ANGSD: Analysis of next generation Sequencing Data

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Allele Frequencies: Difference between revisions

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The allele frequency is the relative frequency of an allele across all alleles for a site.
<div class="keywords"> -domaf,-domaf,-domaf,-domaf,-domaf, domaf, domaf, domaf, domaf, domaf, domaf, dopost, SNP_pval </div>


This can be polarized according to the major/minor, reference/non-refernce or ancestral/derived. Therefore the choice of allele frequency estimator is closely related to choosing which alleles are segregating (see [[Inferring_Major_and_Minor_alleles]]).  
The allele frequency is the relative frequency of an allele for a site. This can be polarized according to the major/minor, reference/non-refernce or ancestral/derived. .Therefore the choice of allele frequency estimator is closely related to choosing which alleles are segregating (see [[Inferring_Major_and_Minor_alleles]]).  


We allow for frequency estimation from different input data:
We allow for frequency estimation from different input data:


# Genotype Likelihoods
# Genotype Likelihoods
# Genotype posteriors
# Genotype posterior probabilities
# Counts of bases
# Counts of bases


The allele frequency estimator from genotype likelihoods are from this  [[suYeon | publication]]
The allele frequency estimator from genotype likelihoods are from this  [[suYeon | publication]], and the base counts method is from this [[Li2010 |publication]].
 
For the case of the genotype likelihood based methods we allow for deviations from Hardy-Weinberg, namely we allow for users to supply a file containing inbreeding coefficients for each individual.
 
=Brief Overview=
=Brief Overview=
<pre>
<pre>
./angsd -doMaf  
./angsd -doMaf
-> angsd version: 0.570 build(Dec 17 2013 14:11:25)
abcFreq.cpp:
-> Analysis helpbox/synopsis information:
-doMaf 0 (Calculate persite frequencies '.mafs.gz')
------------------------
1: Frequency (fixed major and minor)
analysisMaf.cpp:
2: Frequency (fixed major unknown minor)
-doMaf 0
4: Frequency from genotype probabilities
1: BFGS frequency (known major minor)
8: AlleleCounts based method (known major minor)
2: EM frequency (known major minor)
NB. Filedumping is supressed if value is negative
4: BFGS frequency (unknown major minor)
8: EM frequency (unknown major minor)
16: Frequency from genotype probabilities
32: AlleleCounts based method (known major minor)
-doSNP 0
-minMaf 0.010000 0
-minLRT 24.000000 0
-ref (null)
-anc (null)
-eps 0.001000 [Only used for -doMaf &32]
-doPost 0 (Calculate posterior prob 3xgprob)
-doPost 0 (Calculate posterior prob 3xgprob)
1: Using frequency as prior
1: Using frequency as prior
2: Using uniform prior
2: Using uniform prior
-beagleProb 0 (Dump beagle style postprobs)
3: Using SFS as prior (still in development)
NB these frequency estimators requires major/minor -doMajorMinor
4: Using reference panel as prior (still in development), requires a site file with chr pos major minor af ac an
Filters:
-minMaf  -1.000000 (Remove sites with MAF below)
-SNP_pval 0.317311 (Remove sites with a pvalue larger)
-rmSNPs 0 (Remove infered SNPs instead of keeping them (pval > SNP_pval)
-rmTriallelic 0.000000 (Remove sites with a pvalue lower)
-forceMaf 0 (Write .mafs file when running -doAsso (by default does not output .mafs file with -doAsso))
-skipMissing 1 (Set post to 0.33 if missing (do not use freq as prior))
Extras:
-ref (null) (Filename for fasta reference)
-anc (null) (Filename for fasta ancestral)
-eps 0.001000 [Only used for -doMaf &8]
-beagleProb 0 (Dump beagle style postprobs)
-indFname (null) (file containing individual inbreedcoeficients)
-underFlowProtect 0 (file containing individual inbreedcoeficients)
NB These frequency estimators requires major/minor -doMajorMinor
 
</pre>
</pre>


=Allele Frequency estimation=
=Allele Frequency estimation=
The major and minor allele is first inferred from the data or given by the user (see [[Inferring_Major_and_Minor_alleles]]). This includes information from both major and minor allele, a reference genome (for major) or an ancestral genome.


; -doMaf [int]
; -doMaf [int]


INT=bfgs known minor
1: Known major, and Known minor. Here both the major and minor allele is assumed to be known (inferred or given by user). The allele frequency is the obtained using based on the genotype likelihoods. The allele frequency estimator from genotype likelihoods are from this [[suYeon | publication]] but using the EM algorithm and is briefly described [[SYKmaf|here]].
 
INT=2 EM known minor


INT=4 BFGS unknown minor
2: Known major, Unknown minor. Here the major allele is assumed to be known  (inferred or given by user) however the minor allele is not determined. Instead we sum over the 3 possible minor alleles weighted by their probabilities. The allele frequency estimator from genotype likelihoods are from this [[suYeon | publication]] but using the EM algorithm and is briefly described [[SYKmaf|here]].
.


INT=8 EM unknown minor
4: frequency based on genotype posterior probabilities. If genotype probabilities are used as input to ANGSD the allele frequency is estimated directly on these by [[postFreq|summing over the probabitlies]].


INT=16 frequencies from genotype probabilities
8: frequency based on base counts. This method does not rely on genotype likelihood or probabilities but instead infers the allele frequency directly on the base counts. The base counts method is from this [[Li2010 |publication]].


Multiple estimators can be used simultaniusly be summing up the above numbers. Thus -doMaf 7 (1+2+4) will use the first three estimators. If the allele frequencies are estimated from the genotype likelihoods then you need to infer the major and minor allele (-doMajorMinor)
Multiple estimators can be used simultaniusly be summing up the above numbers. Thus -doMaf 7 (1+2+4) will use the first three estimators. If the allele frequencies are estimated from the genotype likelihoods then you need to infer the major and minor allele (-doMajorMinor)


==Allele frequencies from genotype likelihoods==
;NB using -doMaf 4 is only supported if the posteriors are supplied as external files. Since the estimation of genotype posteriors in itself requires a maf estimator.
The allele frequency estimators are described in [[suYeon | citation]]. For testing reasons two optimazations are availeble. The BFGS and the EM algorithm. The EM algorithm is much faster then the BFGS. The allele frequencies are estimated by assuming that the site is diallelic and the major or minor alleles can be infered prior to the estimation or the uncertaincy of the minor allele can be incorborated into the model.


===ML estimator with known minor===
=Example=


First infer the [[Inferring_Major_and_Minor_alleles|Major and Minor]] allele and then use BFGS (-doMaf 1) optimazation or the EM algorithm (-doMaf 2) to estimate the allele frequencies.
==From genotype likelihood==
Example for estimating the allele frequencies both while assuming known major and minor allele but also while taking the uncertaincy of the minor allele inference into account. The [[Inferring_Major_and_Minor_alleles|inference of the major and minor]] allele is done directly from the genotype likelihood


<math>
<pre>
L(D|f) \propto \prod_i^N p(D_i|f) = \prod_i^N \sum_{g\in\{0,1,2\}}p(D_i|G=g)p(G=g|f)
./angsd -out out -doMajorMinor 1 -doMaf 3 -bam bam.filelist -GL 2
</math>
</pre>


<math>
==From genotype probabilities==
  \hat{f}=argmax_{f} L(D|f)
Example of the use of a genotype probability file for example from the output from beagle.  
</math>
 
===ML estimator with unknown minor===
 
First infer the [[Inferring_Major_and_Minor_alleles|Major]] allele and then use BFGS (-doMaf 4) optimazation or the EM algorithm (-doMaf 8) to estimate the allele frequencies. Here only the Major allele needs to be known and the uncertaincy of infering the minor allele is modelled.
 
Let <math>\{M,m\}</math> denote the major an minor allele assuming adiallelic site, then the maximum likelihood estimate of this pair is found using the likelihood function
 
<math>
  P(D|M,f) =  \prod_i P(D_i|M,f) =  \sum_m \sum_{A_1,A_2} P(D_i|G=A_1A_2)p(G=A_1A_2|m,M)p(m),
</math>
 
===Example===
Example for estimating the allele frequencies both while assuming known major and minor allele but also while taking the uncertaincy of the minor allele inference into account. The [[Inferring_Major_and_Minor_alleles|inference of the major and minor]] allele is done directly from the genotype likelihood


<pre>
<pre>
./angsd -out out -doMajorMinor 1 -doMaf 10 -bam bam.filelist
./angsd -out out -doMaf 4 -beagle beagle.file.gz
</pre>
</pre>


==Estimator from genotype probabilities==


If the genotype probabilities are known the frequencies can be estimated by summing up the posterior probabilities <math> p(G=g|D)</math> where <math>D</math> is the sequencing data and <math>g\in\{0,1,2\}</math> the allele count of the minor allele. The frequency estimate
==Estimator from base counts==


<math>
The allele frequencies can be infered directy from the sequencing data [[Li2010|citation]].
  \hat{f}=\frac{1}{2N}\sum_i^N \left(2p(G=2|D)+p(G=1|D)\right)
This works by using "counts" of alleles, and should be invoked like
</math>


===example===
Example of the use of a genotype probability file for example from the output from beagle.


<pre>
<pre>
./angsd -out out -doMaf 16 -beagle beagle.file.gz
./angsd -out out -doMajorMinor 2 -doMaf 8 -bam bam.filelist -doCounts 1
</pre>
</pre>


==Estimator from sequencing data==
The allele frequencies can be infered directy from the sequencing data [[Li2010|citation]].
This works by using "counts" of alleles, and should be invoked like
;-doCounts 1 -doPhat 1:


=Output data=
=Output data=
==.mafs==
==.mafs.gz==
<pre>
<pre>
chromo position major minor ref knownEM unknownEM nInd
chromo position major minor ref knownEM unknownEM nInd
Line 120: Line 107:


</pre>
</pre>
The first 4 columns are always defined to be:
;1. chromosome name
;2. position
;3. major allele
;4. minor allele
Depending on whether or not a reference and/or ancestral fasta files has been supplied these can occur as column 5 and 6.
There are 4 different MAF estimators the estimate for these are given by the names knownEM,unknownEM,knownBFGS,unknownBFGS.
Futhermore if -doSNP is included, then the corresponding LRT will be printed.
The nInd column is the effective sample size, as detmined by the genotype likelihoods.
Anders check below:


This pretty explanatory, nInd is the number of individuals where we have "reliable" reads (see bugs section)
;chromo
Depending on -doMaf INT, and -ref FILENAME and -anc FILENAME, extra column will be input.
chromosome name
;position
position
;major
major allele
;minor
minor allele
;knownEM
frequency using -doMaf 1
;unknownEM
frequency using -doMaf 2
;phat
frequency using -doMaf 8
;nInd  
is the number of individuals with data
;pK-EM
p-value for the frequency of (known) minor allele (-doSNPStat 1 -doMaf 1)
;pu-EM
p-value for the frequency of (unknown) minor allele (-doSNPStat 1 -doMaf 2)

Latest revision as of 11:16, 8 June 2023

-domaf,-domaf,-domaf,-domaf,-domaf, domaf, domaf, domaf, domaf, domaf, domaf, dopost, SNP_pval

The allele frequency is the relative frequency of an allele for a site. This can be polarized according to the major/minor, reference/non-refernce or ancestral/derived. .Therefore the choice of allele frequency estimator is closely related to choosing which alleles are segregating (see Inferring_Major_and_Minor_alleles).

We allow for frequency estimation from different input data:

  1. Genotype Likelihoods
  2. Genotype posterior probabilities
  3. Counts of bases

The allele frequency estimator from genotype likelihoods are from this publication, and the base counts method is from this publication.

For the case of the genotype likelihood based methods we allow for deviations from Hardy-Weinberg, namely we allow for users to supply a file containing inbreeding coefficients for each individual.

Brief Overview

 ./angsd -doMaf
abcFreq.cpp:
-doMaf	0 (Calculate persite frequencies '.mafs.gz')
	1: Frequency (fixed major and minor)
	2: Frequency (fixed major unknown minor)
	4: Frequency from genotype probabilities
	8: AlleleCounts based method (known major minor)
	NB. Filedumping is supressed if value is negative
-doPost	0	(Calculate posterior prob 3xgprob)
	1: Using frequency as prior
	2: Using uniform prior
	3: Using SFS as prior (still in development)
	4: Using reference panel as prior (still in development), requires a site file with chr pos major minor af ac an
Filters:
	-minMaf  	-1.000000	(Remove sites with MAF below)
	-SNP_pval	0.317311	(Remove sites with a pvalue larger)
	-rmSNPs 	0	(Remove infered SNPs instead of keeping them (pval > SNP_pval)
	-rmTriallelic	0.000000	(Remove sites with a pvalue lower)
	-forceMaf	0	(Write .mafs file when running -doAsso (by default does not output .mafs file with -doAsso))
	-skipMissing	1	(Set post to 0.33 if missing (do not use freq as prior))
Extras:
	-ref	(null)	(Filename for fasta reference)
	-anc	(null)	(Filename for fasta ancestral)
	-eps	0.001000 [Only used for -doMaf &8]
	-beagleProb	0 (Dump beagle style postprobs)
	-indFname	(null) (file containing individual inbreedcoeficients)
	-underFlowProtect	0 (file containing individual inbreedcoeficients)
NB These frequency estimators requires major/minor -doMajorMinor

Allele Frequency estimation

The major and minor allele is first inferred from the data or given by the user (see Inferring_Major_and_Minor_alleles). This includes information from both major and minor allele, a reference genome (for major) or an ancestral genome.

-doMaf [int]

1: Known major, and Known minor. Here both the major and minor allele is assumed to be known (inferred or given by user). The allele frequency is the obtained using based on the genotype likelihoods. The allele frequency estimator from genotype likelihoods are from this publication but using the EM algorithm and is briefly described here.

2: Known major, Unknown minor. Here the major allele is assumed to be known (inferred or given by user) however the minor allele is not determined. Instead we sum over the 3 possible minor alleles weighted by their probabilities. The allele frequency estimator from genotype likelihoods are from this publication but using the EM algorithm and is briefly described here. .

4: frequency based on genotype posterior probabilities. If genotype probabilities are used as input to ANGSD the allele frequency is estimated directly on these by summing over the probabitlies.

8: frequency based on base counts. This method does not rely on genotype likelihood or probabilities but instead infers the allele frequency directly on the base counts. The base counts method is from this publication.

Multiple estimators can be used simultaniusly be summing up the above numbers. Thus -doMaf 7 (1+2+4) will use the first three estimators. If the allele frequencies are estimated from the genotype likelihoods then you need to infer the major and minor allele (-doMajorMinor)

NB using -doMaf 4 is only supported if the posteriors are supplied as external files. Since the estimation of genotype posteriors in itself requires a maf estimator.

Example

From genotype likelihood

Example for estimating the allele frequencies both while assuming known major and minor allele but also while taking the uncertaincy of the minor allele inference into account. The inference of the major and minor allele is done directly from the genotype likelihood

./angsd -out out -doMajorMinor 1 -doMaf 3 -bam bam.filelist -GL 2

From genotype probabilities

Example of the use of a genotype probability file for example from the output from beagle.

./angsd -out out -doMaf 4 -beagle beagle.file.gz


Estimator from base counts

The allele frequencies can be infered directy from the sequencing data citation. This works by using "counts" of alleles, and should be invoked like


./angsd -out out -doMajorMinor 2 -doMaf 8 -bam bam.filelist -doCounts 1


Output data

.mafs.gz

chromo	position	major	minor	ref	knownEM	unknownEM	nInd
21      9719788 T       A       0.000001        -0.000012       3
21      9719789 G       A       0.000000        -0.000001       3
21      9719790 A       C       0.000000        -0.000004       3
21      9719791 G       A       0.000000        -0.000001       3
21      9719792 G       A       0.000000        -0.000002       3
21      9719793 G       T       0.498277        41.932766       3
21      9719794 T       A       0.000000        -0.000001       3
21      9719795 T       A       0.000000        -0.000001       3

chromo

chromosome name

position

position

major

major allele

minor

minor allele

knownEM

frequency using -doMaf 1

unknownEM

frequency using -doMaf 2

phat

frequency using -doMaf 8

nInd

is the number of individuals with data

pK-EM

p-value for the frequency of (known) minor allele (-doSNPStat 1 -doMaf 1)

pu-EM

p-value for the frequency of (unknown) minor allele (-doSNPStat 1 -doMaf 2)