTURE was able to reliably and simply dissect six complex data sets into easily identifiable groups for straightforward analysis and data output. Applied to complex pharmacological datasets, VENNTURE's improved features and ease of analysis are much improved over currently available Venn diagram programs. VENNTURE enabled the delineation of highly complex patterns of dose-dependent G protein-coupled receptor activity and its dependence on physiological cellular contexts. This study highlights the potential for such a program in fields such as pharmacology, genomics, and bioinformatics.

Show MeSH
Related in: MedlinePlus