IOBR is an R package to perform comprehensive analysis of tumor microenvironment and signatures for immuno-oncology.
-
- IOBR collects 255 published signature gene sets, involving tumor
microenvironment, tumor metabolism, m6A, exosomes,
microsatellite instability, and tertiary lymphoid structure.
Running the function
signature_collection_citation
to attain the source papers. The functionsignature_collection
returns the detail signature genes of all given signatures.
- IOBR collects 255 published signature gene sets, involving tumor
microenvironment, tumor metabolism, m6A, exosomes,
microsatellite instability, and tertiary lymphoid structure.
Running the function
-
- IOBR integrates 8 published methodologies decoding tumor
microenvironment (TME) contexture:
CIBERSORT
,TIMER
,xCell
,MCPcounter
,ESITMATE
,EPIC
,IPS
,quanTIseq
;
- IOBR integrates 8 published methodologies decoding tumor
microenvironment (TME) contexture:
-
- IOBR adopts three computational methods to calculate the
signature score, comprising
PCA
,z-score
, andssGSEA
;
- IOBR adopts three computational methods to calculate the
signature score, comprising
-
- IOBR integrates multiple approaches for variable transition, visualization, batch survival analysis, feature selection, and statistical analysis.
-
- IOBR also integrates methods for batch visualization of subgroup characteristics.
It is essential that you have R 3.6.3 or above already installed on your computer or server. IOBR utilizes many other R packages that are currently available from CRAN, Bioconductor and GitHub. Before installing IOBR, please install all dependencies by executing the following command in R console:
The dependencies includs tibble
, survival
, survminer
, limma
,
limSolve
, GSVA
, e1071
, preprocessCore
, ggplot2
and ggpubr
.
# options("repos"= c(CRAN="https://mirrors.tuna.tsinghua.edu.cn/CRAN/"))
# options(BioC_mirror="http://mirrors.tuna.tsinghua.edu.cn/bioconductor/")
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")
#> Bioconductor version '3.12' is out-of-date; the current release version '3.13'
#> is available with R version '4.1'; see https://bioconductor.org/install
depens<-c('tibble', 'survival', 'survminer', 'sva', 'limma', "DESeq2","devtools",
'limSolve', 'GSVA', 'e1071', 'preprocessCore', 'ggplot2', "biomaRt",
'ggpubr', "devtools", "tidyHeatmap", "caret", "glmnet", "ppcor", "timeROC","pracma")
for(i in 1:length(depens)){
depen<-depens[i]
if (!requireNamespace(depen, quietly = TRUE))
BiocManager::install(depen,update = FALSE)
}
The package is not yet on CRAN or Bioconductor. You can install it from Github:
if (!requireNamespace("IOBR", quietly = TRUE))
devtools::install_github("IOBR/IOBR")
Library R packages
library(IOBR)
IOBR pipeline diagram below outlines the data processing flow of this package, and detailed guidance of how to use IOBR could be found in the GitHub vignette or HTML vignette.
tme_deconvolution_methods
#> MCPcounter EPIC xCell CIBERSORT
#> "mcpcounter" "epic" "xcell" "cibersort"
#> CIBERSORT Absolute IPS ESTIMATE SVR
#> "cibersort_abs" "ips" "estimate" "svr"
#> lsei TIMER quanTIseq
#> "lsei" "timer" "quantiseq"
# Return available parameter options of TME deconvolution.
If you use this package in your work, please cite both our package and the method(s) you are using.
method | license | citation |
---|---|---|
CIBERSORT | free for non-commerical use only | Newman, A. M., Liu, C. L., Green, M. R., Gentles, A. J., Feng, W., Xu, Y., … Alizadeh, A. A. (2015). Robust enumeration of cell subsets from tissue expression profiles. Nature Methods, 12(5), 453–457. https://doi.org/10.1038/nmeth.3337 |
ESTIMATE | free (GPL2.0) | Vegesna R, Kim H, Torres-Garcia W, …, Verhaak R. (2013). Inferring tumour purity and stromal and immune cell admixture from expression data. Nature Communications 4, 2612. http://doi.org/10.1038/ncomms3612 |
quanTIseq | free (BSD) | Finotello, F., Mayer, C., Plattner, C., Laschober, G., Rieder, D., Hackl, H., …, Sopper, S. (2019). Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data. Genome medicine, 11(1), 34. https://doi.org/10.1186/s13073-019-0638-6 |
TIMER | free (GPL 2.0) | Li, B., Severson, E., Pignon, J.-C., Zhao, H., Li, T., Novak, J., … Liu, X. S. (2016). Comprehensive analyses of tumor immunity: implications for cancer immunotherapy. Genome Biology, 17(1), 174. https://doi.org/10.1186/s13059-016-1028-7 |
IPS | free (BSD) | P. Charoentong et al., Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade. Cell Reports 18, 248-262 (2017). https://doi.org/10.1016/j.celrep.2016.12.019 |
MCPCounter | free (GPL 3.0) | Becht, E., Giraldo, N. A., Lacroix, L., Buttard, B., Elarouci, N., Petitprez, F., … de Reyniès, A. (2016). Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression. Genome Biology, 17(1), 218. https://doi.org/10.1186/s13059-016-1070-5 |
xCell | free (GPL 3.0) | Aran, D., Hu, Z., & Butte, A. J. (2017). xCell: digitally portraying the tissue cellular heterogeneity landscape. Genome Biology, 18(1), 220. https://doi.org/10.1186/s13059-017-1349-1 |
EPIC | free for non-commercial use only (Academic License) | Racle, J., de Jonge, K., Baumgaertner, P., Speiser, D. E., & Gfeller, D. (2017). Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data. ELife, 6, e26476. https://doi.org/10.7554/eLife.26476 |
signature_score_calculation_methods
#> PCA ssGSEA z-score Integration
#> "pca" "ssgsea" "zscore" "integration"
# Return available parameter options of signature estimation.
method | license | citation |
---|---|---|
GSVA | free (GPL (>= 2)) | Hänzelmann S, Castelo R, Guinney J (2013). “GSVA: gene set variation analysis for microarray and RNA-Seq data.” BMC Bioinformatics, 14, 7. doi: 10.1186/1471-2105-14-7, http://www.biomedcentral.com/1471-2105/14/7 |
#References of collected signatures
signature_collection_citation[!duplicated(signature_collection_citation$Journal),]
#> # A tibble: 19 x 6
#> Signatures `Published year` Journal Title PMID DOI
#> <chr> <dbl> <chr> <chr> <chr> <chr>
#> 1 CD_8_T_effector 2018 Nature TGFβ attenuate~ 2944~ 10.1038~
#> 2 TMEscoreA_CIR 2019 Cancer Immu~ Tumor Microenv~ 3084~ 10.1158~
#> 3 CD8_Rooney_et_al 2015 Cell Molecular and ~ 2559~ 10.1016~
#> 4 T_cell_inflamed~ 2017 The Journal~ IFN-γ–related ~ 2865~ 10.1172~
#> 5 MDSC_Wang_et_al 2016 Canccer Dis~ Targeting YAP-~ 2670~ 10.1158~
#> 6 B_cells_Danaher~ 2017 Journal for~ Gene expressio~ 2823~ 10.1186~
#> 7 Nature_metaboli~ 2019 Nature Meta~ Characterizati~ 3198~ 10.1038~
#> 8 Winter_hypoxia_~ 2007 Cancer Rese~ Relation of a ~ 1740~ 10.1158~
#> 9 Hu_hypoxia_sign~ 2019 Molecular B~ The Genome Lan~ 3044~ 10.1093~
#> 10 MT_exosome 2019 Molecular T~ An EV-Associat~ 3147~ 10.1016~
#> 11 SR_exosome 2017 Scientific ~ Genetic Mutati~ 2838~ 10.1038~
#> 12 MC_Review_Exoso~ 2016 Molcular Ca~ Diagnostic, Pr~ 2718~ 10.1186~
#> 13 CMLS_Review_Exo~ 2018 Cellular an~ Current knowle~ 2873~ 10.1007~
#> 14 Positive_regula~ 2020 Gene Ontolo~ http://geneont~ <NA> <NA>
#> 15 Molecular_Cance~ 2020 Molecular C~ m6A regulator-~ <NA> 10.1186~
#> 16 Ferroptosis 2020 IOBR Constructed by~ <NA> <NA>
#> 17 T_cell_accumula~ 2018 Nature Medi~ Signatures of ~ 3012~ 10.1038~
#> 18 Antigen_Process~ 2020 Nature Comm~ Pan-cancer Cha~ 3208~ 10.1038~
#> 19 CD8_T_cells_Bin~ 2013 Immunity Spatio-tempora~ 2413~ 10.1016~
#signature groups
sig_group[1:3]
#> $tumor_signature
#> [1] "CellCycle_Reg"
#> [2] "Cell_cycle"
#> [3] "DDR"
#> [4] "Mismatch_Repair"
#> [5] "Histones"
#> [6] "Homologous_recombination"
#> [7] "Nature_metabolism_Hypoxia"
#> [8] "Molecular_Cancer_m6A"
#> [9] "MT_exosome"
#> [10] "Positive_regulation_of_exosomal_secretion"
#> [11] "Ferroptosis"
#> [12] "EV_Cell_2020"
#>
#> $EMT
#> [1] "Pan_F_TBRs" "EMT1" "EMT2" "EMT3" "WNT_target"
#>
#> $io_biomarkers
#> [1] "TMEscore_CIR" "TMEscoreA_CIR"
#> [3] "TMEscoreB_CIR" "T_cell_inflamed_GEP_Ayers_et_al"
#> [5] "CD_8_T_effector" "IPS_IPS"
#> [7] "Immune_Checkpoint" "Exhausted_CD8_Danaher_et_al"
#> [9] "Pan_F_TBRs" "Mismatch_Repair"
#> [11] "APM"
Zeng D, Ye Z, Shen R, Yu G, Wu J, Xiong Y,…, Liao W (2021) IOBR: Multi-Omics Immuno-Oncology Biological Research to Decode Tumor Microenvironment and Signatures. Frontiers in Immunology. 12:687975. doi: 10.3389/fimmu.2021.687975
Please report bugs to the Github issues page
E-mail any questions to [email protected]