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Revision as of 16:47, 16 June 2014
, 16:47, 16 June 2014→Normalization
##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">
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
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 for the passed variants.
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) #frame shift / non frameshift indels proportion, the bracket gives the counts of the frame shift and non frameshift indels
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) #fraction of indels in low complexity region, the bracket gives the counts of the indels <br>
Low complexity : 0.46 (283/613) #fraction of indels in low complexity region, the bracket gives the counts of the indels <br>
1000G #1000 Genomes Phase 1 data set
1000G #1000 Genomes Phase 1 data set
A-B 371 [0.76] #variants found in data set only
A-B 371 [0.76] #variants found in call set only, square brackets contain insertion deletion ratio
A&B 242 [0.66]#variants found in both data sets
A&B 242 [0.66] #variants found in both data sets
B-A 276 [0.89] #variants found in 1000G phase 1 data set only
B-A 276 [0.89] #variants found in 1000G phase 1 data set only
Precision 39.5% #39.6% of the call set are previously known, so 60.5% are novel variants.
Precision 39.5% #39.5% of the call set are previously known, so 60.5% are novel variants.
Sensitivity 46.7% #sensitivity of variant calling, 46,7% of known variants from 1000 Genomes were rediscovered <br>
Sensitivity 46.7% #sensitivity of variant calling, 46,7% of known variants from 1000 Genomes were rediscovered <br>
mills #Mills et al. data set
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]
Precision 11.6%
Precision 11.6%
Sensitivity 69.6% <br>
Sensitivity 69.6% <br>
dbsnp # Indels from 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]
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.
We perform the same analysis for the failed variants again:
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 /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
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.
