Error(s) in re-building vignettes:
  ...
--- re-building ‘AplotIdiogramsVig.Rmd’ using rmarkdown
version 1.14.11 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, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

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 data.frames:


Comparing OTU named:  Species one of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing chromosome names among data.frames:


Comparing OTU named:  Species one of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence

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


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

Calculating chromosome indexes in Species 1

Calculating chromosome indexes in Species 2

Checking mandatory columns from dfMarkPos: chrName, markName, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

OK marks of OTU Species 1 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 data.frames:


Comparing OTU named:  Species 1 of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing chromosome names among data.frames:


Comparing OTU named:  Species 2 of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence

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


Check OK

Species 2:
Calculating karyotype indexes A and A2

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

Checking mandatory columns from dfMarkPos: chrName, markName, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

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 data.frames:


Comparing OTU named:  1 of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing chromosome names among data.frames:


Comparing OTU named:  1 of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence
By default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame
Color dfsd invalid, removed from mycolors
1:
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. 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
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU Species one checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  Species one of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

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


Colors provided in to dfMarkColor are not enough, internal colors will be used.

By default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame
Species one:
Calculating karyotype index A2

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 1 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
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU 1 checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  1 of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence
By default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame
1:
Calculating karyotype index A2

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
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU Species one checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  Species one of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

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


Colors provided in to dfMarkColor are not enough, internal colors will be used.

By default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame
Species one:
Calculating karyotype index 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, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

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 data.frames:


Comparing OTU named:  Species 1 of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Species 3 of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

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

Comparing chromosome names among data.frames:


Comparing OTU named:  Species 2 of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence

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

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


Check OK


Warning: Chromosome names duplicated in data.frame 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

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

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 three 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
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU species two checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  species two of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

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


Check OK

species three:
Calculating karyotype index A2

species two:
Calculating karyotype index A2

species one:
Calculating karyotype index 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  Parental 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  Parental 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  Allopolyploid has all columns with info to have monocen. If not, you have to clean your data

Calculating chromosome indexes in Parental 1

Calculating chromosome indexes in Parental 2

Calculating chromosome indexes in Allopolyploid

Checking mandatory columns from dfMarkPos: chrName, markName, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

OK marks of OTU Allopolyploid checked 


OK marks of OTU Parental 1 checked 


OK marks of OTU Parental 2 checked 


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


OK cen. marks of OTU Allopolyploid checked 


OK cen. marks of OTU Parental 1 checked 


OK cen. marks of OTU Parental 2 checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  Parental 1 of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Parental 2 of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Allopolyploid of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing chromosome names among data.frames:


Comparing OTU named:  Parental 1 of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence

Comparing OTU named:  Parental 2 of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence

Comparing OTU named:  Allopolyploid of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence
By default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame
Allopolyploid:
Calculating karyotype indexes A and A2

Parental 2:
Calculating karyotype indexes A and A2

Parental 1:
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. without cen.: 
chrName, chrSize,
 (column OTU  is necessary if more than one species)


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

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 Parental 2 has all columns with info to have holocen. If not, you have to clean your data

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 Allopolyploid 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
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU Allopolyploid checked 


OK marks of OTU Parental 1 checked 


OK marks of OTU Parental 2 checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  Parental 1 of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing OTU named:  Parental 2 of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing OTU named:  Allopolyploid of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence
By default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame
Allopolyploid:
Calculating karyotype index A2

Parental 2:
Calculating karyotype index A2

Parental 1:
Calculating karyotype index A2

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

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 three 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
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU species two checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  species two of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

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


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. without cen.: 
chrName, chrSize,
 (column OTU  is necessary if more than one species)


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

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 2 genome has all columns with info to have holocen. If not, you have to clean your data

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 3 genome 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
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU Species 1 genome checked 


OK marks of OTU Species 3 genome checked 


OK marks of OTU Species 2 genome checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  Species 1 genome of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing OTU named:  Species 2 genome of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing OTU named:  Species 3 genome of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence
By default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame
Species 3 genome:
Calculating karyotype index A2

Species 2 genome:
Calculating karyotype index A2

Species 1 genome:
Calculating karyotype index A2

By default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame
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. without cen.: 
chrName, chrSize,
 (column OTU  is necessary if more than one species)


OTU Species 1 genome has all columns with info to have holocen. 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. without cen.: 
chrName, chrSize,
 (column OTU  is necessary if more than one species)


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

Calculating chromosome indexes in Species 1

Calculating chromosome indexes in Species 2

Checking mandatory columns from dfMarkPos: chrName, markName, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

OK marks of OTU Species 1 checked 


Checking mandatory columns from dfMarkPos (without cen.): chrName, markName, markPos
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU Species 1 genome checked 


OK marks of OTU Species 2 genome 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 data.frames:


Comparing OTU named:  Species 1 of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing chromosome names among data.frames:


Comparing OTU named:  Species 1 genome of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing OTU named:  Species 2 genome of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing chromosome names among data.frames:


Comparing OTU named:  Species 2 of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence

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


Check OK

Species 2 genome:
Calculating karyotype index A2

Species 2:
Calculating karyotype indexes A and A2

Species 1 genome:
Calculating karyotype index A2

Species 1:
Calculating karyotype indexes A and A2

By default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame
Not enough colors in mycolor parameter, will be recycled
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. without cen.: 
chrName, chrSize,
 (column OTU  is necessary if more than one species)


OTU Species 1 genome has all columns with info to have holocen. 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. without cen.: 
chrName, chrSize,
 (column OTU  is necessary if more than one species)


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

Calculating chromosome indexes in Species 1

Calculating chromosome indexes in Species 2

Checking mandatory columns from dfMarkPos: chrName, markName, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

OK marks of OTU Species 1 checked 


Checking mandatory columns from dfMarkPos (without cen.): chrName, markName, markPos
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU Species 1 genome checked 


OK marks of OTU Species 2 genome 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 data.frames:


Comparing OTU named:  Species 1 of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing chromosome names among data.frames:


Comparing OTU named:  Species 1 genome of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing OTU named:  Species 2 genome of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing chromosome names among data.frames:


Comparing OTU named:  Species 2 of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence

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


Check OK

Species 2 genome:
Calculating karyotype index A2

Species 2:
Calculating karyotype indexes A and A2

Species 1 genome:
Calculating karyotype index A2

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

Checking mandatory columns from dfMarkPos: chrName, markName, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

OK marks of OTU hetero checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  hetero of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

WARNING Chromosome Names in data.frame first duplicated - Error when d.f. of marks present
By default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame

Warning: Chromosome names duplicated in data.frame first, 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. without cen.: 
chrName, chrSize,
 (column OTU  is necessary if more than one species)


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

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 heteromorphic 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
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU heteromorphic checked 


Comparing chromosome names among data.frames:


WARNING Chromosome Names in data.frame Species name duplicated - Error when d.f. of marks present

Comparing OTU named:  heteromorphic of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence
By default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame

Warning: Chromosome names duplicated in data.frame Species name, will be renamed
 this correction is available when no marks to be plotted, otherwise, is fatal
group column present - remove column if not using
Could not determine mime type for `https://kit.fontawesome.com/af0a13599b.js'
Error: processing vignette 'AplotIdiogramsVig.Rmd' failed with diagnostics:
pandoc document conversion failed with error 63
--- failed re-building ‘AplotIdiogramsVig.Rmd’

--- re-building ‘BcircularVig.Rmd’ using rmarkdown
Loading required package: idiogramFISH
version 1.14.11 See help: ?idiogramFISH - browseVignettes('idiogramFISH') - https://ferroao.gitlab.io/manualidiogramfish
Loading required package: plyr
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 mono 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. without cen.: 
chrName, chrSize,
 (column OTU  is necessary if more than one species)


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

Calculating chromosome indexes in Species mono

Checking mandatory columns from dfMarkPos: chrName, markName, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

OK marks of OTU Species mono checked 


Checking mandatory columns from dfMarkPos (without cen.): chrName, markName, markPos
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU Species holo checked 


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


OK cen. marks of OTU Species mono checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  Species mono of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing chromosome names among data.frames:


Comparing OTU named:  Species holo of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing chromosome names among data.frames:


Comparing OTU named:  Species mono of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence

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


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

ERROR in short/long arm classif. It will not be fixed
Chr. (cen) indexes will not be calculated
in Tradescantia spathacea

Fix measures or use chrIndex="", and morpho="" 

Checking mandatory columns from dfMarkPos: chrName, markName, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

OK marks of OTU Tradescantia spathacea checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  Tradescantia spathacea of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

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


Check OK


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 Bacillus cereus strain 03BB87 plasmid pBCN has all columns with info to have holocen. If not, you have to clean your data

Comparing chromosome names among data.frames:


Comparing OTU named:  Bacillus cereus strain 03BB87 plasmid pBCN of main data.frame with correspondent data.frame  listOfdfMarks  

 No divergence
By default 5S are plotted as dots, to change this behavior make your own dfMarkColor data.frame
Not enough colors in mycolor parameter, will be recycled
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 Bacillus cereus strain 03BB87 plasmid pBCN 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
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU Bacillus cereus strain 03BB87 plasmid pBCN checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  Bacillus cereus strain 03BB87 plasmid pBCN of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

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


Check OK

--- finished re-building ‘BcircularVig.Rmd’

--- re-building ‘DphylogenyVig.Rmd’ using rmarkdown
version 1.14.11 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

Attaching package: 'ggpubr'

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

    rotate

Loading required package: grid
Loading required package: ggtree
ggtree v2.2.0  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. Using ggtree to visualize data on tree-like structures. Current Protocols in Bioinformatics, 2020, 69:e96. doi:10.1002/cpbi.96
[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: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, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

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 data.frames:


Comparing OTU named:  Species_F of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Species_H of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Species_C of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Species_B of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Species_A of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing chromosome names among data.frames:


Comparing OTU named:  Species_C of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence

Comparing OTU named:  Species_A of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence

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


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

Loading required package: treeio
treeio v1.12.0  For help: https://yulab-smu.github.io/treedata-book/

If you use treeio in published research, please cite:

LG Wang, TTY Lam, S Xu, Z Dai, L Zhou, T Feng, P Guo, CW Dunn, BR Jones, T Bradley, H Zhu, Y Guan, Y Jiang, G Yu. treeio: an R package for phylogenetic tree input and output with richly annotated and associated data. Molecular Biology and Evolution 2020, 37(2):599-603. doi: 10.1093/molbev/msz240


Attaching package: 'treeio'

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

    read.newick

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

    drop.tip

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

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

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

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

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_F 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
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU Species_C checked 


OK marks of OTU Species_H checked 


OK marks of OTU Species_A checked 


OK marks of OTU Species_B checked 


OK marks of OTU Species_F checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  Species_B of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing OTU named:  Species_A of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing OTU named:  Species_H of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing OTU named:  Species_C of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing OTU named:  Species_F of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

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


Check OK

Species_F:
Calculating karyotype index A2

Species_C:
Calculating karyotype index A2

Species_H:
Calculating karyotype index A2

Species_A:
Calculating karyotype index A2

Species_B:
Calculating karyotype index A2

Loading required package: plyr

Attaching package: 'plyr'

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

    mutate

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

    ozone

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_B has all columns with info to have holocen. 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

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_H has all columns with info to have holocen. 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_F has all columns with info to have monocen. If not, you have to clean your data

Calculating chromosome indexes in Species_A

Calculating chromosome indexes in Species_C

Calculating chromosome indexes in Species_F

Checking mandatory columns from dfMarkPos: chrName, markName, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

OK marks of OTU Species_C checked 


OK marks of OTU Species_A checked 


OK marks of OTU Species_F checked 


Checking mandatory columns from dfMarkPos (without cen.): chrName, markName, markPos
 (column OTU  is necessary if more than one species)
markSize column is not necessary for style of mark cM

OK marks of OTU Species_H checked 


OK marks of OTU Species_B 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 data.frames:


Comparing OTU named:  Species_A of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Species_C of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  Species_F of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing chromosome names among data.frames:


Comparing OTU named:  Species_B of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing OTU named:  Species_H of main data.frame with correspondent data.frame  listOfdfMarkPosHolocen  

 No divergence

Comparing chromosome names among data.frames:


Comparing OTU named:  Species_A of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence

Comparing OTU named:  Species_C of main data.frame with correspondent data.frame  listOfdfDataCen  

 No divergence

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


Check OK

Species_F:
Calculating karyotype indexes A and A2

Species_C:
Calculating karyotype indexes A and A2

Species_H:
Calculating karyotype index A2

Species_A:
Calculating karyotype indexes A and A2

Species_B:
Calculating karyotype index A2

--- finished re-building ‘DphylogenyVig.Rmd’

--- re-building ‘EhumanVig.Rmd’ using rmarkdown
version 1.14.11 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, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

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 data.frames:


Comparing OTU named:  otu1 of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  otu2 of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  otu3 of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

Comparing OTU named:  otu4 of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

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


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

Checking mandatory columns from dfMarkPos: chrName, markName, chrRegion,markDistCen
 (column OTU  is necessary if more than one species)
markSize can be absent when cM style

OK marks of OTU otu3 checked 


Comparing chromosome names among data.frames:


Comparing OTU named:  otu3 of main data.frame with correspondent data.frame  listOfdfMarkPosMonocen  

 No divergence

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


Check OK

--- finished re-building ‘EhumanVig.Rmd’

--- re-building ‘index.Rmd’ using rmarkdown
package is up-to-date release version
trying URL ‘https://liberapay.com/assets/widgets/donate.svg’
Content type 'image/svg+xml' length 1457 bytes
==================================================
downloaded 1457 bytes

trying URL ‘http://img.shields.io/liberapay/receives/ferroao.svg’
downloaded 1031 bytes

--- finished re-building ‘index.Rmd’

SUMMARY: processing the following file failed:
  ‘AplotIdiogramsVig.Rmd’

Error: Vignette re-building failed.
Execution halted