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BUILD report for tidybulk on tokay1

This page was generated on 2021-05-06 12:33:57 -0400 (Thu, 06 May 2021).

To the developers/maintainers of the tidybulk package:
Please make sure to use the following settings in order to reproduce any error or warning you see on this page.
Package 1855/1974HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
tidybulk 1.2.1  (landing page)
Stefano Mangiola
Snapshot Date: 2021-05-05 14:51:38 -0400 (Wed, 05 May 2021)
URL: https://git.bioconductor.org/packages/tidybulk
Branch: RELEASE_3_12
Last Commit: 15d7391
Last Changed Date: 2021-04-06 00:58:01 -0400 (Tue, 06 Apr 2021)
malbec1Linux (Ubuntu 18.04.5 LTS) / x86_64  OK    ERROR  skipped
tokay1Windows Server 2012 R2 Standard / x64  OK    ERROR  skippedskipped
merida1macOS 10.14.6 Mojave / x86_64  OK    ERROR  skippedskipped

Summary

Package: tidybulk
Version: 1.2.1
Command: chmod a+r tidybulk -R && C:\Users\biocbuild\bbs-3.12-bioc\R\bin\R.exe CMD build --keep-empty-dirs --no-resave-data tidybulk
StartedAt: 2021-05-05 23:51:27 -0400 (Wed, 05 May 2021)
EndedAt: 2021-05-05 23:53:54 -0400 (Wed, 05 May 2021)
EllapsedTime: 146.8 seconds
RetCode: 1
Status:   ERROR   
PackageFile: None
PackageFileSize: NA

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   chmod a+r tidybulk -R && C:\Users\biocbuild\bbs-3.12-bioc\R\bin\R.exe CMD build --keep-empty-dirs --no-resave-data tidybulk
###
##############################################################################
##############################################################################


* checking for file 'tidybulk/DESCRIPTION' ... OK
* preparing 'tidybulk':
* checking DESCRIPTION meta-information ... OK
* installing the package to process help pages
* building the PDF package manual
Hmm ... looks like a package
Converting Rd files to LaTeX ...........
Creating pdf output from LaTeX ...
Saving output to 'C:/Users/biocbuild/bbs-3.12-bioc/tmpdir/RtmpIh231x/Rbuild1e643a925725/tidybulk/build/tidybulk.pdf' ...
Done
* creating vignettes ... ERROR
--- re-building 'comparison_with_base_R.Rmd' using knitr
Warning in aggregate_duplicated_transcripts_bulk(.data, .sample = !!.sample,  :
  tidybulk says: for aggregation, factors and logical columns were converted to character
Converted to characters
logical
Getting the 500 most variable genes
tidybulk says: to access the raw results do `attr(..., "internals")$MDS`
Getting the 393 most variable genes
Fraction of variance explained by the selected principal components
# A tibble: 2 x 2
  `Fraction of variance`    PC
                   <dbl> <int>
1                  0.581     1
2                  0.321     2
tidybulk says: to access the raw results do `attr(..., "internals")$PCA`
No group or design set. Assuming all samples belong to one group.
Warning in eliminate_sparse_transcripts(., !!.feature) :
  tidybulk says: Some transcripts have been omitted from the analysis because not present in every sample.
Getting the 488 most variable genes
=====================================
tidybulk says: All testing methods use raw counts, irrespective of if scale_abundance 
or adjust_abundance have been calculated. Therefore, it is essential to add covariates 
such as batch effects (if applicable) in the formula.
=====================================
Warning in eval(dots[[i]][[action]], env, env) :
  tidybulk says: highly abundant transcripts were not identified (i.e. identify_abundant()) or filtered (i.e., keep_abundant), therefore this operation will be performed on unfiltered data. In rare occasions this could be wanted. In standard whole-transcriptome workflows is generally unwanted.
tidybulk says: The design column names are "(Intercept), conditionTRUE"
tidybulk says: to access the raw results (fitted GLM) do `attr(..., "internals")$edgeR`
Found2batches
Adjusting for1covariate(s) or covariate level(s)
Standardizing Data across genes
Fitting L/S model and finding priors
Finding parametric adjustments
Adjusting the Data

Registered S3 method overwritten by 'spatstat.geom':
  method     from
  print.boxx cli 
Warning: The following arguments are not used: display.progress, num.cores, do.par
Suggested parameter: verbose instead of display.progress

Centering and scaling data matrix

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
PC_ 1 
Positive:  ENSG00000129514, ENSG00000109436, ENSG00000124942, ENSG00000115648, ENSG00000167978, ENSG00000117335, ENSG00000074410, ENSG00000091831, ENSG00000134107, ENSG00000164125 
	   ENSG00000113494, ENSG00000107485, ENSG00000139644, ENSG00000168743, ENSG00000166147, ENSG00000196405, ENSG00000075275, ENSG00000133110, ENSG00000135821, ENSG00000168461 
	   ENSG00000123384, ENSG00000104763, ENSG00000111799, ENSG00000163359, ENSG00000245532, ENSG00000185630, ENSG00000065361, ENSG00000260032, ENSG00000123124, ENSG00000148154 
Negative:  ENSG00000171863, ENSG00000143947, ENSG00000231500, ENSG00000182899, ENSG00000166441, ENSG00000105372, ENSG00000177600, ENSG00000142937, ENSG00000140988, ENSG00000105640 
	   ENSG00000197756, ENSG00000167526, ENSG00000114391, ENSG00000122406, ENSG00000174444, ENSG00000142676, ENSG00000142534, ENSG00000008988, ENSG00000221983, ENSG00000145592 
	   ENSG00000138326, ENSG00000130255, ENSG00000065978, ENSG00000171858, ENSG00000136942, ENSG00000118181, ENSG00000089009, ENSG00000182774, ENSG00000063177, ENSG00000137154 
PC_ 2 
Positive:  ENSG00000091831, ENSG00000129514, ENSG00000004478, ENSG00000107485, ENSG00000104447, ENSG00000151892, ENSG00000106537, ENSG00000136068, ENSG00000109436, ENSG00000183779 
	   ENSG00000134759, ENSG00000115648, ENSG00000096384, ENSG00000102316, ENSG00000138696, ENSG00000113739, ENSG00000139644, ENSG00000065361, ENSG00000123124, ENSG00000167978 
	   ENSG00000081479, ENSG00000251562, ENSG00000074410, ENSG00000160862, ENSG00000124145, ENSG00000108953, ENSG00000185630, ENSG00000110092, ENSG00000076554, ENSG00000075275 
Negative:  ENSG00000163430, ENSG00000087245, ENSG00000204262, ENSG00000035862, ENSG00000164692, ENSG00000163359, ENSG00000130635, ENSG00000113140, ENSG00000168542, ENSG00000108821 
	   ENSG00000101825, ENSG00000011465, ENSG00000142173, ENSG00000186340, ENSG00000038427, ENSG00000139329, ENSG00000166033, ENSG00000106333, ENSG00000166147, ENSG00000157227 
	   ENSG00000142156, ENSG00000123384, ENSG00000106624, ENSG00000182492, ENSG00000169604, ENSG00000133110, ENSG00000111799, ENSG00000060718, ENSG00000123500, ENSG00000145423 
PC_ 3 
Positive:  ENSG00000145741, ENSG00000186468, ENSG00000164587, ENSG00000141753, ENSG00000162244, ENSG00000143878, ENSG00000115648, ENSG00000107485, ENSG00000197958, ENSG00000100316 
	   ENSG00000196531, ENSG00000148303, ENSG00000174748, ENSG00000109475, ENSG00000170889, ENSG00000198034, ENSG00000129514, ENSG00000204628, ENSG00000188846, ENSG00000063177 
	   ENSG00000163682, ENSG00000137818, ENSG00000071082, ENSG00000012660, ENSG00000142541, ENSG00000065361, ENSG00000139644, ENSG00000111057, ENSG00000133112, ENSG00000075275 
Negative:  ENSG00000103257, ENSG00000152558, ENSG00000147065, ENSG00000115415, ENSG00000146731, ENSG00000112096, ENSG00000253729, ENSG00000065978, ENSG00000094755, ENSG00000143321 
	   ENSG00000138755, ENSG00000196230, ENSG00000104419, ENSG00000074800, ENSG00000166598, ENSG00000140545, ENSG00000102144, ENSG00000105220, ENSG00000117632, ENSG00000084207 
	   ENSG00000142949, ENSG00000111716, ENSG00000083444, ENSG00000136235, ENSG00000090382, ENSG00000173898, ENSG00000130066, ENSG00000164754, ENSG00000146648, ENSG00000115053 
PC_ 4 
Positive:  ENSG00000152583, ENSG00000159388, ENSG00000156508, ENSG00000120738, ENSG00000071967, ENSG00000170345, ENSG00000104332, ENSG00000150593, ENSG00000175061, ENSG00000265972 
	   ENSG00000122406, ENSG00000109475, ENSG00000091986, ENSG00000132465, ENSG00000175899, ENSG00000137154, ENSG00000185650, ENSG00000198755, ENSG00000167978, ENSG00000111716 
	   ENSG00000198034, ENSG00000071082, ENSG00000049540, ENSG00000143947, ENSG00000118523, ENSG00000133112, ENSG00000125730, ENSG00000118181, ENSG00000163682, ENSG00000112306 
Negative:  ENSG00000109062, ENSG00000178719, ENSG00000172757, ENSG00000185624, ENSG00000106211, ENSG00000117450, ENSG00000039068, ENSG00000111057, ENSG00000149925, ENSG00000170421 
	   ENSG00000165949, ENSG00000092841, ENSG00000113719, ENSG00000143761, ENSG00000096384, ENSG00000167004, ENSG00000108679, ENSG00000108829, ENSG00000126709, ENSG00000080824 
	   ENSG00000125534, ENSG00000067225, ENSG00000004478, ENSG00000171345, ENSG00000141367, ENSG00000164924, ENSG00000184009, ENSG00000167642, ENSG00000102144, ENSG00000135404 
PC_ 5 
Positive:  ENSG00000253729, ENSG00000080824, ENSG00000110321, ENSG00000113494, ENSG00000111371, ENSG00000102144, ENSG00000164754, ENSG00000164924, ENSG00000142949, ENSG00000109971 
	   ENSG00000070756, ENSG00000104408, ENSG00000096696, ENSG00000146731, ENSG00000096384, ENSG00000144381, ENSG00000009307, ENSG00000147676, ENSG00000198363, ENSG00000272398 
	   ENSG00000260032, ENSG00000147604, ENSG00000112378, ENSG00000104341, ENSG00000076554, ENSG00000141367, ENSG00000169604, ENSG00000123500, ENSG00000064651, ENSG00000115221 
Negative:  ENSG00000204592, ENSG00000166710, ENSG00000204525, ENSG00000234745, ENSG00000019582, ENSG00000206503, ENSG00000231389, ENSG00000196126, ENSG00000204287, ENSG00000142089 
	   ENSG00000185885, ENSG00000126709, ENSG00000157601, ENSG00000165949, ENSG00000130203, ENSG00000160932, ENSG00000102265, ENSG00000138755, ENSG00000101439, ENSG00000115415 
	   ENSG00000030582, ENSG00000108679, ENSG00000135404, ENSG00000125730, ENSG00000205542, ENSG00000185499, ENSG00000182326, ENSG00000140264, ENSG00000160182, ENSG00000167004 
Computing nearest neighbor graph
Computing SNN
Quitting from lines 434-437 (comparison_with_base_R.Rmd) 
Error: processing vignette 'comparison_with_base_R.Rmd' failed with diagnostics:
invalid class "Graph" object: superclass "Mnumeric" not defined in the environment of the object's class
--- failed re-building 'comparison_with_base_R.Rmd'

--- re-building 'introduction.Rmd' using knitr
Warning in aggregate_duplicated_transcripts_bulk(.data, .sample = !!.sample,  :
  tidybulk says: for aggregation, factors and logical columns were converted to character
Converted to characters
logical
Warning in aggregate_duplicated_transcripts_bulk(.data, .sample = !!.sample,  :
  tidybulk says: for aggregation, factors and logical columns were converted to character
Converted to characters
factorfactorfactorfactorlogical
tidybulk says: to access the raw results do `attr(..., "internals")$MDS`
tidybulk says: to access the raw results do `attr(..., "internals")$MDS`
Getting the 393 most variable genes
Fraction of variance explained by the selected principal components
# A tibble: 3 x 2
  `Fraction of variance`    PC
                   <dbl> <int>
1                 0.581      1
2                 0.321      2
3                 0.0896     3
tidybulk says: to access the raw results do `attr(..., "internals")$PCA`
Getting the 393 most variable genes
Fraction of variance explained by the selected principal components
# A tibble: 3 x 2
  `Fraction of variance`    PC
                   <dbl> <int>
1                 0.581      1
2                 0.321      2
3                 0.0896     3
tidybulk says: to access the raw results do `attr(..., "internals")$PCA`
No group or design set. Assuming all samples belong to one group.
Warning in eliminate_sparse_transcripts(., !!.feature) :
  tidybulk says: Some transcripts have been omitted from the analysis because not present in every sample.
Getting the 488 most variable genes
No group or design set. Assuming all samples belong to one group.
Warning in eliminate_sparse_transcripts(., !!.feature) :
  tidybulk says: Some transcripts have been omitted from the analysis because not present in every sample.
Getting the 488 most variable genes
=====================================
tidybulk says: All testing methods use raw counts, irrespective of if scale_abundance 
or adjust_abundance have been calculated. Therefore, it is essential to add covariates 
such as batch effects (if applicable) in the formula.
=====================================
tidybulk says: The design column names are "(Intercept), conditionTRUE"
tidybulk says: to access the raw results (fitted GLM) do `attr(..., "internals")$edgeR`
=====================================
tidybulk says: All testing methods use raw counts, irrespective of if scale_abundance 
or adjust_abundance have been calculated. Therefore, it is essential to add covariates 
such as batch effects (if applicable) in the formula.
=====================================
Warning in eval(dots[[i]][[action]], env, env) :
  tidybulk says: highly abundant transcripts were not identified (i.e. identify_abundant()) or filtered (i.e., keep_abundant), therefore this operation will be performed on unfiltered data. In rare occasions this could be wanted. In standard whole-transcriptome workflows is generally unwanted.
tidybulk says: The design column names are "(Intercept), conditionTRUE"
tidybulk says: to access the raw results (fitted GLM) do `attr(..., "internals")$edgeR`
Joining, by = "sample"
Found2batches
Adjusting for1covariate(s) or covariate level(s)
Standardizing Data across genes
Fitting L/S model and finding priors
Finding parametric adjustments
Adjusting the Data

Warning in eval(dots[[i]][[action]], env, env) :
  tidybulk says: highly abundant transcripts were not identified (i.e. identify_abundant()) or filtered (i.e., keep_abundant), therefore this operation will be performed on unfiltered data. In rare occasions this could be wanted. In standard whole-transcriptome workflows is generally unwanted.
Found2batches
Adjusting for1covariate(s) or covariate level(s)
Standardizing Data across genes
Fitting L/S model and finding priors
Finding parametric adjustments
Adjusting the Data

Warning: The following arguments are not used: display.progress, num.cores, do.par
Suggested parameter: verbose instead of display.progress

Centering and scaling data matrix

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Calculating gene variances
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Calculating feature variances of standardized and clipped values
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
PC_ 1 
Positive:  ENSG00000129514, ENSG00000109436, ENSG00000124942, ENSG00000115648, ENSG00000167978, ENSG00000117335, ENSG00000074410, ENSG00000091831, ENSG00000134107, ENSG00000164125 
	   ENSG00000113494, ENSG00000107485, ENSG00000139644, ENSG00000168743, ENSG00000166147, ENSG00000196405, ENSG00000075275, ENSG00000133110, ENSG00000135821, ENSG00000168461 
	   ENSG00000123384, ENSG00000104763, ENSG00000111799, ENSG00000163359, ENSG00000245532, ENSG00000185630, ENSG00000065361, ENSG00000260032, ENSG00000123124, ENSG00000148154 
Negative:  ENSG00000171863, ENSG00000143947, ENSG00000231500, ENSG00000182899, ENSG00000166441, ENSG00000105372, ENSG00000177600, ENSG00000142937, ENSG00000140988, ENSG00000105640 
	   ENSG00000197756, ENSG00000167526, ENSG00000114391, ENSG00000122406, ENSG00000174444, ENSG00000142676, ENSG00000142534, ENSG00000008988, ENSG00000221983, ENSG00000145592 
	   ENSG00000138326, ENSG00000130255, ENSG00000065978, ENSG00000171858, ENSG00000136942, ENSG00000118181, ENSG00000089009, ENSG00000182774, ENSG00000063177, ENSG00000137154 
PC_ 2 
Positive:  ENSG00000091831, ENSG00000129514, ENSG00000004478, ENSG00000107485, ENSG00000104447, ENSG00000151892, ENSG00000106537, ENSG00000136068, ENSG00000109436, ENSG00000183779 
	   ENSG00000134759, ENSG00000115648, ENSG00000096384, ENSG00000102316, ENSG00000138696, ENSG00000113739, ENSG00000139644, ENSG00000065361, ENSG00000123124, ENSG00000167978 
	   ENSG00000081479, ENSG00000251562, ENSG00000074410, ENSG00000160862, ENSG00000124145, ENSG00000108953, ENSG00000185630, ENSG00000110092, ENSG00000076554, ENSG00000075275 
Negative:  ENSG00000163430, ENSG00000087245, ENSG00000204262, ENSG00000035862, ENSG00000164692, ENSG00000163359, ENSG00000130635, ENSG00000113140, ENSG00000168542, ENSG00000108821 
	   ENSG00000101825, ENSG00000011465, ENSG00000142173, ENSG00000186340, ENSG00000038427, ENSG00000139329, ENSG00000166033, ENSG00000106333, ENSG00000166147, ENSG00000157227 
	   ENSG00000142156, ENSG00000123384, ENSG00000106624, ENSG00000182492, ENSG00000169604, ENSG00000133110, ENSG00000111799, ENSG00000060718, ENSG00000123500, ENSG00000145423 
PC_ 3 
Positive:  ENSG00000145741, ENSG00000186468, ENSG00000164587, ENSG00000141753, ENSG00000162244, ENSG00000143878, ENSG00000115648, ENSG00000107485, ENSG00000197958, ENSG00000100316 
	   ENSG00000196531, ENSG00000148303, ENSG00000174748, ENSG00000109475, ENSG00000170889, ENSG00000198034, ENSG00000129514, ENSG00000204628, ENSG00000188846, ENSG00000063177 
	   ENSG00000163682, ENSG00000137818, ENSG00000071082, ENSG00000012660, ENSG00000142541, ENSG00000065361, ENSG00000139644, ENSG00000111057, ENSG00000133112, ENSG00000075275 
Negative:  ENSG00000103257, ENSG00000152558, ENSG00000147065, ENSG00000115415, ENSG00000146731, ENSG00000112096, ENSG00000253729, ENSG00000065978, ENSG00000094755, ENSG00000143321 
	   ENSG00000138755, ENSG00000196230, ENSG00000104419, ENSG00000074800, ENSG00000166598, ENSG00000140545, ENSG00000102144, ENSG00000105220, ENSG00000117632, ENSG00000084207 
	   ENSG00000142949, ENSG00000111716, ENSG00000083444, ENSG00000136235, ENSG00000090382, ENSG00000173898, ENSG00000130066, ENSG00000164754, ENSG00000146648, ENSG00000115053 
PC_ 4 
Positive:  ENSG00000152583, ENSG00000159388, ENSG00000156508, ENSG00000120738, ENSG00000071967, ENSG00000170345, ENSG00000104332, ENSG00000150593, ENSG00000175061, ENSG00000265972 
	   ENSG00000122406, ENSG00000109475, ENSG00000091986, ENSG00000132465, ENSG00000175899, ENSG00000137154, ENSG00000185650, ENSG00000198755, ENSG00000167978, ENSG00000111716 
	   ENSG00000198034, ENSG00000071082, ENSG00000049540, ENSG00000143947, ENSG00000118523, ENSG00000133112, ENSG00000125730, ENSG00000118181, ENSG00000163682, ENSG00000112306 
Negative:  ENSG00000109062, ENSG00000178719, ENSG00000172757, ENSG00000185624, ENSG00000106211, ENSG00000117450, ENSG00000039068, ENSG00000111057, ENSG00000149925, ENSG00000170421 
	   ENSG00000165949, ENSG00000092841, ENSG00000113719, ENSG00000143761, ENSG00000096384, ENSG00000167004, ENSG00000108679, ENSG00000108829, ENSG00000126709, ENSG00000080824 
	   ENSG00000125534, ENSG00000067225, ENSG00000004478, ENSG00000171345, ENSG00000141367, ENSG00000164924, ENSG00000184009, ENSG00000167642, ENSG00000102144, ENSG00000135404 
PC_ 5 
Positive:  ENSG00000253729, ENSG00000080824, ENSG00000110321, ENSG00000113494, ENSG00000111371, ENSG00000102144, ENSG00000164754, ENSG00000164924, ENSG00000142949, ENSG00000109971 
	   ENSG00000070756, ENSG00000104408, ENSG00000096696, ENSG00000146731, ENSG00000096384, ENSG00000144381, ENSG00000009307, ENSG00000147676, ENSG00000198363, ENSG00000272398 
	   ENSG00000260032, ENSG00000147604, ENSG00000112378, ENSG00000104341, ENSG00000076554, ENSG00000141367, ENSG00000169604, ENSG00000123500, ENSG00000064651, ENSG00000115221 
Negative:  ENSG00000204592, ENSG00000166710, ENSG00000204525, ENSG00000234745, ENSG00000019582, ENSG00000206503, ENSG00000231389, ENSG00000196126, ENSG00000204287, ENSG00000142089 
	   ENSG00000185885, ENSG00000126709, ENSG00000157601, ENSG00000165949, ENSG00000130203, ENSG00000160932, ENSG00000102265, ENSG00000138755, ENSG00000101439, ENSG00000115415 
	   ENSG00000030582, ENSG00000108679, ENSG00000135404, ENSG00000125730, ENSG00000205542, ENSG00000185499, ENSG00000182326, ENSG00000140264, ENSG00000160182, ENSG00000167004 
Computing nearest neighbor graph
Computing SNN
Quitting from lines 470-489 (introduction.Rmd) 
Error: processing vignette 'introduction.Rmd' failed with diagnostics:
invalid class "Graph" object: superclass "Mnumeric" not defined in the environment of the object's class
--- failed re-building 'introduction.Rmd'

--- re-building 'manuscript_differential_transcript_abundance.Rmd' using knitr
Joining, by = "sample"
Warning in aggregate_duplicated_transcripts_bulk(.data, .sample = !!.sample,  :
  tidybulk says: for aggregation, factors and logical columns were converted to character
Converted to characters
factorfactorfactorfactor
No group or design set. Assuming all samples belong to one group.
tidybulk says: to access the raw results do `attr(..., "internals")$MDS`
Registered S3 method overwritten by 'GGally':
  method from   
  +.gg   ggplot2
Found2batches
Adjusting for1covariate(s) or covariate level(s)
Standardizing Data across genes
Fitting L/S model and finding priors
Finding parametric adjustments
Adjusting the Data

tidybulk says: to access the raw results do `attr(..., "internals")$MDS`
=====================================
tidybulk says: All testing methods use raw counts, irrespective of if scale_abundance 
or adjust_abundance have been calculated. Therefore, it is essential to add covariates 
such as batch effects (if applicable) in the formula.
=====================================
tidybulk says: The design column names are "(Intercept), conditionuntreated, typesingle-read"
tidybulk says: to access the raw results (fitted GLM) do `attr(..., "internals")$edgeR`
Warning: Using size for a discrete variable is not advised.
Warning: Using alpha for a discrete variable is not advised.
Warning: Removed 7390 rows containing missing values (geom_text_repel).
Joining, by = "transcript"
--- finished re-building 'manuscript_differential_transcript_abundance.Rmd'

--- re-building 'manuscript_transcriptional_signatures.Rmd' using knitr
--- finished re-building 'manuscript_transcriptional_signatures.Rmd'

SUMMARY: processing the following files failed:
  'comparison_with_base_R.Rmd' 'introduction.Rmd'

Error: Vignette re-building failed.
Execution halted