Last updated on 2020-10-30 08:49:17 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.1.11 | 28.77 | 252.23 | 281.00 | WARN | |
| r-devel-linux-x86_64-debian-gcc | 0.1.11 | 19.62 | 189.42 | 209.04 | OK | |
| r-devel-linux-x86_64-fedora-clang | 0.1.11 | 341.62 | WARN | |||
| r-devel-linux-x86_64-fedora-gcc | 0.1.11 | 374.76 | OK | |||
| r-patched-solaris-x86 | 0.1.11 | 374.80 | WARN | |||
| r-release-linux-x86_64 | 0.1.11 | 24.35 | 235.29 | 259.64 | OK | |
| r-release-macos-x86_64 | 0.1.8 | WARN | ||||
| r-oldrel-macos-x86_64 | 0.1.11 | ERROR |
Version: 0.1.11
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: 'dittoSeq'
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.1.11
Check: re-building of vignette outputs
Result: WARN
Error(s) in re-building vignettes:
...
--- re-building 'introduction.Rmd' using knitr
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Attaching package: 'magrittr'
The following object is masked from 'package:purrr':
set_names
The following object is masked from 'package:tidyr':
extract
Attaching package: 'tidyseurat'
The following object is masked from 'package:Seurat':
pbmc_small
The following object is masked from 'package:magrittr':
extract
The following objects are masked from 'package:dplyr':
bind_cols, bind_rows, count
The following object is masked from 'package:stats':
filter
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
tidyseurat says: A data frame is returned for independent data analysis.
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
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Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
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Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in irlba(A = t(x = object), nv = npcs, ...) :
You're computing too large a percentage of total singular values, use a standard svd instead.
tidyseurat says: A data frame is returned for independent data analysis.
Calculating cluster 0
Calculating cluster 1
Calculating cluster 2
Calculating cluster 3
Warning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session
13:24:22 UMAP embedding parameters a = 0.9922 b = 1.112
13:24:22 Read 80 rows and found 15 numeric columns
13:24:22 Using Annoy for neighbor search, n_neighbors = 30
13:24:22 Building Annoy index with metric = cosine, n_trees = 50
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
13:24:22 Writing NN index file to temp file /tmp/RtmpzSsl2t/file28ac2ba8f311
13:24:22 Searching Annoy index using 1 thread, search_k = 3000
13:24:22 Annoy recall = 100%
13:24:23 Commencing smooth kNN distance calibration using 1 thread
13:24:23 Initializing from normalized Laplacian + noise
13:24:23 Commencing optimization for 500 epochs, with 2040 positive edges
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
13:24:24 Optimization finished
tidyseurat says: A data frame is returned for independent data analysis.
tidyseurat says: A data frame is returned for independent data analysis.
Quitting from lines 307-320 (./../man/fragments/intro.Rmd)
Quitting from lines 50-51 (./../man/fragments/intro.Rmd)
Error: processing vignette 'introduction.Rmd' failed with diagnostics:
Insufficient values in manual scale. 11 needed but only 4 provided.
--- failed re-building 'introduction.Rmd'
SUMMARY: processing the following file failed:
'introduction.Rmd'
Error: Vignette re-building failed.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.1.11
Check: package dependencies
Result: NOTE
Packages suggested but not available for checking:
'SingleCellSignalR', 'dittoSeq'
Flavors: r-devel-linux-x86_64-fedora-clang, r-patched-solaris-x86, r-oldrel-macos-x86_64
Version: 0.1.11
Check: re-building of vignette outputs
Result: WARN
Error(s) in re-building vignettes:
--- re-building ‘introduction.Rmd’ using knitr
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Attaching package: 'magrittr'
The following object is masked from 'package:purrr':
set_names
The following object is masked from 'package:tidyr':
extract
Attaching package: 'tidyseurat'
The following object is masked from 'package:Seurat':
pbmc_small
The following object is masked from 'package:magrittr':
extract
The following objects are masked from 'package:dplyr':
bind_cols, bind_rows, count
The following object is masked from 'package:stats':
filter
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
tidyseurat says: A data frame is returned for independent data analysis.
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
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Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in irlba(A = t(x = object), nv = npcs, ...) :
You're computing too large a percentage of total singular values, use a standard svd instead.
tidyseurat says: A data frame is returned for independent data analysis.
Calculating cluster 0
For a more efficient implementation of the Wilcoxon Rank Sum Test,
(default method for FindMarkers) please install the limma package
--------------------------------------------
install.packages('BiocManager')
BiocManager::install('limma')
--------------------------------------------
After installation of limma, Seurat will automatically use the more
efficient implementation (no further action necessary).
This message will be shown once per session
Calculating cluster 1
Calculating cluster 2
Calculating cluster 3
Warning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session
14:03:38 UMAP embedding parameters a = 0.9922 b = 1.112
14:03:38 Read 80 rows and found 15 numeric columns
14:03:38 Using Annoy for neighbor search, n_neighbors = 30
14:03:38 Building Annoy index with metric = cosine, n_trees = 50
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
14:03:38 Writing NN index file to temp file /tmp/RtmpbPEzuN/working_dir/Rtmpdh0Ne2/file1710856e7e229f
14:03:38 Searching Annoy index using 1 thread, search_k = 3000
14:03:39 Annoy recall = 100%
14:03:39 Commencing smooth kNN distance calibration using 1 thread
14:03:41 Initializing from normalized Laplacian + noise
14:03:41 Commencing optimization for 500 epochs, with 2040 positive edges
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
14:03:42 Optimization finished
tidyseurat says: A data frame is returned for independent data analysis.
tidyseurat says: A data frame is returned for independent data analysis.
Quitting from lines 307-320 (./../man/fragments/intro.Rmd)
Quitting from lines 50-51 (./../man/fragments/intro.Rmd)
Error: processing vignette 'introduction.Rmd' failed with diagnostics:
Insufficient values in manual scale. 11 needed but only 4 provided.
--- failed re-building ‘introduction.Rmd’
SUMMARY: processing the following file failed:
‘introduction.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.1.11
Check: re-building of vignette outputs
Result: WARN
Error(s) in re-building vignettes:
...
--- re-building ‘introduction.Rmd’ using knitr
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Attaching package: 'magrittr'
The following object is masked from 'package:purrr':
set_names
The following object is masked from 'package:tidyr':
extract
Attaching package: 'tidyseurat'
The following object is masked from 'package:Seurat':
pbmc_small
The following object is masked from 'package:magrittr':
extract
The following objects are masked from 'package:dplyr':
bind_cols, bind_rows, count
The following object is masked from 'package:stats':
filter
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
tidyseurat says: A data frame is returned for independent data analysis.
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
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Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in irlba(A = t(x = object), nv = npcs, ...) :
You're computing too large a percentage of total singular values, use a standard svd instead.
tidyseurat says: A data frame is returned for independent data analysis.
Calculating cluster 0
For a more efficient implementation of the Wilcoxon Rank Sum Test,
(default method for FindMarkers) please install the limma package
--------------------------------------------
install.packages('BiocManager')
BiocManager::install('limma')
--------------------------------------------
After installation of limma, Seurat will automatically use the more
efficient implementation (no further action necessary).
This message will be shown once per session
Calculating cluster 1
Calculating cluster 2
Calculating cluster 3
Warning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session
09:18:40 UMAP embedding parameters a = 0.9922 b = 1.112
09:18:40 Read 80 rows and found 15 numeric columns
09:18:40 Using Annoy for neighbor search, n_neighbors = 30
09:18:40 Building Annoy index with metric = cosine, n_trees = 50
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
09:18:40 Writing NN index file to temp file /tmp/Rtmp5Da41x/working_dir/RtmpkRaijW/file6049731346f7
09:18:40 Searching Annoy index using 1 thread, search_k = 3000
09:18:40 Annoy recall = 100%
09:18:41 Commencing smooth kNN distance calibration using 1 thread
09:18:41 Initializing from normalized Laplacian + noise
09:18:42 Commencing optimization for 500 epochs, with 2040 positive edges
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
09:18:42 Optimization finished
tidyseurat says: A data frame is returned for independent data analysis.
tidyseurat says: A data frame is returned for independent data analysis.
Quitting from lines 307-320 (./../man/fragments/intro.Rmd)
Quitting from lines 50-51 (./../man/fragments/intro.Rmd)
Error: processing vignette 'introduction.Rmd' failed with diagnostics:
Insufficient values in manual scale. 11 needed but only 4 provided.
--- failed re-building ‘introduction.Rmd’
SUMMARY: processing the following file failed:
‘introduction.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavor: r-patched-solaris-x86
Version: 0.1.8
Check: package dependencies
Result: NOTE
Packages suggested but not available for checking:
'SingleCellSignalR', 'dittoSeq'
Flavor: r-release-macos-x86_64
Version: 0.1.8
Check: re-building of vignette outputs
Result: WARN
Error(s) in re-building vignettes:
--- re-building ‘introduction.Rmd’ using knitr
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Attaching package: 'magrittr'
The following object is masked from 'package:purrr':
set_names
The following object is masked from 'package:tidyr':
extract
Attaching package: 'tidyseurat'
The following object is masked from 'package:Seurat':
pbmc_small
The following object is masked from 'package:ggplot2':
ggplot
The following object is masked from 'package:magrittr':
extract
The following objects are masked from 'package:tidyr':
as_tibble, extract, nest, pivot_longer, separate, unite, unnest
The following objects are masked from 'package:dplyr':
arrange, as_tibble, bind_cols, bind_rows, count, distinct, filter,
full_join, group_by, inner_join, left_join, mutate, pull, rename,
right_join, rowwise, sample_frac, sample_n, select, slice,
summarise
The following object is masked from 'package:stats':
filter
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
tidyseurat says: A data frame is returned for independent data analysis.
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
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Warning in sqrt(1/i) : NaNs produced
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Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in sqrt(1/i) : NaNs produced
Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
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Warning in theta.ml(y = y, mu = fit$fitted) : iteration limit reached
Warning in irlba(A = t(x = object), nv = npcs, ...) :
You're computing too large a percentage of total singular values, use a standard svd instead.
tidyseurat says: A data frame is returned for independent data analysis.
Calculating cluster 0
Calculating cluster 1
Calculating cluster 2
Calculating cluster 3
Warning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session
07:10:52 UMAP embedding parameters a = 0.9922 b = 1.112
07:10:52 Read 80 rows and found 15 numeric columns
07:10:52 Using Annoy for neighbor search, n_neighbors = 30
07:10:52 Building Annoy index with metric = cosine, n_trees = 50
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
07:10:52 Writing NN index file to temp file /Volumes/Temp/tmp/Rtmp2PYENS/filec4e13fa7acec
07:10:52 Searching Annoy index using 1 thread, search_k = 3000
07:10:52 Annoy recall = 100%
07:10:52 Commencing smooth kNN distance calibration using 1 thread
07:10:53 Initializing from normalized Laplacian + noise
07:10:53 Commencing optimization for 500 epochs, with 2058 positive edges
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
07:10:53 Optimization finished
tidyseurat says: A data frame is returned for independent data analysis.
tidyseurat says: A data frame is returned for independent data analysis.
Quitting from lines 307-320 (./../man/fragments/intro.Rmd)
Quitting from lines 50-51 (./../man/fragments/intro.Rmd)
Error: processing vignette 'introduction.Rmd' failed with diagnostics:
Insufficient values in manual scale. 11 needed but only 4 provided.
--- failed re-building ‘introduction.Rmd’
SUMMARY: processing the following file failed:
‘introduction.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavor: r-release-macos-x86_64
Version: 0.1.11
Check: whether package can be installed
Result: ERROR
Installation failed.
Flavor: r-oldrel-macos-x86_64