By using GEPIA2, experimental biologists can easily explore the large TCGA and GTEx datasets, ask specific questions, and test their hypotheses in a higher resolution.
For the isoform analysis in boxplot and survival analyses, users can easily get the result that POMT1-003 isoform in ACC cancer type was over expressed compared with the normal tissue. Meanwhile, given the high expression of POMT1-003 isoform, the patients in ACC had a worse prognostic outcome.
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In addition, based on the Isoform Usage, users can find that SLC7A2-202 in SLC7A2 gene has a isoform switch event in LIHC compared with other cancer types.
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Users also can use Isoform Structure find that 3 isoforms in ERCC1 have different isoform structures.
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For Survival Map, users can get the survival significance map of gene HSPB6, which have significant results in BLCA, KIRP, LGG and SARC.
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For gene signature analysis in similar genes detection, users can find that MIR155HG, CD8A, IL21R, CD27 and PTPN7 have highest correlation with T-cell exhausted signature in LIHC cancer type.
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For the combination of signature and subtype analysis in boxplot, GEPIA2 provides the expression distribution of Th-1 like signature in the 3 COAD subtypes.
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For analyzing the user-upload data, the features in custom data analysis enables users classify their uploaded data into cancer subtype or compare their own data with TCGA and GTEx data.
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For doing the analyses in the local machine, GEPIA2 provides the python package gepia in API. Users can get the batch of analysis results using this package.
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GEPIA2 also retained the original features of GEPIA:
In differential analysis and expression profile, users can easily discover differentially expressed genes, such as MPO in leukemia and UPK2 in bladder cancer.
MPO specifically expressed in leukemia:
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UPK2 specifically expressed in bladder cancer:
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The chromosomal distribution of over- or under- expressed genes can be plotted in Differential Genes.
Over-expressed genes:
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Under-expressed genes:
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Both over-expressed and under-expressed genes:
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In Survival analysis, genes with the most significant association with patient survival can be identified, such as MCTS1 in breast cancer and HILPDA in liver cancer. Code
MCTS1 in breast cancer
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HILPDA in liver cancer:
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Gene expression is visualized by both a bodymap and a bar plot in General.
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Gene expression by pathological stage is plotted in Stage plot. Code
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Users can compare the expression of one gene in multiple cancers by Boxplot, or compare multiple genes by a matrix plot in Multiple gene comparison. Code
Boxplot:
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Matrix plot:
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GEPIA provides pair-wise gene correlation analysis of a given set of TCGA and/or GTEx expression data. Normalization is optional and customizable. Code
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GEPIA provides Principal Component Analysis of multiple genes and cancer types in PCA, and presents results by 2D or 3D plots.
2D plots:
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3D plots:
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Variances distribution:
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Genes with similar expression pattern can be identified in Similar Genes, for example, PGAP3 and GRB7 are similar to ERBB2.
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ERBB2:
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PGAP3:
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GRB7:
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