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   ##INFO=<ID=FIC,Number=1,Type=Float,Description="Genotype likelihood based Inbreeding Coefficient">
 
   ##INFO=<ID=FIC,Number=1,Type=Float,Description="Genotype likelihood based Inbreeding Coefficient">
 
   ##INFO=<ID=AB,Number=1,Type=Float,Description="Genotype likelihood based Allele Balance">
 
   ##INFO=<ID=AB,Number=1,Type=Float,Description="Genotype likelihood based Allele Balance">
   ##FILTER=<ID=TPASS,Description="Temporary pass">
+
   ##FILTER=<ID=PASS,Description="Temporary pass">
 
   ##FILTER=<ID=overlap,Description="Overlapping variant">
 
   ##FILTER=<ID=overlap,Description="Overlapping variant">
   Line 50: Line 50:  
The columns are CHROM, POS, ID, REF, ALT, QUAL, FILTER, INFO, FORMAT, Genotype fields denoted by the sample name.
 
The columns are CHROM, POS, ID, REF, ALT, QUAL, FILTER, INFO, FORMAT, Genotype fields denoted by the sample name.
   −
   22 36990877 . GGT G . TPASS AC=32;AN=116;AF=0.275862;GC=32,20,6;GN=58;
+
   22 36990878 . GGT G 455 PASS AC=32;AN=116;AF=0.275862;GC=32,20,6;GN=58;
 
                                                                 GF=0.551724,0.344828,0.103448;NS=58;  
 
                                                                 GF=0.551724,0.344828,0.103448;NS=58;  
 
                                                                 HWEAF=0.275797;HWEGF=0.52447,0.399466,0.0760642;
 
                                                                 HWEAF=0.275797;HWEGF=0.52447,0.399466,0.0760642;
Line 61: Line 61:     
   22            : chromosome
 
   22            : chromosome
   36990877       : genome position
+
   36990878       : genome position
 
   .              : this is the ID field that is left blank.
 
   .              : this is the ID field that is left blank.
   GGT            : the reference sequence that is replaced by the alternative sequence below.
+
   GGT            : the reference sequence that is replaced by the alternative sequence below.
   G              : so this is basically a deletion of GT
+
   G              : so this is basically a deletion of GT
   .              : QUAL field which is left missing.
+
   455            : QUAL field denoting validity of this variant, higher the better.
   TPASS          : a temporary passed variant.
+
   PASS          : a passed variant.
   INFO          : fields containing information about the variant.
+
   INFO          : fields containing information about the variant.
 
   FORMAT        : format field labels for the genotype columns.
 
   FORMAT        : format field labels for the genotype columns.
 
   0/0:0,9,108:9:3,0,6:10 :  genotype information.
 
   0/0:0,9,108:9:3,0,6:10 :  genotype information.
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         no. of observed variants          :        720
 
         no. of observed variants          :        720
   −
The variants have filter labels TPASS meaning a temporary pass and overlap, meaning that the variants are overlapping with another variant, implying multiallelicity.
+
The variants have filter labels PASS meaning a temporary pass and overlap, meaning that the variants are overlapping with another variant, implying multiallelicity.
 
We can count the number of variants with the following commands.
 
We can count the number of variants with the following commands.
   −
   vt peek all.genotypes.bcf -f "FILTER.TPASS"
+
   vt peek all.genotypes.bcf -f "FILTER.PASS"
    
   stats: no. of samples                    :        62
 
   stats: no. of samples                    :        62
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         no. of chromosomes                :          1 <br>
 
         no. of chromosomes                :          1 <br>
 
         no. Indels                        :        136
 
         no. Indels                        :        136
             2 alleles (ins/del)            :            136 (1.89) [89/47]  #notice the difference insertion deletion ratios differences
+
             2 alleles (ins/del)            :            136 (1.89) [89/47]  #notice the difference in insertion deletion ratios
 
             >=3 alleles (ins/del)          :              0 (-nan) [0/0]
 
             >=3 alleles (ins/del)          :              0 (-nan) [0/0]
    
   #passed singletons only
 
   #passed singletons only
   vt peek all.genotypes.bcf -f "FILTER.TPASS&&INFO.AC==1"
+
   vt peek all.genotypes.bcf -f "FILTER.PASS&&INFO.AC==1"
 
   
 
   
 
   #passed indels of length 1 only
 
   #passed indels of length 1 only
   vt peek all.genotypes.bcf -f "FILTER.TPASS&&LEN==1"
+
   vt peek all.genotypes.bcf -f "FILTER.PASS&&LEN==1"
 
   
 
   
 
   #passed indels of length >4  
 
   #passed indels of length >4  
   vt peek all.genotypes.bcf -f "FILTER.TPASS&&LEN>1"
+
   vt peek all.genotypes.bcf -f "FILTER.PASS&&LEN>1"
 
    
 
    
 
   #passed singletons of length 4 or insertions of length 3
 
   #passed singletons of length 4 or insertions of length 3
   vt peek all.genotypes.bcf -f "FILTER.TPASS&&(LEN==4||DLEN==3)"
+
   vt peek all.genotypes.bcf -f "FILTER.PASS&&(LEN==4||DLEN==3)"
    
== Comparison with other data sets ==
 
== Comparison with other data sets ==
   −
It is usually useful to examine the call sets against known data sets.
+
It is usually useful to examine the call sets against known data sets for the passed variants.
   −
   vt profile_indels -g /net/fantasia/home/atks/ref/vt/grch37/indel.reference.txt  -r /net/fantasia/home/atks/ref/vt/grch37/hs37d5.fa run/final/all.genotypes.bcf -i 22:36000000-37000000 -f "PASS"
+
   vt profile_indels -g indel.reference.txt  -r hs37d5.fa all.genotypes.bcf -i 22:36000000-37000000 -f "PASS"
    
   data set
 
   data set
     No Indels        :        613 [0.72]
+
     No Indels        :        613 [0.72]   #613 passed variants with an insertion deletion ratio of 0.72
       FS/NFS        :      0.50 (2/2)
+
       FS/NFS        :      0.50 (2/2)     #frame shift / non frameshift indels proportion, the bracket gives the counts of the frame shift and non frameshift indels
       Low complexity :      0.46 (283/613) <br>
+
       Low complexity :      0.46 (283/613) #fraction of indels in low complexity region, the bracket gives the counts of the indels <br>
   1000G
+
   1000G #1000 Genomes Phase 1 data set
     A-B        371 [0.76]
+
     A-B        371 [0.76] #variants found in call set only, square brackets contain insertion deletion ratio
     A&B        242 [0.66]
+
     A&B        242 [0.66] #variants found in both data sets
     B-A        276 [0.89]
+
     B-A        276 [0.89] #variants found in 1000G phase 1 data set only
     Precision    39.5%
+
     Precision    39.5%   #39.5% of the call set are previously known, so 60.5% are novel variants.
     Sensitivity  46.7% <br>
+
     Sensitivity  46.7%   #sensitivity of variant calling, 46,7% of known variants from 1000 Genomes were rediscovered  <br>
   mills
+
   mills #The gold standard Mills et al. indel set
 
     A-B        542 [0.68]
 
     A-B        542 [0.68]
 
     A&B        71 [1.03]
 
     A&B        71 [1.03]
 
     B-A        31 [1.07]
 
     B-A        31 [1.07]
 
     Precision    11.6%
 
     Precision    11.6%
     Sensitivity  69.6% <br>
+
     Sensitivity  69.6% <br>
   dbsnp
+
   dbsnp #Indels from dbSNP
 
     A-B        405 [0.68]
 
     A-B        405 [0.68]
 
     A&B        208 [0.79]
 
     A&B        208 [0.79]
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Overlap analysis:  overlap analysis with other data sets is an indicator of sensitivity.
 
Overlap analysis:  overlap analysis with other data sets is an indicator of sensitivity.
    +
* 1000G: contains Indels from 1000 Genomes, represent a wide spectrum of variants from many different populations.  Variants here have an allele frequency above 0.005.
 +
* Mills:  contains doublehit common indels from the Mills. et al paper and is a relatively good measure of sensitivity for common variants.  Because not all Indels in this set is expected to be present in your sample, this actually gives you an underestimate of sensitivity.
 
* dbsnp: contains Indels submitted from everywhere, I am not sure what does this represent exactly.  But assuming most are real, then precision is a useful estimated quantity from this reference data set.
 
* dbsnp: contains Indels submitted from everywhere, I am not sure what does this represent exactly.  But assuming most are real, then precision is a useful estimated quantity from this reference data set.
* dbsnp: contains Indels submitted from everywhere, I am not sure what does this represent exactly.  But assuming most are real, then precision is a useful estimated quantity from this reference data set.
  −
* Mills:  contains doublehit common indels from the Mills. et al paper and is a relatively good measure of sensitivity for common variants.  Because not all Indels in this set is expected to be present in your sample, this actually gives you an underestimate of sensitivity.
     −
   vt profile_indels -g /net/fantasia/home/atks/ref/vt/grch37/indel.reference.txt  -r /net/fantasia/home/atks/ref/vt/grch37/hs37d5.fa run/final/all.genotypes.bcf -i 22:36000000-37000000 -f "~PASS"
+
We perform the same analysis for the failed variants again, the relatively low overlap with known data sets imply a reasonable tradeoff in sensitivity and specificity.
 +
 
 +
   vt profile_indels -g indel.reference.txt  -r hs37d5.fa all.genotypes.bcf -i 22:36000000-37000000 -f "~PASS"
    
   data set
 
   data set
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     Precision    4.7%
 
     Precision    4.7%
 
     Sensitivity  0.7%
 
     Sensitivity  0.7%
 +
 +
 
This analysis supports filters too.
 
This analysis supports filters too.
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To normalize and remove duplicate variants:
 
To normalize and remove duplicate variants:
   −
   vt normalize  mills.genotypes.bcf -r ~/ref/vt/grch37/hs37d5.fa  | vt mergedups - -o mills.normalized.genotypes.bcf  
+
   vt normalize  mills.genotypes.bcf -r hs37d5.fa  | vt mergedups - -o mills.normalized.genotypes.bcf  
    
and you will observe that 3994 variants had to be left aligned and 1092 variants were removed.
 
and you will observe that 3994 variants had to be left aligned and 1092 variants were removed.
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