Error in re-building vignettes:
  ...

Ping wird ausgefhrt fr www.google.com [216.58.205.228] mit 32 Bytes Daten:
Antwort von 216.58.205.228: Bytes=32 Zeit=6ms TTL=55
Antwort von 216.58.205.228: Bytes=32 Zeit=6ms TTL=55
Antwort von 216.58.205.228: Bytes=32 Zeit=6ms TTL=55
Antwort von 216.58.205.228: Bytes=32 Zeit=6ms TTL=55

Ping-Statistik fr 216.58.205.228:
    Pakete: Gesendet = 4, Empfangen = 4, Verloren = 0 (0% Verlust),
Ca. Zeitangaben in Millisek.:
    Minimum = 6ms, Maximum = 6ms, Mittelwert = 6ms
version 1.14.7 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, 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

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, style


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, style


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, style


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, style


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, style


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, 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. 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, style


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, style


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

Ping wird ausgefhrt fr www.google.com [216.58.205.228] mit 32 Bytes Daten:
Antwort von 216.58.205.228: Bytes=32 Zeit=6ms TTL=55
Antwort von 216.58.205.228: Bytes=32 Zeit=6ms TTL=55
Antwort von 216.58.205.228: Bytes=32 Zeit=6ms TTL=55
Antwort von 216.58.205.228: Bytes=32 Zeit=6ms TTL=55

Ping-Statistik fr 216.58.205.228:
    Pakete: Gesendet = 4, Empfangen = 4, Verloren = 0 (0% Verlust),
Ca. Zeitangaben in Millisek.:
    Minimum = 6ms, Maximum = 6ms, Mittelwert = 6ms
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, 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  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, style


Check OK

Quitting from lines 224-358 (BcircularVig.Rmd) 
Error: processing vignette 'BcircularVig.Rmd' failed with diagnostics:
object 'tibble_update_attrs' not found
Execution halted