Last updated on 2026-10-24 01:51:46 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.3.2 | 9.29 | 109.97 | 119.26 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.3.2 | 7.07 | 71.04 | 78.11 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.3.2 | 84.60 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 1.3.2 | 86.76 | OK | |||
| r-devel-windows-x86_64 | 1.3.2 | 13.00 | 125.00 | 138.00 | OK | |
| r-patched-linux-x86_64 | 1.3.2 | 11.19 | 103.81 | 115.00 | OK | |
| r-release-linux-x86_64 | 1.3.2 | 8.77 | 104.59 | 113.36 | OK | |
| r-release-macos-arm64 | 1.3.2 | 3.00 | 32.00 | 35.00 | OK | |
| r-release-macos-x86_64 | 1.3.2 | 7.00 | 120.00 | 127.00 | OK | |
| r-release-windows-x86_64 | 1.3.2 | 13.00 | 123.00 | 136.00 | OK | |
| r-oldrel-macos-arm64 | 1.3.2 | OK | ||||
| r-oldrel-macos-x86_64 | 1.3.2 | 7.00 | 131.00 | 138.00 | OK | |
| r-oldrel-windows-x86_64 | 1.3.2 | 16.00 | 150.00 | 166.00 | OK |
Version: 1.3.2
Check: examples
Result: ERROR
Running examples in ‘SIMMS-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: SIMMS-package
> ### Title: SIMMS - Subnetwork Integration for Multi-Modal Signatures
> ### Aliases: SIMMS-package SIMMS
> ### Keywords: package
>
> ### ** Examples
>
>
> options("warn" = -1);
>
> # get data directory
> data.directory <- get.program.defaults(networks.database = "test")[["test.data.dir"]];
>
> # initialise params
> output.directory <- tempdir();
> data.types <- c("mRNA");
> feature.selection.datasets <- c("Breastdata1");
> training.datasets <- c("Breastdata1");
> validation.datasets <- c("Breastdata2");
> feature.selection.p.thresholds <- c(0.5);
> feature.selection.p.threshold <- 0.5;
> learning.algorithms <- c("backward", "forward", "glm");
> top.n.features <- 5;
>
> # compute network HRs for all the subnet features
> derive.network.features(
+ data.directory = data.directory,
+ output.directory = output.directory,
+ data.types = data.types,
+ feature.selection.datasets = feature.selection.datasets,
+ feature.selection.p.thresholds = feature.selection.p.thresholds,
+ networks.database = "test"
+ );
>
> # preparing training and validation datasets.
> # Normalisation & patientwise subnet feature scores
> prepare.training.validation.datasets(
+ data.directory = data.directory,
+ output.directory = output.directory,
+ data.types = data.types,
+ p.threshold = feature.selection.p.threshold,
+ feature.selection.datasets = feature.selection.datasets,
+ datasets = unique(c(training.datasets, validation.datasets)),
+ networks.database = "test"
+ );
>
> # create classifier assessing univariate prognostic power of subnetwork modules (Train and Validate)
> create.classifier.univariate(
+ data.directory = data.directory,
+ output.directory = output.directory,
+ feature.selection.datasets = feature.selection.datasets,
+ feature.selection.p.threshold = feature.selection.p.threshold,
+ training.datasets = training.datasets,
+ validation.datasets = validation.datasets,
+ top.n.features = top.n.features
+ );
skipping cox model as less than 2 levels found in groups
skipping cox model as less than 2 levels found in groups
skipping cox model as less than 2 levels found in groups
skipping cox model as less than 2 levels found in groups
skipping cox model as less than 2 levels found in groups
skipping cox model as less than 2 levels found in groups
skipping cox model as less than 2 levels found in groups
skipping cox model as less than 2 levels found in groups>
> # create a multivariate classifier (Train and Validate)
> create.classifier.multivariate(
+ data.directory = data.directory,
+ output.directory = output.directory,
+ feature.selection.datasets = feature.selection.datasets,
+ feature.selection.p.threshold = feature.selection.p.threshold,
+ training.datasets = training.datasets,
+ validation.datasets = validation.datasets,
+ learning.algorithms = learning.algorithms,
+ top.n.features = top.n.features
+ );
***************** starting fit Model 1 backward *****************
Surv(survtime, survstat) ~ X.ID.100002_1.NAME.wnt.signaling.pathway +
X.ID.100012_1.NAME.tpo.signaling.pathway + X.ID.100010_1.NAME.tsp.1.induced.apoptosis.in.microvascular.endothelial.cell +
X.ID.500008_1.NAME.ER.PGR.ERBB2.MKI67 + X.ID.100013_3.NAME.toll.like.receptor.pathway
<environment: 0x55b796f70aa8>
Start: AIC=28.26
Surv(survtime, survstat) ~ X.ID.100002_1.NAME.wnt.signaling.pathway +
X.ID.100012_1.NAME.tpo.signaling.pathway + X.ID.100010_1.NAME.tsp.1.induced.apoptosis.in.microvascular.endothelial.cell +
X.ID.500008_1.NAME.ER.PGR.ERBB2.MKI67 + X.ID.100013_3.NAME.toll.like.receptor.pathway
Df
- X.ID.500008_1.NAME.ER.PGR.ERBB2.MKI67 1
- X.ID.100013_3.NAME.toll.like.receptor.pathway 1
- X.ID.100010_1.NAME.tsp.1.induced.apoptosis.in.microvascular.endothelial.cell 1
<none>
- X.ID.100012_1.NAME.tpo.signaling.pathway 1
- X.ID.100002_1.NAME.wnt.signaling.pathway 1
AIC
- X.ID.500008_1.NAME.ER.PGR.ERBB2.MKI67 26.272
- X.ID.100013_3.NAME.toll.like.receptor.pathway 26.290
- X.ID.100010_1.NAME.tsp.1.induced.apoptosis.in.microvascular.endothelial.cell 27.148
<none> 28.256
- X.ID.100012_1.NAME.tpo.signaling.pathway 29.344
- X.ID.100002_1.NAME.wnt.signaling.pathway 39.483
Step: AIC=26.27
Surv(survtime, survstat) ~ X.ID.100002_1.NAME.wnt.signaling.pathway +
X.ID.100012_1.NAME.tpo.signaling.pathway + X.ID.100010_1.NAME.tsp.1.induced.apoptosis.in.microvascular.endothelial.cell +
X.ID.100013_3.NAME.toll.like.receptor.pathway
Df
- X.ID.100013_3.NAME.toll.like.receptor.pathway 1
- X.ID.100010_1.NAME.tsp.1.induced.apoptosis.in.microvascular.endothelial.cell 1
<none>
- X.ID.100012_1.NAME.tpo.signaling.pathway 1
- X.ID.100002_1.NAME.wnt.signaling.pathway 1
AIC
- X.ID.100013_3.NAME.toll.like.receptor.pathway 24.299
- X.ID.100010_1.NAME.tsp.1.induced.apoptosis.in.microvascular.endothelial.cell 25.234
<none> 26.272
- X.ID.100012_1.NAME.tpo.signaling.pathway 27.349
- X.ID.100002_1.NAME.wnt.signaling.pathway 38.581
Step: AIC=24.3
Surv(survtime, survstat) ~ X.ID.100002_1.NAME.wnt.signaling.pathway +
X.ID.100012_1.NAME.tpo.signaling.pathway + X.ID.100010_1.NAME.tsp.1.induced.apoptosis.in.microvascular.endothelial.cell
Df
- X.ID.100010_1.NAME.tsp.1.induced.apoptosis.in.microvascular.endothelial.cell 1
<none>
- X.ID.100012_1.NAME.tpo.signaling.pathway 1
- X.ID.100002_1.NAME.wnt.signaling.pathway 1
AIC
- X.ID.100010_1.NAME.tsp.1.induced.apoptosis.in.microvascular.endothelial.cell 23.647
<none> 24.299
- X.ID.100012_1.NAME.tpo.signaling.pathway 25.364
- X.ID.100002_1.NAME.wnt.signaling.pathway 37.229
Step: AIC=23.65
Surv(survtime, survstat) ~ X.ID.100002_1.NAME.wnt.signaling.pathway +
X.ID.100012_1.NAME.tpo.signaling.pathway
Df AIC
<none> 23.647
- X.ID.100012_1.NAME.tpo.signaling.pathway 1 30.895
- X.ID.100002_1.NAME.wnt.signaling.pathway 1 35.650
storing StepAIC results for: 1
storing AIC TRACE, the last one being the AIC of the final modelError in a$specials[[i]] : subscript out of bounds
Calls: create.classifier.multivariate -> predict -> predict.coxph -> delete.response -> off
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.3.2
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
...
--- re-building ‘Using-SIMMS.Rmd’ using rmarkdown
Quitting from Using-SIMMS.Rmd:124-232 [unnamed-chunk-1]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
<error/rlang_error>
Error in `a$specials[[i]]`:
! subscript out of bounds
---
Backtrace:
▆
1. └─SIMMS::create.classifier.multivariate(...)
2. ├─stats::predict(model.fit, newdata = new.data, type = "risk")
3. └─survival:::predict.coxph(model.fit, newdata = new.data, type = "risk")
4. └─stats::delete.response(Terms)
5. └─stats (local) off(a$specials[[i]])
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Error: processing vignette 'Using-SIMMS.Rmd' failed with diagnostics:
subscript out of bounds
--- failed re-building ‘Using-SIMMS.Rmd’
SUMMARY: processing the following file failed:
‘Using-SIMMS.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc