ANGSD: Analysis of next generation Sequencing Data

Latest tar.gz version is (0.938/0.939 on github), see Change_log for changes, and download it here.

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In most analysis you are only interested in a subset of sites and not all sites. Currently we have the following filter options.
We allow for filtering at many different levels.
 
# Read level, MapQ, unique mapped reads etc
# Base level, qscore
# Sequencing depth
# Regions (using BAM indexing (active lookup))
# Single sites (passive lookup, also allows for forcing major and minor) [[Sites |-sites]]
# Filtering based on downstream analysis. minimum MAF, LRT for SNP calling etc.
# Trimming out the ends of the reads
# etc
 
It follows that some filters will select a subset of data, and some of the filters will discard certain sites. If multiple filters has been chosen, the analysis will be limited to the chain of filters.
 
=Filters for reads in Bam files=
 
We allow for filtering and manipulation a the read level. These filters include minimum mapping and base qualtity, paired reads and others. Additionally specific regions can be analysed. All of the filters for bam files are described in [[Input#BAM_files]].


=Selected Sites=
=Selected Sites=
We support 2 different kinds of inputfiles for filtering. Bim files, if you want to use a specific major minor, or plain textfiles containing chromosome tab position.
For analysing specfic regions see [[Input#BAM_files]]. If you are interested in running your analysis at individual sites that are distributed throughout the entire genome, it might be faster to simply to loop over the entire data, but only analyse the data at specific positions. This can be done by supplying the [[Sites | -sites]] argument. With this approach we also allows for the forcing of major/minor alleles using external information.


; -filter [bimfile.bim] or -filter [afile.keep]  
=Allele frequencies=
; -minMaf [float]: only work with sites with a maf above [float]


File is determed by suffix of file.
Requires [[Allele Frequency estimation | -doMaf]].


=Polymorphic sites=


Only use sites contained in the bim (plink format) file. With -doMajorMinor 3 the major/minor alleles from the bim file is used.
; -SNP_pval [float]: only work with sites with a p-value less than [float]


Example of a bim file
Requires [[Allele Frequency estimation | -doMaf]].
<pre>
1 rs11240767 0 728951 T C
1 rs3131972 0 752721 A G
1 rs3131969 0 754182 A G
1 rs3131967 0 754334 T C
1 rs1048488 0 760912 C T
1 rs12124819 0 776546 G A
1 rs4040617 0 779322 G A
1 rs4970383 0 838555 A C
</pre>
Columns are, chromosome name, rsnumber, position in centimorgan, position in bp and major/major.
Only column 1,4,5,6 are used. The major and minor state can also be encoded as 0,1,2,3,4. With 0=A,1=C,2=G,3=T,4=N


Example of a keep file
=Number of non missing individuals=
<pre>
chr1  100001
chr1  2500000
chr1  347348
</pre>


The .keep are implemented in 0.503 or above.


For the .bim file no ordering is assumed. We require that the .keep file is sorted according to chromosome.
; -minInd [int]: Only keep sites with at least minIndDepth (default is 1) from at least [int] individuals


=Allele frequencies=
=Extra=
; -minMaf [float]: only work with sites with a maf above 'float'
;-setMinDepth [int]:
Discard site if total sequencing depth (all individuals added together) is below [int].
Requires [[Alleles counts | -doCounts]]


=polymorphic sites=
;-setMaxDepth [int]:
Discard site if total sequencing depth (all individuals added together) is above [int]
[[Alleles counts | -doCounts]]


; -minLRT [float]: only work with sits with an LRT>float
;-setMinDepthInd [int]:
Discard individual if sequencing depth for an individual is below [int]. This filter is only applied to analysis which are based on counts of alleles i.e. analysis that uses [[Alleles counts | -doCounts]]


=Major minor=
;-setMaxDepthInd [int]:
=Number of non missing individuals=
Discard individual if sequencing depth for an individual is above [int] This filter is only applied to analysis which are based on counts of alleles i.e. analysis that uses [[Alleles counts | -doCounts]]




; -minKeepIndC [int]: only work with sites with information from atleast int individiduals, requires -doCounts 1


;-geno_minDepth [int]
Only call genotypes if the depth is as least [int] for that individuals


This requires [[Alleles counts | -doCounts]] and [[Genotype calling |-doGeno ]]


=Examples=


First we do a run with no filters


First we do a run with no filters
<pre>
<pre>
./angsd  -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1:
./angsd  -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1:
...
head TSK.mafs
chromo position major minor knownEM nInd
1 13999919 A C 0.000008 1
1 13999920 G A 0.000008 1
1 13999921 G A 0.000008 1
1 13999922 C A 0.000008 1
1 13999923 A C 0.000008 1
1 13999924 G A 0.000008 1
1 13999925 G A 0.000008 1
1 13999926 A C 0.000008 1
1 13999927 G A 0.000008 1
</pre>
</pre>
<div class="toccolours mw-collapsible mw-collapsed">
gunzip -c TSK.mafs.gz | head
<pre class="mw-collapsible-content">
chromo position major minor unknownEM nInd
1 13999919 A C 0.000006 1
1 13999920 G A 0.000006 1
1 13999921 G A 0.000006 1
1 13999922 C A 0.000006 1
1 13999923 A C 0.000006 1
1 13999924 G A 0.000006 1
1 13999925 G A 0.000006 1
1 13999926 A C 0.000006 1
1 13999927 G A 0.000006 1
</pre>
</div>


Now we do a filter with MAF cutoff of 1\%
Now we do a filter with MAF cutoff of 1\%


<pre>
<pre>
../angsd0.3/angsd -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1: -minMaf 0.01
./angsd -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1: -minMaf 0.01
head TSK.mafs  
</pre>
chromo position major minor knownEM nInd
 
1 13999950 T G 0.495291 2
<div class="toccolours mw-collapsible mw-collapsed">
1 14000019 G T 0.047247 9
gunzip -c TSK.mafs.gz | head
1 14000056 C T 0.055851 10
<pre class="mw-collapsible-content">
1 14000127 G T 0.060760 10
chromo position major minor unknownEM nInd
1 14000170 C T 0.052388 9
1 14000003 G A 0.032285 9
1 14000176 G A 0.047928 10
1 14000013 G A 0.058291 9
1 14000202 G A 0.279722 9
1 14000019 G T 0.013709 9
1 14000262 C T 0.058555 9
1 14000023 C A 0.025033 9
1 14000322 A G 0.040471 8
1 14000170 C T 0.031133 10
1 14000176 G A 0.028189 10
1 14000200 C A 0.075946 7
1 14000202 G A 0.257007 7
1 14000774 G T 0.030039 10
</pre>
</pre>
</div>


Similar if we only want sites with information for atleast 5 samples
Similar if we only want sites with information for atleast 5 samples
<pre>
<pre>
../angsd0.3/angsd -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1: -minKeepInd 5
./angsd -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1: -minInd 5
head TSK.mafs  
</pre>
chromo position major minor knownEM nInd
<div class="toccolours mw-collapsible mw-collapsed">
1 13999971 T A 0.000007 6
gunzip -c TSK.mafs.gz | head
1 13999972 G A 0.000007 6
<pre class="mw-collapsible-content">
1 13999973 C A 0.000005 5
chromo position major minor unknownEM nInd
1 13999974 G A 0.000006 6
1 13999972 G A 0.000003 5
1 13999973 C A 0.000002 5
1 13999974 G A 0.000002 5
1 13999975 C A 0.000002 5
1 13999975 C A 0.000002 5
1 13999976 C A 0.000004 7
1 13999976 C A 0.000002 5
1 13999977 A C 0.000005 8
1 13999977 A C 0.000000 5
1 13999978 C A 0.000005 8
1 13999978 C A 0.000000 5
1 13999979 T A 0.000005 8
1 13999979 T A 0.000000 5
1 13999980 G A 0.000001 5
</pre>
</pre>
</div>
If we are interested in all sites with a p-value of 10^(-6) of being variable
If we are interested in all sites with a p-value of 10^(-6) of being variable
<pre>
<pre>
../angsd0.3/angsd -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1: -minLRT 24 -doSNP 1
./angsd -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1: -SNP_pval 1e-6
head TSK.mafs  
</pre>
chromo position major minor knownEM pK-EM nInd
<div class="toccolours mw-collapsible mw-collapsed">
1 14000202 G A 0.279722 42.623150 9
gunzip -c TSK.mafs.gz | head
1 14000873 G A 0.212120 79.118476 10
<pre class="mw-collapsible-content">
1 14001018 T C 0.333736 89.040311 8
chromo position major minor unknownEM pu-EM nInd
1 14001867 A G 0.200232 47.195423 10
1 14000873 G A 0.282476 0.000000e+00 10
1 14002422 A T 0.167692 43.196259 9
1 14001018 T C 0.259890 7.494005e-14 9
1 14003581 C T 0.207404 58.593208 9
1 14001867 A G 0.272099 6.361578e-14 10
1 14004623 T C 0.219838 102.856433 10
1 14002422 A T 0.377890 0.000000e+00 9
1 14007493 A G 0.453217 28.398647 9
1 14003581 C T 0.194393 5.551115e-16 9
1 14007558 C T 0.395670 80.236777 7
1 14004623 T C 0.259172 2.424727e-13 10
 
1 14007493 A G 0.297176 5.114086e-07 9
1 14007558 C T 0.381770 0.000000e+00 8
1 14007649 G A 0.220547 1.054967e-11 9
</pre>
</pre>
 
</div>
 
==Deprecated options==
These options should either be included (as is) or be discarded
 
;-minDepth:
;-maxDepth:

Latest revision as of 07:49, 15 November 2019

We allow for filtering at many different levels.

  1. Read level, MapQ, unique mapped reads etc
  2. Base level, qscore
  3. Sequencing depth
  4. Regions (using BAM indexing (active lookup))
  5. Single sites (passive lookup, also allows for forcing major and minor) -sites
  6. Filtering based on downstream analysis. minimum MAF, LRT for SNP calling etc.
  7. Trimming out the ends of the reads
  8. etc

It follows that some filters will select a subset of data, and some of the filters will discard certain sites. If multiple filters has been chosen, the analysis will be limited to the chain of filters.

Filters for reads in Bam files

We allow for filtering and manipulation a the read level. These filters include minimum mapping and base qualtity, paired reads and others. Additionally specific regions can be analysed. All of the filters for bam files are described in Input#BAM_files.

Selected Sites

For analysing specfic regions see Input#BAM_files. If you are interested in running your analysis at individual sites that are distributed throughout the entire genome, it might be faster to simply to loop over the entire data, but only analyse the data at specific positions. This can be done by supplying the -sites argument. With this approach we also allows for the forcing of major/minor alleles using external information.

Allele frequencies

-minMaf [float]
only work with sites with a maf above [float]

Requires -doMaf.

Polymorphic sites

-SNP_pval [float]
only work with sites with a p-value less than [float]

Requires -doMaf.

Number of non missing individuals

-minInd [int]
Only keep sites with at least minIndDepth (default is 1) from at least [int] individuals

Extra

-setMinDepth [int]

Discard site if total sequencing depth (all individuals added together) is below [int]. Requires -doCounts

-setMaxDepth [int]

Discard site if total sequencing depth (all individuals added together) is above [int] -doCounts

-setMinDepthInd [int]

Discard individual if sequencing depth for an individual is below [int]. This filter is only applied to analysis which are based on counts of alleles i.e. analysis that uses -doCounts

-setMaxDepthInd [int]

Discard individual if sequencing depth for an individual is above [int] This filter is only applied to analysis which are based on counts of alleles i.e. analysis that uses -doCounts


-geno_minDepth [int]

Only call genotypes if the depth is as least [int] for that individuals

This requires -doCounts and -doGeno

Examples

First we do a run with no filters 

./angsd  -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1:

gunzip -c TSK.mafs.gz | head 

chromo	position	major	minor	unknownEM	nInd
1	13999919	A	C	0.000006	1
1	13999920	G	A	0.000006	1
1	13999921	G	A	0.000006	1
1	13999922	C	A	0.000006	1
1	13999923	A	C	0.000006	1
1	13999924	G	A	0.000006	1
1	13999925	G	A	0.000006	1
1	13999926	A	C	0.000006	1
1	13999927	G	A	0.000006	1

Now we do a filter with MAF cutoff of 1\% 

./angsd -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1: -minMaf 0.01

gunzip -c TSK.mafs.gz | head 

chromo	position	major	minor	unknownEM	nInd
1	14000003	G	A	0.032285	9
1	14000013	G	A	0.058291	9
1	14000019	G	T	0.013709	9
1	14000023	C	A	0.025033	9
1	14000170	C	T	0.031133	10
1	14000176	G	A	0.028189	10
1	14000200	C	A	0.075946	7
1	14000202	G	A	0.257007	7
1	14000774	G	T	0.030039	10

Similar if we only want sites with information for atleast 5 samples 

./angsd -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1: -minInd 5

gunzip -c TSK.mafs.gz | head 

chromo	position	major	minor	unknownEM	nInd
1	13999972	G	A	0.000003	5
1	13999973	C	A	0.000002	5
1	13999974	G	A	0.000002	5
1	13999975	C	A	0.000002	5
1	13999976	C	A	0.000002	5
1	13999977	A	C	0.000000	5
1	13999978	C	A	0.000000	5
1	13999979	T	A	0.000000	5
1	13999980	G	A	0.000001	5

If we are interested in all sites with a p-value of 10^(-6) of being variable 

./angsd -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1: -SNP_pval 1e-6

gunzip -c TSK.mafs.gz | head 

chromo	position	major	minor	unknownEM	pu-EM	nInd
1	14000873	G	A	0.282476	0.000000e+00	10
1	14001018	T	C	0.259890	7.494005e-14	9
1	14001867	A	G	0.272099	6.361578e-14	10
1	14002422	A	T	0.377890	0.000000e+00	9
1	14003581	C	T	0.194393	5.551115e-16	9
1	14004623	T	C	0.259172	2.424727e-13	10
1	14007493	A	G	0.297176	5.114086e-07	9
1	14007558	C	T	0.381770	0.000000e+00	8
1	14007649	G	A	0.220547	1.054967e-11	9
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