Analyses of Indels - Revision history

Atks: /* Motivation */

2014-06-15T22:12:47Z

Motivation

← Older revision		Revision as of 18:12, 15 June 2014
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	=Motivation=		=Motivation=

	This wiki page details some standard Indel analyses ~~for~~ the ~~sequencing workshop~~ in the ~~example indel data set~~.		This wiki page details some standard Indel analyses which hopefully can help the group in understanding the issues and perform the analyses quickly without reinventing the wheel.

	=Tools=		=Tools=

Atks: /* Anatomy of all.genotypes.bcf */

2014-06-15T22:12:10Z

Anatomy of all.genotypes.bcf

← Older revision		Revision as of 18:12, 15 June 2014
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	The file generated from the indel calling is a binary version [[http://www.1000genomes.org/wiki/analysis/variant-call-format/bcf-binary-vcf-version-2 BCFv2.1]] of the Variant Call Format (VCF). BCFv2.1 is more efficient to process as the data is already stored in computer readable format on the hard disk. It is however not necessarily more compact than VCF4.2 especially when the format fields are rich in details.		The file generated from the indel calling is a binary version [[http://www.1000genomes.org/wiki/analysis/variant-call-format/bcf-binary-vcf-version-2 BCFv2.1]] of the Variant Call Format (VCF). BCFv2.1 is more efficient to process as the data is already stored in computer readable format on the hard disk. It is however not necessarily more compact than VCF4.2 especially when the format fields are rich in details.

	~~== Anatomy of all.genotypes.bcf ==~~

	~~You can access the header by running the command:~~

	~~vt view -H all.genotypes.bcf.~~

	~~The header is as follows:~~

	~~##fileformat=VCFv4.2~~
	~~##FILTER=<ID=PASS,Description="All filters passed">~~
	~~##contig=<ID=22,length=51304566>~~
	~~##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">~~
	~~##FORMAT=<ID=PL,Number=G,Type=Integer,Description="Normalized, Phred-scaled likelihoods for genotypes">~~
	~~##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Depth">~~
	~~##FORMAT=<ID=AD,Number=3,Type=Integer,Description="Allele Depth">~~
	~~##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality">~~
	~~##INFO=<ID=AC,Number=A,Type=Integer,Description="Alternate Allele Counts">~~
	~~##INFO=<ID=AN,Number=1,Type=Integer,Description="Total Number Allele Counts">~~
	~~##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of Samples With Data">~~
	~~##INFO=<ID=AF,Number=A,Type=Float,Description="Alternate Allele Frequency">~~
	~~##INFO=<ID=GC,Number=G,Type=Integer,Description="Genotype Counts">~~
	~~##INFO=<ID=GN,Number=1,Type=Integer,Description="Total Number of Genotypes Counts">~~
	~~##INFO=<ID=GF,Number=G,Type=Float,Description="Genotype Frequency">~~
	~~##INFO=<ID=HWEAF,Number=A,Type=Float,Description="Genotype likelihood based MLE Allele Frequency assuming HWE">~~
	~~##INFO=<ID=HWEGF,Number=G,Type=Float,Description="Genotype likelihood based MLE Genotype Frequency assuming HWE">~~
	~~##INFO=<ID=MLEAF,Number=A,Type=Float,Description="Genotype likelihood based MLE Allele Frequency">~~
	~~##INFO=<ID=MLEGF,Number=G,Type=Float,Description="Genotype likelihood based MLE Genotype Frequency">~~
	~~##INFO=<ID=HWE_LLR,Number=1,Type=Float,Description="Genotype likelihood based Hardy Weinberg ln(Likelihood Ratio)">~~
	~~##INFO=<ID=HWE_LPVAL,Number=1,Type=Float,Description="Genotype likelihood based Hardy Weinberg Likelihood Ratio Test Statistic ln(p-value)">~~
	~~##INFO=<ID=HWE_DF,Number=1,Type=Integer,Description="Degrees of freedom for Genotype likelihood based Hardy Weinberg Likelihood Ratio Test Statistic">~~
	~~##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">~~
	~~##FILTER=<ID=TPASS,Description="Temporary pass">~~
	~~##FILTER=<ID=overlap,Description="Overlapping variant">~~

	~~=== body ===~~

	~~To view some of the records:~~

	~~22 36990877 . GGT G . TPASS AC=32;AN=116;AF=0.275862;GC=32,20,6;GN=58;GF=0.551724,0.344828,0.103448;NS=58;~~
	~~HWEAF=0.275797;HWEGF=0.52447,0.399466,0.0760642;MLEAF=0.27366;~~
	~~MLEGF=0.494275,0.464129,0.0415952;HWE_LLR=-0.453098;HWE_LPVAL=-1.0755;HWE_DF=1;FIC=-0.0718807;AB=0.6129~~
	~~GT:PL:DP:AD:GQ 0/0:0,9,108:9:3,0,6:10~~
	22 36991203 . TGAG T . TPASS AC=5;AN=124;AF=0.0403226;GC=58,3,1;GN=62;GF=0.935484,0.0483871,0.016129;NS=62;HWEAF=0.0355594;HWEGF=0.930145,0.0685899,0.00126447;MLEAF=0.0353706;MLEGF=0.929259,0.0707412,5.94815e-11;HWE_LLR=-0.0443401;HWE_LPVAL=-0.266754;HWE_DF=1;FIC=-0.0109029;AB=0.562243 GT:PL:DP:AD:GQ 0/0:0,12,155:6:4,0,2:12
	22 36995311 . GA G . TPASS AC=61;AN=124;AF=0.491935;GC=21,21,20;GN=62;GF=0.33871,0.33871,0.322581;NS=62;HWEAF=0.492227;HWEGF=0.257834,0.499879,0.242287;MLEAF=0.492028;MLEGF=0.298019,0.419905,0.282076;HWE_LLR=-0.605122;HWE_LPVAL=-1.30459;HWE_DF=1;FIC=0.0444598;AB=0.53981 GT:PL:DP:AD:GQ 0/1:55,0,24:3:1,2,0:24
	22 36995329 . GA G . TPASS AC=2;AN=124;AF=0.016129;GC=60,2,0;GN=62;GF=0.967742,0.0322581,0;NS=62;HWEAF=0.0164696;HWEGF=0.967332,0.0323966,0.000271246;MLEAF=0.0165148;MLEGF=0.96697,0.0330296,7.28675e-44;HWE_LLR=-0.0171385;HWE_LPVAL=-0.158856;HWE_DF=1;FIC=-0.00275028;AB=0.339746 GT:PL:DP:AD:GQ 0/0:0,9,97:5:3,0,2:10
	==File Preparation==		==File Preparation==

Atks: /* Analyses */

2014-06-15T21:41:51Z

Analyses

← Older revision		Revision as of 17:41, 15 June 2014
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	=Analyses=		=Analyses=

	The file generated from the indel calling is a binary version [[http://www.1000genomes.org/wiki/analysis/variant-call-format/bcf-binary-vcf-version-2 BCFv2.1]] of the Variant Call Format (VCF). ~~The binary version~~		The file generated from the indel calling is a binary version [[http://www.1000genomes.org/wiki/analysis/variant-call-format/bcf-binary-vcf-version-2 BCFv2.1]] of the Variant Call Format (VCF). BCFv2.1 is more efficient to process as the data is already stored in computer readable format on the hard disk. It is however not necessarily more compact than VCF4.2 especially when the format fields are rich in details.
	== Anatomy of ~~file~~ ==
			== Anatomy of all.genotypes.bcf ==

	You can access the header by running the command:		You can access the header by running the command:
Line 45:		Line 46:
	##FILTER=<ID=overlap,Description="Overlapping variant">		##FILTER=<ID=overlap,Description="Overlapping variant">

			=== body ===

			To view some of the records:

			22 36990877 . GGT G . TPASS AC=32;AN=116;AF=0.275862;GC=32,20,6;GN=58;GF=0.551724,0.344828,0.103448;NS=58;
			HWEAF=0.275797;HWEGF=0.52447,0.399466,0.0760642;MLEAF=0.27366;
			MLEGF=0.494275,0.464129,0.0415952;HWE_LLR=-0.453098;HWE_LPVAL=-1.0755;HWE_DF=1;FIC=-0.0718807;AB=0.6129
			GT:PL:DP:AD:GQ 0/0:0,9,108:9:3,0,6:10
			22 36991203 . TGAG T . TPASS AC=5;AN=124;AF=0.0403226;GC=58,3,1;GN=62;GF=0.935484,0.0483871,0.016129;NS=62;HWEAF=0.0355594;HWEGF=0.930145,0.0685899,0.00126447;MLEAF=0.0353706;MLEGF=0.929259,0.0707412,5.94815e-11;HWE_LLR=-0.0443401;HWE_LPVAL=-0.266754;HWE_DF=1;FIC=-0.0109029;AB=0.562243 GT:PL:DP:AD:GQ 0/0:0,12,155:6:4,0,2:12
			22 36995311 . GA G . TPASS AC=61;AN=124;AF=0.491935;GC=21,21,20;GN=62;GF=0.33871,0.33871,0.322581;NS=62;HWEAF=0.492227;HWEGF=0.257834,0.499879,0.242287;MLEAF=0.492028;MLEGF=0.298019,0.419905,0.282076;HWE_LLR=-0.605122;HWE_LPVAL=-1.30459;HWE_DF=1;FIC=0.0444598;AB=0.53981 GT:PL:DP:AD:GQ 0/1:55,0,24:3:1,2,0:24
			22 36995329 . GA G . TPASS AC=2;AN=124;AF=0.016129;GC=60,2,0;GN=62;GF=0.967742,0.0322581,0;NS=62;HWEAF=0.0164696;HWEGF=0.967332,0.0323966,0.000271246;MLEAF=0.0165148;MLEGF=0.96697,0.0330296,7.28675e-44;HWE_LLR=-0.0171385;HWE_LPVAL=-0.158856;HWE_DF=1;FIC=-0.00275028;AB=0.339746 GT:PL:DP:AD:GQ 0/0:0,9,97:5:3,0,2:10
	==File Preparation==		==File Preparation==

Line 51:		Line 63:
	To convert to BCF format which will work fast with vt:		To convert to BCF format which will work fast with vt:

	22 36990877 . GGT G . TPASS AC=32;AN=116;AF=0.275862;GC=32,20,6;GN=58;GF=0.551724,0.344828,0.103448;NS=58;HWEAF=0.275797;HWEGF=0.52447,0.399466,0.0760642;MLEAF=0.27366;MLEGF=0.494275,0.464129,0.0415952;HWE_LLR=-0.453098;HWE_LPVAL=-1.0755;HWE_DF=1;FIC=-0.0718807;AB=0.6129 GT:PL:DP:AD:GQ 0/0:0,9,108:9:3,0,6:10
	22 36991203 . TGAG T . TPASS AC=5;AN=124;AF=0.0403226;GC=58,3,1;GN=62;GF=0.935484,0.0483871,0.016129;NS=62;HWEAF=0.0355594;HWEGF=0.930145,0.0685899,0.00126447;MLEAF=0.0353706;MLEGF=0.929259,0.0707412,5.94815e-11;HWE_LLR=-0.0443401;HWE_LPVAL=-0.266754;HWE_DF=1;FIC=-0.0109029;AB=0.562243 GT:PL:DP:AD:GQ 0/0:0,12,155:6:4,0,2:12
	22 36995311 . GA G . TPASS AC=61;AN=124;AF=0.491935;GC=21,21,20;GN=62;GF=0.33871,0.33871,0.322581;NS=62;HWEAF=0.492227;HWEGF=0.257834,0.499879,0.242287;MLEAF=0.492028;MLEGF=0.298019,0.419905,0.282076;HWE_LLR=-0.605122;HWE_LPVAL=-1.30459;HWE_DF=1;FIC=0.0444598;AB=0.53981 GT:PL:DP:AD:GQ 0/1:55,0,24:3:1,2,0:24
	22 36995329 . GA G . TPASS AC=2;AN=124;AF=0.016129;GC=60,2,0;GN=62;GF=0.967742,0.0322581,0;NS=62;HWEAF=0.0164696;HWEGF=0.967332,0.0323966,0.000271246;MLEAF=0.0165148;MLEGF=0.96697,0.0330296,7.28675e-44;HWE_LLR=-0.0171385;HWE_LPVAL=-0.158856;HWE_DF=1;FIC=-0.00275028;AB=0.339746 GT:PL:DP:AD:GQ 0/0:0,9,97:5:3,0,2:10

	vt view mills.vcf -o mills.bcf		vt view mills.vcf -o mills.bcf

Atks at 21:35, 15 June 2014

2014-06-15T21:35:48Z

@@ Line 1: / Line 1: @@
 =Motivation=
-This wiki page details some standard Indel analyses which hopefully can help the group in understanding the issues and perform the analyses quickly without reinventing the wheel.
+This wiki page details some standard Indel analyses for the sequencing workshop in the example indel data set.
 =Tools=
-You can download [[vt|vt]] and have some working knowledge of PERL to do stuff that vt does not support.
+This walkthrough requires  [[vt|vt]].
 =Analyses=
 ==File Preparation==
@@ Line 14: / Line 50: @@
 To convert to BCF format which will work fast with vt:
     vt view mills.vcf -o mills.bcf

Atks: /* Insertion/Deletion ratios, Coding Regions and Overlap analysis */

2014-02-20T22:23:02Z

Insertion/Deletion ratios, Coding Regions and Overlap analysis

← Older revision		Revision as of 18:23, 20 February 2014
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	data set		data set
	No Indels : 8904 [0.93]		No Indels : 8904 [0.93] //#variants in your data set [ins/del ratio]
	FS/NFS : 0.66 (67/35) //Proportion of frameshift Indels. (#Frameshift Indels/#Nonframeshift Indels)<br>		FS/NFS : 0.66 (67/35) //Proportion of frameshift Indels. (#Frameshift Indels/#Nonframeshift Indels)<br>
	dbsnp //A represents the data set you input, B represents dbsnp		dbsnp //A represents the data set you input, B represents dbsnp

Atks: /* to document */

2014-02-20T22:19:47Z

to document

← Older revision		Revision as of 18:19, 20 February 2014
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	* Annotation of STRs is really important. Show example of a deceptive single base pair variant		* Annotation of STRs is really important. Show example of a deceptive single base pair variant
			* Mendelian analysis
			* AFS
	* Can check concordance of genotypes between callers - partitiion		* Can check concordance of genotypes between callers - partitiion
	* Type of Indels - homopolymer types and STR types and isolated, Adjacent SNPs ,Adjacent MNPs,Clumping variants		* Type of Indels - homopolymer types and STR types and isolated, Adjacent SNPs ,Adjacent MNPs,Clumping variants

Atks: /* Insertion/Deletion ratios, Coding Regions and Overlap analysis */

2014-02-20T22:16:54Z

Insertion/Deletion ratios, Coding Regions and Overlap analysis

← Older revision		Revision as of 18:16, 20 February 2014
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	data set		data set
	No Indels : 8904 [0.93]		No Indels : 8904 [0.93]
	FS/NFS : 0.66 (67/35) // Proportion of frameshift Indels. (#Frameshift Indels/#Nonframeshift Indels)<br>		FS/NFS : 0.66 (67/35) //Proportion of frameshift Indels. (#Frameshift Indels/#Nonframeshift Indels)<br>
	dbsnp		dbsnp //A represents the data set you input, B represents dbsnp
	A-B 2975 [1.06] //#variants in A only [ins/del ratio]		A-B 2975 [1.06] //#variants in A only [ins/del ratio]
	A&B 5929 [0.86]		A&B 5929 [0.86] //#variants in A and B
	B-A 2059845 [1.51]		B-A 2059845 [1.51]
	Precision 66.6% // A&B/A this represents how novel your data set is in the variants represented.		Precision 66.6% //A&B/A this represents how novel your data set is in the variants represented.
	Sensitivity 0.3% ~~<br>~~ // A&B/B this represents sensitivity somewhat if dbsnp is considered a high quality Indel set		Sensitivity 0.3% //A&B/B this represents sensitivity somewhat if dbsnp is considered a high quality Indel
			//set and the sample are the same in both data sets. (which they usually are not, this is still
			//nonetheless a useful indicator)<br>
	mills		mills
	A-B 5705 [0.81]		A-B 5705 [0.81]

Atks: /* Insertion/Deletion ratios, Coding Regions and Overlap analysis */

2014-02-20T22:10:34Z

Insertion/Deletion ratios, Coding Regions and Overlap analysis

← Older revision		Revision as of 18:10, 20 February 2014
Line 204:		Line 204:
	data set		data set
	No Indels : 8904 [0.93]		No Indels : 8904 [0.93]
	FS/NFS : 0.66 (67/35)<br>		FS/NFS : 0.66 (67/35) // Proportion of frameshift Indels. (#Frameshift Indels/#Nonframeshift Indels)<br>
	dbsnp		dbsnp
	A-B 2975 [1.06]		A-B 2975 [1.06] //#variants in A only [ins/del ratio]
	A&B 5929 [0.86]		A&B 5929 [0.86]
	B-A 2059845 [1.51]		B-A 2059845 [1.51]
	Precision 66.6%		Precision 66.6% // A&B/A this represents how novel your data set is in the variants represented.
	Sensitivity 0.3% <br>		Sensitivity 0.3% <br> // A&B/B this represents sensitivity somewhat if dbsnp is considered a high quality Indel set
	mills		mills
	A-B 5705 [0.81]		A-B 5705 [0.81]

Atks: /* Insertion/Deletion ratios, Coding Regions and Overlap analysis */

2014-02-20T22:06:18Z

Insertion/Deletion ratios, Coding Regions and Overlap analysis

← Older revision		Revision as of 18:06, 20 February 2014
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	Sensitivity 0.2%		Sensitivity 0.2%

	Ins/Del ratios: Reference alignment based methods tend to be biased towards the detection of deletions. This provides a useful measure for discovery Indel sets to show the varying degree of biasness.		Ins/Del ratios: Reference alignment based methods tend to be biased towards the detection of deletions. This provides a useful measure for discovery Indel sets to show the varying degree of biasness. It also appears that as coverage increases, the ins/del ratio tends to 1.

	Coding region analysis: Coding region Indels may be categorised as Frame shift Indels and Non frameshift Indels. A lower proportion of Frameshift Indels may indicate a better quality data set but this depends also on the individuals sequenced.		Coding region analysis: Coding region Indels may be categorised as Frame shift Indels and Non frameshift Indels. A lower proportion of Frameshift Indels may indicate a better quality data set but this depends also on the individuals sequenced.

Atks: /* Insertion/Deletion ratios, Coding Regions and Overlap analysis */

2014-02-20T22:01:29Z

Insertion/Deletion ratios, Coding Regions and Overlap analysis

← Older revision		Revision as of 18:01, 20 February 2014
Line 240:		Line 240:
	* Mills chip: This is a subset of the Mills data set. There are genotypes here that are useful for subsetting polymophic subsets of variants that are present in samples common with your data set, this can potentially provide a better estimate of sensitivity. In general not very useful unless you happen to be working on 1000 Genomes data or any data set who's individuals are commonly studied.		* Mills chip: This is a subset of the Mills data set. There are genotypes here that are useful for subsetting polymophic subsets of variants that are present in samples common with your data set, this can potentially provide a better estimate of sensitivity. In general not very useful unless you happen to be working on 1000 Genomes data or any data set who's individuals are commonly studied.
	* Affy Exome Chip: This contains somewhat rare variants in exonic regions and is useful for exome chip analysis. You should subset your exome data to exome region Indels before comparing against this data set.		* Affy Exome Chip: This contains somewhat rare variants in exonic regions and is useful for exome chip analysis. You should subset your exome data to exome region Indels before comparing against this data set.

			This analysis supports filters too.

	==to document==		==to document==