Error(s) in re-building vignettes:
  ...
--- re-building ‘AplotIdiogramsVig.Rmd’ using rmarkdown
see help: ?idiogramFISH - browseVignettes('idiogramFISH') - https://ferroao.gitlab.io/manualidiogramfish
Making checks

In case of error see messages and the help ?functionName


Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species one has all columns with info to have monocen. If not, you have to clean your data

Calculating chromosome indexes in Species one

Checking mandatory columns from dfMarkPos: chrName, markName, markArm,markDistCen,markSize
 (column OTU  is necessary if more than one species)


OK marks of OTU Species one checked 


Checking mandatory columns from dfCenMarks: chrName, markName
 (column OTU  is necessary if more than one species)


OK cen. marks of OTU Species one checked 


Comparing chromosome names among dataframes:


Comparing OTU named:  Species one of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

Comparing chromosome names among dataframes:


Comparing OTU named:  Species one of main dataframe with correspondent dataframe  listOfdfDataCen  

 No divergence

####
Checking mandatory columns from dfMarkColor: markName, markColor, style


Check OK

Species one:
Calculating karyotype indexes A and A2

Making checks

In case of error see messages and the help ?functionName


Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species one has all columns with info to have monocen. If not, you have to clean your data

Calculating chromosome indexes in Species one

Checking mandatory columns from dfMarkPos: chrName, markName, markArm,markDistCen,markSize
 (column OTU  is necessary if more than one species)


OK marks of OTU Species one checked 


Checking mandatory columns from dfCenMarks: chrName, markName
 (column OTU  is necessary if more than one species)


OK cen. marks of OTU Species one checked 


Comparing chromosome names among dataframes:


Comparing OTU named:  Species one of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

####
Checking mandatory columns from dfMarkColor: markName, markColor, style


Check OK

Species one:
Calculating karyotype indexes A and A2

Making checks

In case of error see messages and the help ?functionName


Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species 1 has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species 2 has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species 3 has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species 4 has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species 5 has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species 6 has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species 7 has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species 8 has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species 9 has all columns with info to have monocen. If not, you have to clean your data

Calculating chromosome indexes in Species 1

Calculating chromosome indexes in Species 2

Calculating chromosome indexes in Species 3

Calculating chromosome indexes in Species 4

Calculating chromosome indexes in Species 5

Calculating chromosome indexes in Species 6

Calculating chromosome indexes in Species 7

Calculating chromosome indexes in Species 8

Calculating chromosome indexes in Species 9

Checking mandatory columns from dfMarkPos: chrName, markName, markArm,markDistCen,markSize
 (column OTU  is necessary if more than one species)


OK marks of OTU Species 1 checked 


OK marks of OTU Species 3 checked 


Checking mandatory columns from dfCenMarks: chrName, markName
 (column OTU  is necessary if more than one species)


OK cen. marks of OTU Species 2 checked 


Comparing chromosome names among dataframes:


Comparing OTU named:  Species 1 of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Species 3 of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

WARNING Chromosome Names in dataframe Species 9 duplicated - Error when d.f. of marks present

Comparing chromosome names among dataframes:


Comparing OTU named:  Species 2 of main dataframe with correspondent dataframe  listOfdfDataCen  

 No divergence

WARNING Chromosome Names in dataframe Species 9 duplicated - Error when d.f. of marks present

####
Checking mandatory columns from dfMarkColor: markName, markColor, style


Check OK


Warning: Chromosome names duplicated in dataframe Species 9, will be renamed
 this correction is available when no marks to be plotted, otherwise, is fatal
Species 9:
Calculating karyotype indexes A and A2

Species 8:
Calculating karyotype indexes A and A2

Species 7:
Calculating karyotype indexes A and A2

Species 6:
Calculating karyotype indexes A and A2

Species 5:
Calculating karyotype indexes A and A2

Species 4:
Calculating karyotype indexes A and A2

Species 3:
Calculating karyotype indexes A and A2

Species 2:
Calculating karyotype indexes A and A2

Species 1:
Calculating karyotype indexes A and A2

Quitting from lines 417-451 (AplotIdiogramsVig.Rmd) 
Error: processing vignette 'AplotIdiogramsVig.Rmd' failed with diagnostics:
'list' object cannot be coerced to type 'double'
--- failed re-building ‘AplotIdiogramsVig.Rmd’

--- re-building ‘BplotIdiogramsHoloVig.Rmd’ using rmarkdown
see help: ?idiogramFISH - browseVignettes('idiogramFISH') - https://ferroao.gitlab.io/manualidiogramfish
Making checks

In case of error see messages and the help ?functionName


Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. without cen.: 
chrName, chrSize,
 (column OTU  is necessary if more than one species)


OTU Species one has all columns with info to have holocen. If not, you have to clean your data

Checking mandatory columns from dfMarkPos (without cen.): chrName, markName, markPos,markSize
 (column OTU  is necessary if more than one species)


OK marks of OTU Species one checked 


Comparing chromosome names among dataframes:


Comparing OTU named:  Species one of main dataframe with correspondent dataframe  listOfdfMarkPosHolocen  

 No divergence

####
Checking mandatory columns from dfMarkColor: markName, markColor, style


Check OK

Species one:
Calculating karyotype index A2

Quitting from lines 200-232 (BplotIdiogramsHoloVig.Rmd) 
Error: processing vignette 'BplotIdiogramsHoloVig.Rmd' failed with diagnostics:
'list' object cannot be coerced to type 'double'
--- failed re-building ‘BplotIdiogramsHoloVig.Rmd’

--- re-building ‘CgroupsVig.Rmd’ using rmarkdown
see help: ?idiogramFISH - browseVignettes('idiogramFISH') - https://ferroao.gitlab.io/manualidiogramfish
Making checks

In case of error see messages and the help ?functionName


Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  1 has all columns with info to have monocen. If not, you have to clean your data

Warning: Chromosome names duplicated in dataframe 1, will be renamed
 this correction is available when no marks to be plotted, otherwise, is fatal
group column present - remove column if not using
Making checks

In case of error see messages and the help ?functionName


Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  1 has all columns with info to have monocen. If not, you have to clean your data

Checking mandatory columns from dfMarkPos: chrName, markName, markArm,markDistCen,markSize
 (column OTU  is necessary if more than one species)


OK marks of OTU 1 checked 


Comparing chromosome names among dataframes:


Comparing OTU named:  1 of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence
group column present - remove column if not using
Quitting from lines 188-222 (CgroupsVig.Rmd) 
Error: processing vignette 'CgroupsVig.Rmd' failed with diagnostics:
'list' object cannot be coerced to type 'double'
--- failed re-building ‘CgroupsVig.Rmd’

--- re-building ‘DphylogenyVig.Rmd’ using rmarkdown
see help: ?idiogramFISH - browseVignettes('idiogramFISH') - https://ferroao.gitlab.io/manualidiogramfish
Loading required package: ggplot2
Loading required package: phytools
Loading required package: ape
Loading required package: maps
Loading required package: ggpubr
Loading required package: magrittr

Attaching package: 'ggpubr'

The following object is masked from 'package:ape':

    rotate

Loading required package: grid
Loading required package: ggtree
ggtree v2.0.1  For help: https://yulab-smu.github.io/treedata-book/

If you use ggtree in published research, please cite the most appropriate paper(s):

[36m-[39m Guangchuang Yu, Tommy Tsan-Yuk Lam, Huachen Zhu, Yi Guan. Two methods for mapping and visualizing associated data on phylogeny using ggtree. Molecular Biology and Evolution 2018, 35(12):3041-3043. doi: 10.1093/molbev/msy194
[36m-[39m Guangchuang Yu, David Smith, Huachen Zhu, Yi Guan, Tommy Tsan-Yuk Lam. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods in Ecology and Evolution 2017, 8(1):28-36, doi:10.1111/2041-210X.12628



Attaching package: 'ggtree'

The following object is masked from 'package:ggpubr':

    rotate

The following object is masked from 'package:magrittr':

    inset

The following object is masked from 'package:ape':

    rotate

Read 1 item
Making checks

In case of error see messages and the help ?functionName


Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species_F has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species_H has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species_C has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species_B has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  Species_A has all columns with info to have monocen. If not, you have to clean your data

Calculating chromosome indexes in Species_F

Calculating chromosome indexes in Species_H

Calculating chromosome indexes in Species_C

Calculating chromosome indexes in Species_B

Calculating chromosome indexes in Species_A

Checking mandatory columns from dfMarkPos: chrName, markName, markArm,markDistCen,markSize
 (column OTU  is necessary if more than one species)


OK marks of OTU Species_C checked 


OK marks of OTU Species_A checked 


OK marks of OTU Species_H checked 


OK marks of OTU Species_B checked 


OK marks of OTU Species_F checked 


Checking mandatory columns from dfCenMarks: chrName, markName
 (column OTU  is necessary if more than one species)


OK cen. marks of OTU Species_C checked 


OK cen. marks of OTU Species_A checked 


Comparing chromosome names among dataframes:


Comparing OTU named:  Species_F of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Species_H of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Species_C of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Species_B of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Species_A of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

Comparing chromosome names among dataframes:


Comparing OTU named:  Species_C of main dataframe with correspondent dataframe  listOfdfDataCen  

 No divergence

Comparing OTU named:  Species_A of main dataframe with correspondent dataframe  listOfdfDataCen  

 No divergence

####
Checking mandatory columns from dfMarkColor: markName, markColor, style


Check OK

Species_A:
Calculating karyotype indexes A and A2

Species_B:
Calculating karyotype indexes A and A2

Species_C:
Calculating karyotype indexes A and A2

Species_H:
Calculating karyotype indexes A and A2

Species_F:
Calculating karyotype indexes A and A2

Quitting from lines 181-233 (DphylogenyVig.Rmd) 
Error: processing vignette 'DphylogenyVig.Rmd' failed with diagnostics:
'list' object cannot be coerced to type 'double'
--- failed re-building ‘DphylogenyVig.Rmd’

--- re-building ‘EhumanVig.Rmd’ using rmarkdown
see help: ?idiogramFISH - browseVignettes('idiogramFISH') - https://ferroao.gitlab.io/manualidiogramfish
Making checks

In case of error see messages and the help ?functionName


Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  otu1 has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  otu2 has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  otu3 has all columns with info to have monocen. If not, you have to clean your data

Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  otu4 has all columns with info to have monocen. If not, you have to clean your data

Checking mandatory columns from dfMarkPos: chrName, markName, markArm,markDistCen,markSize
 (column OTU  is necessary if more than one species)


OK marks of OTU otu1 checked 


OK marks of OTU otu2 checked 


OK marks of OTU otu3 checked 


OK marks of OTU otu4 checked 


Comparing chromosome names among dataframes:


Comparing OTU named:  otu1 of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  otu2 of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  otu3 of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  otu4 of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

####
Checking mandatory columns from dfMarkColor: markName, markColor, style


Check OK

group column present - remove column if not using
Making checks

In case of error see messages and the help ?functionName


Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  1 has all columns with info to have monocen. If not, you have to clean your data

Checking mandatory columns from dfMarkPos: chrName, markName, markArm,markDistCen,markSize
 (column OTU  is necessary if more than one species)


OK marks of OTU 1 checked 


Comparing chromosome names among dataframes:


Comparing OTU named:  1 of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

####
Checking mandatory columns from dfMarkColor: markName, markColor, style


Check OK

Making checks

In case of error see messages and the help ?functionName


Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  otu3 has all columns with info to have monocen. If not, you have to clean your data

Checking mandatory columns from dfMarkPos: chrName, markName, markArm,markDistCen,markSize
 (column OTU  is necessary if more than one species)


OK marks of OTU otu3 checked 


Comparing chromosome names among dataframes:


Comparing OTU named:  otu3 of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

####
Checking mandatory columns from dfMarkColor: markName, markColor, style


Check OK

group column present - remove column if not using
--- finished re-building ‘EhumanVig.Rmd’

--- re-building ‘index.Rmd’ using rmarkdown
package is up-to-date devel version
see help: ?idiogramFISH - browseVignettes('idiogramFISH') - https://ferroao.gitlab.io/manualidiogramfish
Making checks

In case of error see messages and the help ?functionName


Checking columns from dfChrSize


Checking mandatory columns from dfChrSize for chr. with cen.: 
chrName, shortArmSize,longArmSize,
 (column OTU  is necessary if more than one species)


OTU  1 has all columns with info to have monocen. If not, you have to clean your data

Checking mandatory columns from dfMarkPos: chrName, markName, markArm,markDistCen,markSize
 (column OTU  is necessary if more than one species)


OK marks of OTU 1 checked 


Checking mandatory columns from dfCenMarks: chrName, markName
 (column OTU  is necessary if more than one species)


OK cen. marks of OTU 1 checked 


Comparing chromosome names among dataframes:


Comparing OTU named:  1 of main dataframe with correspondent dataframe  listOfdfMarkPosMonocen  

 No divergence

Comparing chromosome names among dataframes:


Comparing OTU named:  1 of main dataframe with correspondent dataframe  listOfdfDataCen  

 No divergence

####
Checking mandatory columns from dfMarkColor: markName, markColor, style


Check OK

1:
Calculating karyotype indexes A and A2

Quitting from lines 256-288 (index.Rmd) 
Error: processing vignette 'index.Rmd' failed with diagnostics:
'list' object cannot be coerced to type 'double'
--- failed re-building ‘index.Rmd’

SUMMARY: processing the following files failed:
  ‘AplotIdiogramsVig.Rmd’ ‘BplotIdiogramsHoloVig.Rmd’ ‘CgroupsVig.Rmd’
  ‘DphylogenyVig.Rmd’ ‘index.Rmd’

Error: Vignette re-building failed.
Execution halted