Releases: openbiox/UCSCXenaShiny
Releases · openbiox/UCSCXenaShiny
UCSCXenaShiny 2.2.0
- Adapted
interleave(). - Added gene and pathway cross-omics analysis functions/modules.
- Added
app_run2()function for custom app start with lightweight modules. - Fixed
pdf()parameter for KM plot - Improved the UI of Custom TPC Modules.
- Removed a mistake by Yi Xiong for setting problematic threshold parameter in unicox analysis.
UCSCXenaShiny 2.2.0-zenodo
Merge pull request #351 from lishensuo/master Optimize some details
UCSCXenaShiny 2.1.0
- Handled error raised due to internet issue in CRAN check and tests.
- Optimized data preloading of Shiny application.
- Dockerfile updated.
UCSCXenaShiny 2.0.0
See the UCSCXenaShiny v2 Book for a comprehensive guidance.
New Features
Datasets
load_data("tcga_PW"): ssGSEA scores of HALLMARK, KEGG, IOBR terms for TCGA samples.load_data("tcga_PW_meta"): metadata annotation for HALLMARK, KEGG, IOBR terms.load_data("pcawg_TIL"): PCAWG TIL data.load_data("pcawg_PW"): ssGSEA scores of HALLMARK, KEGG, IOBR terms for PCAWG samples.- and more.
R Package Functions
.opt_pancan: Default setting for alternative TPC datasets.mol_quick_analysis(): Quick molecule analysis and report generation based on TCGA dataset.query_tcga_group(): Group TPC samples by build-in or custom phenotype and support filtering or merging operations.vis_dim_dist(): Visualize the distribution difference of TCGA samples after dimension reduction analysis.vis_identifier_dim_dist(): Visualize the distribution difference of samples after Molecule Identifier dimension reduction analysis.vis_toil_Mut(): Visualize molecular profile difference between mutation and wild status of queried gene.vis_toil_Mut_cancer(): Visualize molecular profile difference between mutation and wild status of queried gene in Single Cancer Type
Shiny application
-
Homepage
- Added slicker gallery to display page summary;
- Added report generation for TCGA pan-cancer exploration.
-
General Dataset Analysis
- Added one general dimension reduction analysis module.
-
Quick TPC Analysis
- Added one module for association analysis between molecule and pathway;
- Added one module for association analysis between molecule and mutation;
- Added one module for dimension reduction analysis.
-
Personalized Analysis
- Designed personalized TPC analysis pipelines for based on 3 methods and 3 modes.
-
Download
- Added two modules for exact subset of integrated TPC data and UCSCXena datasets.
Enhancements
- Supported getting more flexible methylation value.
UCSCXenaShiny::get_pancan_methylation_value(
"RCAN2",
rule_out = c("cg21115430", "cg19452802"),
aggr = "Q75"
)-
Supported installing the package from r-universe (https://openbiox.r-universe.dev/UCSCXenaShiny).
-
Supported alternative molecular profiling datasets for quick and personalized TPC analysis.
Bug Fixes
- Merged data with unequal size in pan-cancer data query with a gene signature (#283), the fix also enhance the sample names match.
Test code:
vis_gene_tmb_cor("`ZFAT-AS1` + `SNORD116-1` + SPATA31D1", data_type = "methylation")Release 1.1.10
Fixed check issue due to internet access (#253).
Release 1.1.9
- Added cancer type control for PCAWG survival analysis.
- Added TCGA batch id from MDA.
Release 1.1.8
Release 1.1.7
UCSCXenaShiny 1.1.7
- Added option
include.Tumor.onlyto control if include type - Set default theme if
flatlynot available. - Added example to generate radar plot, close #239
UCSCXenaShiny 1.1.6
- Added description of extra datasets.
UCSCXenaShiny 1.1.5
- Fixed survival KM plot output issue due to
ggsave()failure in General Analysis page. (#230)
Release 1.1.4
- Fixed the colnames being changed by
as.data.frame()when querying a symbol with unvalid R name. (Related to #234) - Added more informative error for scatter plot in General Analysis tab. (#233)
- Reversed default color setting for groups in survival analysis to fit conventional color grouping (in Xena).
(#232, thanks to feedback from Enrique) - Supported known science palette and custom colors for survival analysis in Quick PanCan Analysis tab.
Release 1.1.3
Latest docker image is available at https://hub.docker.com/r/shixiangwang/ucscxenashiny/tags/
Updates:
Committed and checked by Longfei, Yi Xiong and Shixiang.