• Home
• com.databricks
• SnpEff
• 4.3.1
• source code

×

Project download

Many resources are needed to download a project. Please understand that we have to compensate our server costs. Thank you in advance.
Project price only 1 $

You can buy this project and download/modify it how often you want.

s.SnpEff.4.3.1.source-code.snpEff_summary.ftl Maven / Gradle / Ivy

<#-- snpEff summary statistics -->



<#macro countByType counter>

	<#list counter.typeList as type>
		

	

		
 
			
 Type (alphabetical order)  
			
   
			
 Count 
			
 Percent 
		
	
 
			
  ${type}  
 
			
   
			
 ${counter.get(type)} 
 
			
 ${ ( 100 * counter.percent(type) )?string("0.###") }% 
		
	




<#macro intstatsTable intstats>
	<#if intstats.validData>
	

		
 
Min
${intstats.min}
 
		
 
Max
${intstats.max}
 
		
 
Mean
${intstats.mean}
 
		
 
Median
${intstats.median}
 
		
 
Standard deviation
${intstats.std}
 
		
 
Values
${intstats.toStringValues()}
 
		
 
Count
${intstats.toStringCounts()}
 
		
	
	













 
 SnpEff: Variant analysis 
 



	Contents
	Summary

	 Variant rate by chromosome

	Variants by type

	 Number of variants by impact 

	 Number of variants by functional class 

	 Number of variants by effect 

	Quality histogram

	InDel length histogram

	Base variant table

	Transition vs transversions (ts/tv)

	 Allele frequency 

	 Allele Count 

	 Codon change table 

	 Amino acid change table 

	 Chromosome variants plots 

	 Details by gene 










Summary



		<#assign color="#ffffff">
		<#if changeStats.countWarnings > 0> <#assign color="#ffff00"> 
		<#assign color="#dddddd">
		<#if changeStats.countErrors > 0> <#assign color="#ff0000"> 

	
 
		
  Genome  
		
 ${genomeVersion} 
	
	
 
		
  Date  
		
 ${date} 
	
	
 
		
  SnpEff version  
		
 
${version}
 
	
	
 
		
  Command line arguments  
		
 
${args}
 
	
	
 
		
  Warnings  
 
		
 ${changeStats.countWarnings} 
	
	
	
 
		
  Errors  
 
		
 ${changeStats.countErrors} 
	
	
	

		
  Number of lines (input file)  
		
 ${countInputLines} 
	
	

		
  Number of variants (before filter)  
		
 ${countVariants} 
	
	

		
  Number of not variants 
(i.e. reference equals alternative)  
		
 ${variantStats.countNonVariants} 
	
	

		
  Number of variants processed 
 (i.e. after filter and non-variants)  
		
 ${variantStats.count} 
	
	

		
  Number of known variants 
(i.e. non-empty ID)  
		
 
		${variantStats.countNonEmptyId}
		( ${ ( 100 * variantStats.getKnownRatio() )?string("0.###") }% ) 
		
	
	

		
  Number of multi-allelic VCF entries 
(i.e. more than two alleles)  
		
 
		${vcfStats.countMultiallelic}
		
	
	

		
  Number of effects  
		
 ${countEffects} 
	
	

		
  Genome total length  
		
 ${variantStats.genomeLen} 
	
	

		
  Genome effective length  
		
 ${variantStats.genomeLenEffective} 
	
	

		
  Variant rate  
		
 1 variant every ${variantStats.rateOfChange} bases 
	






 
 


 Variants rate details 


 
	<#list variantStats.chromosomeNamesEffective as chr> 
		

	
 Chromosome 
 Length 
 Variants 
 Variants rate 

			
 ${chr} 
			
 ${variantStats.getChromosomeLength(chr)} 
			
 ${variantStats.getCountByChromosome(chr)} 
			
 ${variantStats.getRateOfChangeByChromosome(chr)} 
		
 
	
	

		
 Total 
		
 ${variantStats.genomeLenEffective} 
		
 ${variantStats.count} 
		
 ${variantStats.rateOfChange} 
	
 
 




 
 

 Number variants by type



    	<#list variantStats.changeType as chType>
	    

	

		

			
  Type    
			
  Total   
		
	
    

	    	
  ${chType}  
	    	
 ${variantStats.countByChangeType.get(chType)} 
	    
    	
    
    

	    

	    	
Total  
	    	
 ${variantStats.countByChangeType.get("Total")} 
	    
    





 
 

 Number of effects by impact  
 

<@countByType changeStats.countByImpact />





 
 

 Number of effects by functional class  
 

<@countByType changeStats.countByFunctionalClass />


Missense / Silent ratio: ${changeStats.silentRatio?string("0.####")}





 
 

 Number of effects by type and region  
 


	

		
 Type 
		
 Region 
	
	

		
 <@countByType changeStats.countByEffect /> 
		
 <@countByType changeStats.countByGeneRegion /> 
	









 
 
 Quality: 

	<@intstatsTable vcfStats.qualityStats />		
	





 
 
 Insertions and deletions length: 

	<@intstatsTable variantStats.indelLen />		
	





 
 

 Base changes (SNPs)  


 <#list variantStats.bases as newBase > 
    <#list variantStats.bases as oldBase >
	    <#list variantStats.bases as newBase >

    

    	
   
  ${newBase}  

    
 
  ${oldBase}  
 ${variantStats.getBasesChangesCount(oldBase, newBase)} 
 
    







 

  Ts/Tv (transitions / transversions)  
 


Note: Only SNPs are used for this statistic.

Note: This Ts/Tv ratio is a 'raw' ratio (ratio of observed events).





	
 
 Transitions 
 ${vcfStats.tsTvStats.transitions} 
 
	
 
 Transversions 
 ${vcfStats.tsTvStats.transversions} 
 
	
 
 Ts/Tv ratio 
 ${vcfStats.tsTvStats.tsTvRatio?string("0.####")} 
 




<#assign tstv=vcfStats.hasData()>
<#if tstv>
	All variants:
	
${vcfStats.tsTvStats}
	

	Only known variants (i.e. the ones having a non-empty ID field):
	
${vcfStats.tsTvStatsKnown}





 

  Allele frequency  
 

<#assign af=vcfStats.hasData()>
<#if af>
	

	<@intstatsTable vcfStats.genotypeStats.alleleFrequency />


	


 

  Allele Count  
 
<#if af>
	

	<@intstatsTable vcfStats.genotypeStats.alleleCount />






 

  Hom/Het per sample  
 
<#if af>
	

	

	

	
	
${vcfStats.genotypeStats.homHetTable}




	
 


 Codon changes 


	

		How to read this table: 

		- Rows are reference codons and columns are changed codons. E.g. Row 'AAA' column 'TAA' indicates how many 'AAA' codons have been replaced by 'TAA' codons.

		- Red background colors indicate that more changes happened (heat-map).

		- Diagonals are indicated using grey background color 
 
		- WARNING: This table may include different translation codon tables (e.g. mamalian DNA and mitochondrial DNA).

		

	


  

			<#list changeStats.codonList as newCodon> 
	<#list changeStats.codonList as oldCodon>
			
				<#list changeStats.codonList as newCodon>
					<#assign count = changeStats.getCodonChangeCount(oldCodon, newCodon)>
					<#if count == 0> 
						<#assign count=" "> 
					
					
					<#if oldCodon == newCodon> 
						
					<#else>
						

	

		
 
			
   
 ${newCodon} 
 
		
	
 
				
 ${oldCodon} 
 ${count} 
 ${count} 
					
				
			
	





 


 Amino acid changes
 

	

		How to read this table: 

		- Rows are reference amino acids and columns are changed amino acids. E.g. Row 'A' column 'E' indicates how many 'A' amino acids have been replaced by 'E' amino acids.

		- Red background colors indicate that more changes happened (heat-map).

		- Diagonals are indicated using grey background color 
 
		- WARNING: This table may include different translation codon tables (e.g. mamalian DNA and mitochondrial DNA).

		

	



			<#list changeStats.aaList as newAa> 
	<#list changeStats.aaList as oldAa>
			
				<#list changeStats.aaList as newAa>
					<#assign count = changeStats.getAaChangeCount(oldAa, newAa)>
					<#if count == 0> 
						<#assign count=" "> 
					
					
					<#if oldAa == newAa> 
						
					<#else>
						

	

		
 
			
   
 ${newAa} 
 
		
	
 
				
 ${oldAa} 
 ${count} 
 ${count} 
					
				
			
	





<#if chromoPlots>
 


 Variants by chromosome
 


<#list variantStats.chromosomeNamesEffective as chr> 
	<#assign chrStats = variantStats.getChrPosStats(chr)>
	
		

		${chrStats}
	







	

	 Details by gene 

	

	Here you can find a tab-separated table.