Welcome to UCSCXenaShiny v2!
Thank you for using UCSCXenaShiny v2.2.0 based on UCSCXenaTools v1.5.0. Our web tool aims to povide a user-friendly platform to explore UCSC Xena datasets for both general and personalized cancer molecular research. If you have any questions during use, please do not hesitate to contact us via Github issue. If the tool has faciliated your research, welcome to cite our work. :)
Daily Gene
Pan-Cancer Query
2.Run two explorations:
※ Shiny Page Gallery
※ Example TCGA Modules: Quick analysis with easy steps
Module: Tumor and Normal Comparison
Compare one multi-omics molecular value between tumor and normal (including GTEx) samples.
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Module: Molecule-Molecule Correlation
Calculate the correlation of two multi-omics molecules acccording to their values in tumor samples.
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Module: Kaplan-Meier Survival Analysis
Perform the log-rank test analysis of one multi-omics molecule in tumor samples of one cancer type.
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※ Example TCGA pipelines: In-depth analysis with personalized steps
Pipelines: Comparison Analysis
Compare one of integrated identifiers (e.g. omis, non-omics, user-defined) based on two customizable groups of samples.
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Pipelines: Correlation Analysis
Calculate the correlation between any two of integrated identifiers (e.g. omis, non-omics, user-defined) among custom samples
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Pipelines: Survival Analysis
Perform log-rank test analysis for one of integrated identifiers based on two customizable groups of samples.
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※ Latest significant release notes
- 2024-06-25: Design gene and pathway cross-omics analysis
- 2024-02-14: Incorporate the PharmacoGenomics modules
- 2024-01-21: Adjust homepge with slick gallery to show basic page help.
- 2024-01-16: Introduce MSigDB genesets for molecule batch analysis.
- 2023-12-20: Add download modules that support data requisition.
- See more update logs in our Github .
TPC modules
Here, we introduced multiple custom modules for quick TPC molecule exploration with few steps. In general, 10 panels for common analytical scenario are available, as follows:
1. Box Layout
- The dashboard-based box layouts are adopted for simple and intuitive representation. The left box is usually for data selection and analytical parameters adjustment. The right box is usually for display of result plot and one sidebar panel can be pulled to adjust visualization options and download results.
2. Molecular database
We designate one specific UCSC Xena dataset for each molecular type of TPC databases. You can check the detailed information through the links below.
2.1 TCGA
- mRNA Expression —— TcgaTargetGtex_rsem_gene_tpm
- Transcript Expression —— TcgaTargetGtex_rsem_isoform_tpm
- DNA Methylation —— GDC-PANCAN.methylation450.tsv
- miRNA Expression —— pancanMiRs_EBadjOnProtocolPlatformWithoutRepsWithUnCorrectMiRs_08_04_16.xena
- Protein Expression —— TCGA-RPPA-pancan-clean.xena
- Copy Number Variation —— Gistic2_CopyNumber_Gistic2_all_data_by_genes
- Mutation status —— mc3.v0.2.8.PUBLIC.nonsilentGene.xena
PCAWG
- mRNA Expression —— tophat_star_fpkm_uq.v2_aliquot_gl.sp.log
- miRNA Expression —— x3t2m1.mature.TMM.mirna.matrix.log
- Promoter Activity —— rawPromoterActivity.sp
- Gene Fusion —— pcawg3_fusions_PKU_EBI.gene_centric.sp.xena
- APOBEC mutagenesis —— MAF_Aug31_2016_sorted_A3A_A3B_comparePlus.sp
CCLE
- mRNA Expression —— ccle/CCLE_DepMap_18Q2_RNAseq_RPKM_20180502
- Protein Expression —— ccle/CCLE_RPPA_20180123
- Copy Number Variation —— ccle/CCLE_copynumber_byGene_2013-12-03
Tips: The menu of
TPC Pipelinssupports more general and personalized TPC molecular analysis, including alternative datasets, precise data preparation and versatile modes.
Quick TCGA Analysis: Compare between tumor and normal
1. Select omics type
2. Select omics molecule
3. Select analysis mode
4. Include GTEx normal samples
Analytical results:
-
1. Visualization parameters
(1) Geometry type:
(2) Label type:
(3) Colors:
(4) ggplot theme:
2. Download options
(1) Figure:
(2) Data table:
Quick TCGA Analysis: Compare between tumor and normal
1. Select omics type
2. Select omics molecule
Analytical results:
-
1. Visualization parameters
(1) Gender:
2. Download options
(1) Figure:
(2) Data table:
Quick TCGA Analysis: Compare between mutation and wild tumor samples
1. Select omics type
2. Select omics molecule
3. Group by gene mutation
4. Select analysis mode
Analytical results:
-
1. Visualization parameters
(1) Geometry type:
(2) Label type:
(3) Colors:
2. Download options
(1) Figure:
(2) Data table:
Quick TCGA Analysis: Correlation in tumor samples
X-axis:
1. Select omics type
2. Select omics molecule
Y-axis:
1. Select omics type
2. Select omics molecule
3. Select TCGA cancer(s)
4. Select correlation method
5. Adjust tumor purity
Analytical results:
-
1. Visualization parameters
(1) Regression line:
(2) Point transparent:
(3) Point color:
(4) ggplot theme:
2. Download options
(1) Figure:
(2) Data table:
Quick TCGA Analysis: Correlation in tumor samples
1. Select omics type
2. Select omics molecule
3. Select TIL cell types
4. Select correlation method
Analytical results:
-
1. Visualization parameters
(1) Colors:
2. Download options
(1) Figure:
(2) Data table:
Quick TCGA Analysis: Correlation in tumor samples
1. Select omics type
2. Select omics molecule
3. Select TIL cell types
4. Select correlation method
Analytical results:
-
1. Visualization parameters
(1) Colors:
2. Download options
(1) Figure:
(2) Data table:
Quick TCGA Analysis: Correlation in tumor samples
1. Select omics type
2. Select omics molecule
3. Select fearture type
4. Select correlation method
Analytical results:
-
1. Visualization parameters
(1) Line color:
2. Download options
(1) Figure:
(2) Data table:
Quick TCGA Analysis: Correlation in tumor samples
1. Select omics type
2. Select omics molecule
3. Select one pathway
3. Select TCGA cancer(s)
4. Select correlation method
Analytical results:
-
1. Visualization parameters
(1) Regression line:
(2) Point transparent:
(3) Point color:
(4) ggplot theme:
2. Download options
(1) Figure:
(2) Data table:
Quick TCGA Analysis: Kaplan-Meier survival analysis(Log-rank)
1. Select omics type
2. Select omics molecule
3. Select TCGA cancer type and endpoint type
4. Filter by clinical features
5. Grouping by
Analytical results:
-
1. Visualization parameters
(1) Color palette:
2. Download options
(1) Figure:
(2) Data table:
Quick TCGA Analysis: Univariate Cox regression survival analysis
1. Select omics type
2. Select omics molecule
3. Select TCGA endpoint type
Analytical results:
-
1. Visualization parameters
(1) Color palette:
2. Download options
(1) Figure:
(2) Data table:
Analytical results:
-
1. Visualization parameters
(1) Marginal plot:
(2) Color palette:
2. Download options
(1) Figure:
(2) Data table:
Quick PCAWG Analysis: Compare between tumor and normal
1. Select omics type
2. Select omics molecule
Analytical results:
-
1. Visualization parameters
(1) Geometry type:
(2) Label type:
(3) Colors:
(4) ggplot theme:
2. Download options
(1) Figure:
(2) Data table:
Quick PCAWG Analysis: Correlation in tumor samples
X-axis:
1. Select omics type
2. Select omics molecule
Y-axis:
1. Select omics type
2. Select omics molecule
3. Select PCAWG project(s)
4. Select correlation method
5. Adjust tumor purity
Analytical results:
-
1. Visualization parameters
(1) Regression line:
(2) Point transparent:
(3) Point color:
(4) ggplot theme:
2. Download options
(1) Figure:
(2) Data table:
Quick PCAWG Analysis: Kaplan-Meier survival analysis(Log-rank)
1. Select omics type
2. Select omics molecule
3. Select PCAWG project (Only OS event)
4. Filter by clinical features
5. Grouping by
Analytical results:
-
1. Visualization parameters
(1) Color palette:
2. Download options
(1) Figure:
(2) Data table:
Quick PCAWG Analysis: Univariate Cox regression survival analysis
1. Select omics type
2. Select omics molecule
Analytical results:
-
1. Visualization parameters
(1) Color palette:
2. Download options
(1) Figure:
(2) Data table:
Quick CCLE Analysis: Compare across primary sites
1. Select omics type
2. Select omics molecule
Analytical results:
-
1. Visualization parameters
2. Download options
(1) Figure:
(2) Data table:
Quick CCLE Analysis: Correlation in cancer cell lines
X-axis:
1. Select omics type
2. Select omics molecule
Y-axis:
1. Select omics type
2. Select omics molecule
3. Select primary site(s)
4. Select correlation method
Analytical results:
-
1. Visualization parameters
(1) Regression line:
(2) Point transparent:
(3) Point color:
(4) ggplot theme:
2. Download options
(1) Figure:
(2) Data table:
Quick Analysis: Compare between tumor and normal
1. Select omics type
2. Select one gene list
3. Select X-axis type
Analytical results:
-
1. Visualization parameters
2. Download options
(1) Figure:
(2) Data table:
Quick Analysis: Compare between tumor and normal
1. Select omics type
2. Select one gene list
3. Select primary site(s)
Analytical results:
-
1. Visualization parameters
(1) Show P value:
(2) Colors:
(3) Point transparent:
2. Download options
(1) Figure:
(2) Data table:
TPC pipelines
Here, we introduced a series of personalized TPC pipelines for comprehensive and precise TPC molecule exploration with various operations. In general, 9 panels for common analytical scenario are available, as follows:
Generally, each analytical pipeline comprises of three main subpanels (S1, S2, S3).
- In S1 subpanel, you can prepare and select the expected data and sample ranges;
- In S2 subpanel, you can fetch the specific tumor data for downstream analysis;
- In S3 subpanel, you can execute the analysis, visualize and download results.
Tips: The menu of
TPC modulesenable specific and quick TPC molecular analysis, such as tumor and tomor comparison, molecule and molecule correlation.
TCGA Correlation Analysis
S1: Preset
S1.1 Modify datasets [opt]
No alternative datasets can be chosen.
No alternative datasets can be chosen.
No alternative datasets can be chosen.
No alternative datasets can be chosen.
S1.2 Choose cancer
S1.3 Filter samples [opt]
Quick filter:
Exact filter:
S1.4 Upload metadata [opt]
S1.5 Add signature [opt]
S2: Get data
S2.1 Get data for X-axis
S2.2 Get data for Y-axis
S3: Analyze & Visualize
S3.1 Set analysis parameters
S3.2 Set visualization parameters
S3.3 Download results
S1: Preset
S1.1 Modify datasets [opt]
No alternative datasets can be chosen.
No alternative datasets can be chosen.
No alternative datasets can be chosen.
No alternative datasets can be chosen.
S1.2 Choose cancers
S1.3 Filter samples [opt]
Quick filter:
Exact filter:
S1.4 Upload metadata [opt]
S1.5 Add signature [opt]
S2: Get data
S2.1 Get data for X-axis
S2.2 Get data for Y-axis
S3: Analyze & Visualize
S3.1 Set analysis parameters
S3.2 Set visualization parameters
S3.3 Download results
S1: Preset
S1.1 Modify datasets [opt]
No alternative datasets can be chosen.
No alternative datasets can be chosen.
No alternative datasets can be chosen.
No alternative datasets can be chosen.
S1.2 Choose cancer
S1.3 Filter samples [opt]
Quick filter:
Exact filter:
S1.4 Upload metadata [opt]
S1.5 Add signature [opt]
S3: Analyze
S3.1 Set analysis parameters
S3.2 Download results
TCGA Comparison Analysis
S1: Preset
S1.1 Modify datasets [opt]
No alternative datasets can be chosen.
No alternative datasets can be chosen.
No alternative datasets can be chosen.
No alternative datasets can be chosen.
S1.2 Choose cancer
S1.3 Filter samples [opt]
Quick filter:
Exact filter:
S1.4 Upload metadata [opt]
S1.5 Add signature [opt]
S2: Get data
S2.1 Divide 2 groups by one condition
S2.2 Get data for comparison
S3: Analyze & Visualize
S3.1 Set analysis parameters
S3.2 Set visualization parameters
S3.3 Download results
S1: Preset
S1.1 Modify datasets [opt]
No alternative datasets can be chosen.
No alternative datasets can be chosen.
No alternative datasets can be chosen.
No alternative datasets can be chosen.