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.
Filters
Information on this page is for version 0.569 or higher. Sorry for confusion, hopefully program and wiki will be updated before weekend.
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
- 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. Eg setting a qscore threshold and an effective sample size filter along with a MAF filter will first. Remove the data with low qscores, then we found out the number of samples with data, and remove those below the threshold. Then we calculate the MAF and remove those sites with af MAF below the threshold.
This page will describe some of these filters, and it follows that only some are available in the case of BAM input.
Read level filters
We allow for filtering and manipulation a the read level using the following arguments.
- -only_proper_pairs [int]=0
Include only proper pairs (pairs of read with both mates mapped correctly). 1: include only proper (default), 0: use all reads. If your data is not paired end you have to choose 1
- -uniqueOnly [int]=0
remove reads that have multiple best hits.. 0 no (default), 1 remove
- -remove_bads [int]=1
Same as the samtools flags -x which removes read with a flag above 255 (not primary, failure and duplicate reads)
- -minQ [int]=0
minimum base quality
- -minMapQ [int]=0
minimum mapQ quality. Internally this is handled by setting the bases with a qscore below the threshold to 'N'. -baq [int] =0 perform baq computation, remember to cite the baq paper for this.
Selected Regions
BAM files allows for indexing which makes random retrieval of regions fast and easy. This section describes region lookup as we have implemented it in angsd.
- -r [region]
Specify a region with in a chromosome using the syntax [chr]:[start-stop]. examples
chr1:1-10000 \\ first 10000 based for chr1 chr2:50000- \\chr2 but exclude the first 50000 bases chr11:1- \\all of chr11 chr7:123456 //position 123456 of chr7
- -rf [region file]
specify multiple regions in a file.
The format for the regions supplied to the -rf file is the same the -r command line arguments.
Selected Sites
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.
Allele frequencies
- -minMaf [float]
- only work with sites with a maf above 'float'
Of cause requires -doMaf.
Polymorphic sites
- -minLRT [float]
- only work with sits with an LRT>float
Of cause requires -doMaf.
Number of non missing individuals
- -minInd [int]
- only work with sites with information from atleast int individiduals
Extra
- -setMinDepth
Discard site if sequencing depth is below threshold
- -setMaxDepth
Discard site if sequencing depth is above threshold
These filter is implemented in -doCounts.
- -geno_minDeph
Only call genotypes if per sample genotypes are above this threshold
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: ... 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
Now we do a filter with MAF cutoff of 1\%
../angsd0.3/angsd -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1: -minMaf 0.01 head TSK.mafs chromo position major minor knownEM nInd 1 13999950 T G 0.495291 2 1 14000019 G T 0.047247 9 1 14000056 C T 0.055851 10 1 14000127 G T 0.060760 10 1 14000170 C T 0.052388 9 1 14000176 G A 0.047928 10 1 14000202 G A 0.279722 9 1 14000262 C T 0.058555 9 1 14000322 A G 0.040471 8
Similar if we only want sites with information for atleast 5 samples
../angsd0.3/angsd -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1: -minKeepInd 5 head TSK.mafs chromo position major minor knownEM nInd 1 13999971 T A 0.000007 6 1 13999972 G A 0.000007 6 1 13999973 C A 0.000005 5 1 13999974 G A 0.000006 6 1 13999975 C A 0.000002 5 1 13999976 C A 0.000004 7 1 13999977 A C 0.000005 8 1 13999978 C A 0.000005 8 1 13999979 T A 0.000005 8
If we are interested in all sites with a p-value of 10^(-6) of being variable
../angsd0.3/angsd -doMaf 2 -doMajorMinor 1 -out TSK -bam bam.filelist -GL 1 -r 1: -minLRT 24 -doSNP 1 head TSK.mafs chromo position major minor knownEM pK-EM nInd 1 14000202 G A 0.279722 42.623150 9 1 14000873 G A 0.212120 79.118476 10 1 14001018 T C 0.333736 89.040311 8 1 14001867 A G 0.200232 47.195423 10 1 14002422 A T 0.167692 43.196259 9 1 14003581 C T 0.207404 58.593208 9 1 14004623 T C 0.219838 102.856433 10 1 14007493 A G 0.453217 28.398647 9 1 14007558 C T 0.395670 80.236777 7