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Table 1.

Final merged dataset and training and validation sets.

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Table 1 Expand

Fig 1.

Venn diagram showing the overlap and discrepancies between genes differentially expressed in Clarkson et al. [3] and Stein et al. [4].

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Fig 1 Expand

Fig 2.

The log2 fold change in gene expression profiles for the ten significant clusters identified through the STEM Clustering.

Y-axis represents the relative gene expression levels of involution days 0.5, 1, 2, 3 and 4 days compared lactation day 10 in log base 2 scale. X-axis represents the time points (L10, lactation day 10; I12h, involution day 0.5; I24h, involution day 1; I48h, involution day 2; I72h, involution day 3; I96h, involution day 4). SOCS3, suppressor of cytokine signaling 3; IGF1, insulin-like growth factor 1 (somatomedin C); STAT3, signal transducer and activator of transcription 3 (acute-phase response factor); TGFB3, transforming growth factor, beta 3; ATF4, activating transcription factor 4; IGFBP5, insulin-like growth factor binding protein 5; MMP3, matrix metallopeptidase 3.

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Fig 2 Expand

Table 2.

Patterns, size and p-values of significant clusters identified through the STEM algorithm using data from Clarkson et al. [3].

The far right column indicates Involution Specific Gene Signatures through the STEM clustering using data from Clarkson et al. [3].

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Table 2 Expand

Fig 3.

Enrichment plots form GSEA for Inv5 signature for IBC versus non-IBC in the training and validation sets.

nIBC, non-Inflammatory breast cancer.

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Fig 3 Expand

Table 3.

GSEA results of involution-specific signatures in IBC versus non-IBC in the training and validation sets.

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Table 3 Expand

Table 4.

GSEA results of involution-specific signatures in IBC versus non-IBC in the merged 3 breast cancer data sets.

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Table 4 Expand

Table 5.

List of genes in Inv5 signature and genes enriched in IBC versus non-IBC.

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Table 5 Expand