self-organizing tree algorithm multi experiment viewer software v.4.8.1 (SourceForge net)

SourceForge net self-organizing tree algorithm multi experiment viewer software v.4.8.1

Differential analysis of protein-coding RNAs in uterine EVs <t>across</t> samples. ( A ) Principal component analysis (PCA) based on protein-coding RNA (mRNA) for all <t>experimental</t> <t>groups</t> (pregnancy days 10, 11, 12, and 13: P10, P11, P12, and P13; cyclic controls days 10 and 13 post-ovulation: C10, C13). ( B ) Mean-centered log2 counts per million (cpm) values were calculated (log2 of CPM of respective sample – mean of all samples) for mRNAs DA across samples (FDR 1%). Hierarchical cluster analysis (HCL) (Pearson correlation, MeV software) was performed across experimental groups for differentially abundant (DA) mRNAs. ( C ) Self-organizing tree algorithm (SOTA) analysis was used to identify clusters of genes with similar <t>expression</t> <t>profiles</t> across experimental groups. Six clusters of protein-coding RNA across samples were obtained, with six expression images showing the number of genes and expression profiles in each SOTA cluster. PCA image was created with Bioconductor package EdgeR ( https://bioconductor.org/packages/release/bioc/html/edgeR.html) and other standard R packages. HCL and SOTA expression images were created with Multiple Experiment Viewer (MeV v.4.8.1, https://sourceforge.net/projects/mev-tm4/) . Images were modified in Adobe Photoshop v.22.4.3. Labelling of each sample refers to: day of pregnancy or cycle; followed by the number of EV sample from 1 to 24; followed by the number of endometrial sample collected at the same time and analyzed in a parallel study ; followed by the embryo size (e.g., 1e.5: one embryo collected with 5 mm diameter; 2e.3.4 = two embryos were collected with 3 and 4 mm; nd: the diameter could not be determined, embryo broken during collection; 0: for control samples).

Self Organizing Tree Algorithm Multi Experiment Viewer Software V.4.8.1, supplied by SourceForge net, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Differential analysis of protein-coding RNAs in uterine EVs across samples. ( A ) Principal component analysis (PCA) based on protein-coding RNA (mRNA) for all experimental groups (pregnancy days 10, 11, 12, and 13: P10, P11, P12, and P13; cyclic controls days 10 and 13 post-ovulation: C10, C13). ( B ) Mean-centered log2 counts per million (cpm) values were calculated (log2 of CPM of respective sample – mean of all samples) for mRNAs DA across samples (FDR 1%). Hierarchical cluster analysis (HCL) (Pearson correlation, MeV software) was performed across experimental groups for differentially abundant (DA) mRNAs. ( C ) Self-organizing tree algorithm (SOTA) analysis was used to identify clusters of genes with similar expression profiles across experimental groups. Six clusters of protein-coding RNA across samples were obtained, with six expression images showing the number of genes and expression profiles in each SOTA cluster. PCA image was created with Bioconductor package EdgeR ( https://bioconductor.org/packages/release/bioc/html/edgeR.html) and other standard R packages. HCL and SOTA expression images were created with Multiple Experiment Viewer (MeV v.4.8.1, https://sourceforge.net/projects/mev-tm4/) . Images were modified in Adobe Photoshop v.22.4.3. Labelling of each sample refers to: day of pregnancy or cycle; followed by the number of EV sample from 1 to 24; followed by the number of endometrial sample collected at the same time and analyzed in a parallel study ; followed by the embryo size (e.g., 1e.5: one embryo collected with 5 mm diameter; 2e.3.4 = two embryos were collected with 3 and 4 mm; nd: the diameter could not be determined, embryo broken during collection; 0: for control samples).

Journal: Scientific Reports

Article Title: Uterine extracellular vesicles as multi-signal messengers during maternal recognition of pregnancy in the mare

doi: 10.1038/s41598-022-19958-z

Figure Lengend Snippet: Differential analysis of protein-coding RNAs in uterine EVs across samples. ( A ) Principal component analysis (PCA) based on protein-coding RNA (mRNA) for all experimental groups (pregnancy days 10, 11, 12, and 13: P10, P11, P12, and P13; cyclic controls days 10 and 13 post-ovulation: C10, C13). ( B ) Mean-centered log2 counts per million (cpm) values were calculated (log2 of CPM of respective sample – mean of all samples) for mRNAs DA across samples (FDR 1%). Hierarchical cluster analysis (HCL) (Pearson correlation, MeV software) was performed across experimental groups for differentially abundant (DA) mRNAs. ( C ) Self-organizing tree algorithm (SOTA) analysis was used to identify clusters of genes with similar expression profiles across experimental groups. Six clusters of protein-coding RNA across samples were obtained, with six expression images showing the number of genes and expression profiles in each SOTA cluster. PCA image was created with Bioconductor package EdgeR ( https://bioconductor.org/packages/release/bioc/html/edgeR.html) and other standard R packages. HCL and SOTA expression images were created with Multiple Experiment Viewer (MeV v.4.8.1, https://sourceforge.net/projects/mev-tm4/) . Images were modified in Adobe Photoshop v.22.4.3. Labelling of each sample refers to: day of pregnancy or cycle; followed by the number of EV sample from 1 to 24; followed by the number of endometrial sample collected at the same time and analyzed in a parallel study ; followed by the embryo size (e.g., 1e.5: one embryo collected with 5 mm diameter; 2e.3.4 = two embryos were collected with 3 and 4 mm; nd: the diameter could not be determined, embryo broken during collection; 0: for control samples).

Article Snippet: To identify clusters of genes with similar expression profiles across experimental groups, self-organizing tree algorithm (SOTA, Multi Experiment Viewer software v.4.8.1, https://sourceforge.net/projects/mev-tm4/) was used.

Techniques: Software, Expressing, Modification, Control

Differential analysis of miRNAs in uEVs across samples and identification of enriched pathways for target genes of differentially abundant miRNAs. ( A ) Mean-centered log2 counts per million (cpm) values were calculated (log2 of CPM of respective sample – mean of all samples) for miRNAs differentially abundant (DA) across experimental groups (FDR 10%). Hierarchical cluster analysis (HCL) (Pearson correlation, MeV software) was performed for DA miRNAs (pregnancy days 10, 11, 12, and 13: P10, P11, P12, and P13; cyclic controls days 10 and 13 post-ovulation: C10, C13). ( B ) Differentially abundant miRNAs were used for cluster analysis based on the presence of interactions of target genes and pathways using DIANA-miRPath v3.0. Heatmap illustrates 12 miRNAs versus their associated pathways based on significance levels. Color scale from red (highest significance) to yellow (not significant). Image created with DIANA-miRPath v3.0 ( https://dianalab.e-ce.uth.gr/html/mirpathv3) and modified with Adobe Photoshop v.22.4.3.

Journal: Scientific Reports

Article Title: Uterine extracellular vesicles as multi-signal messengers during maternal recognition of pregnancy in the mare

doi: 10.1038/s41598-022-19958-z

Figure Lengend Snippet: Differential analysis of miRNAs in uEVs across samples and identification of enriched pathways for target genes of differentially abundant miRNAs. ( A ) Mean-centered log2 counts per million (cpm) values were calculated (log2 of CPM of respective sample – mean of all samples) for miRNAs differentially abundant (DA) across experimental groups (FDR 10%). Hierarchical cluster analysis (HCL) (Pearson correlation, MeV software) was performed for DA miRNAs (pregnancy days 10, 11, 12, and 13: P10, P11, P12, and P13; cyclic controls days 10 and 13 post-ovulation: C10, C13). ( B ) Differentially abundant miRNAs were used for cluster analysis based on the presence of interactions of target genes and pathways using DIANA-miRPath v3.0. Heatmap illustrates 12 miRNAs versus their associated pathways based on significance levels. Color scale from red (highest significance) to yellow (not significant). Image created with DIANA-miRPath v3.0 ( https://dianalab.e-ce.uth.gr/html/mirpathv3) and modified with Adobe Photoshop v.22.4.3.

Techniques: Software, Modification

Differential analysis of protein cargo in uEVs across samples. ( A ) Multidimensional scaling (MDS) plot of protein cargo in uEVs derived from pregnant and cyclic control mares. ( B ) Mean-centered log2 intensity values were calculated (value of respective sample – mean of all samples) for proteins differentially abundant (DA) across experimental groups (FDR 10%). Hierarchical cluster analysis (HCL) (Pearson correlation, MeV software) was performed for DA proteins (pregnancy days 10, 11, 12, and 13: P10, P11, P12, and P13; cyclic controls days 10 and 13 post-ovulation: C10, C13). (C) Self-organizing tree algorithm (SOTA) analysis was used to identify clusters of proteins with similar expression profiles. Six clusters containing proteins with similar profiles across experimental groups are shown, with six expression images showing the number of proteins and expression profiles in each SOTA cluster. Vertical axis: mean-centered expression values in log2 scale. MDS plot image was created with Bioconductor package EdgeR ( https://bioconductor.org/packages/release/bioc/html/edgeR.html) . HCL image and SOTA expression images were created with Multiple Experiment Viewer (MeV v.4.8.1, https://sourceforge.net/projects/mev-tm4/) and modified with Adobe Photoshop v.22.4.3. . Labelling of each sample refers to: day of pregnancy or cycle; followed by the number of EV sample from 1 to 24.

Journal: Scientific Reports

Article Title: Uterine extracellular vesicles as multi-signal messengers during maternal recognition of pregnancy in the mare

doi: 10.1038/s41598-022-19958-z

Figure Lengend Snippet: Differential analysis of protein cargo in uEVs across samples. ( A ) Multidimensional scaling (MDS) plot of protein cargo in uEVs derived from pregnant and cyclic control mares. ( B ) Mean-centered log2 intensity values were calculated (value of respective sample – mean of all samples) for proteins differentially abundant (DA) across experimental groups (FDR 10%). Hierarchical cluster analysis (HCL) (Pearson correlation, MeV software) was performed for DA proteins (pregnancy days 10, 11, 12, and 13: P10, P11, P12, and P13; cyclic controls days 10 and 13 post-ovulation: C10, C13). (C) Self-organizing tree algorithm (SOTA) analysis was used to identify clusters of proteins with similar expression profiles. Six clusters containing proteins with similar profiles across experimental groups are shown, with six expression images showing the number of proteins and expression profiles in each SOTA cluster. Vertical axis: mean-centered expression values in log2 scale. MDS plot image was created with Bioconductor package EdgeR ( https://bioconductor.org/packages/release/bioc/html/edgeR.html) . HCL image and SOTA expression images were created with Multiple Experiment Viewer (MeV v.4.8.1, https://sourceforge.net/projects/mev-tm4/) and modified with Adobe Photoshop v.22.4.3. . Labelling of each sample refers to: day of pregnancy or cycle; followed by the number of EV sample from 1 to 24.

Techniques: Derivative Assay, Control, Software, Expressing, Modification

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