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.
Contamination: Difference between revisions
No edit summary |
(→method) |
||
| Line 90: | Line 90: | ||
== | ==Method== | ||
The method is described in the supplementary of [[Rasmussen2011]] | The method is described in the supplementary of [[Rasmussen2011]] | ||
Revision as of 10:03, 28 June 2014
Angsd can estimate contamination, but only for chromosomes that exists in one genecopy (eg chrX for males). This method requires a list of polymorphic sites along with their frequency and we also recommend to discard regions with low mappability.
We have included a mappability and HapMap files for chrX these are found in the RES subfolder of the angsd source package. So if you are working with humans, and your sample is a male then you can estimate the contamination with the follow two commands.
- First we generate a binary count file for chrX for a single BAM file (ANGSD cprogram)
- Then we do a Fisher's exact test for finding a p-value, and jackknife to get an estimate of contamination (Rprogram)
An example are found below:
#run angsd ./angsd -i my.bam -r X: -doCounts 1 -iCounts 1 -minMapQ 30 -minQ 20 #do jackKnife in R Rscript contamination.R mapFile="map100.chrX.bz2" hapFile="hapMapCeuXlift.map.bz2" countFile="angsdput.icnts.gz" mc.cores=24
The contamination.R program is found in the R/ subfolder, and the resource files are found in the RES folder. The jackknive procedure can be quite slow, so we allocate 24 cores for this analysis mc.cores=24.
Output
The output from the above command is shown below
Rscript ../R/contamination.R mapFile="map100.chrX.bz2" hapFile="hapMapCeuXlift.map.bz2" countFile="angsdput.icnts.gz" mc.cores=24
Loading required package: parallel
-----------------------
Doing Fisher exact test for Method1:
SNP site adjacent site
minor base 616 3554
major base 198492 1589087
Fisher's Exact Test for Count Data
data: mat
p-value = 5.286e-13
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
1.271632 1.512213
sample estimates:
odds ratio
1.387606
-----------------------
Doing Fisher exact test for Method2:
SNP site adjacent site
minor base 114 654
major base 37983 304122
Fisher's Exact Test for Count Data
data: mat2
p-value = 0.001532
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
1.133367 1.705751
sample estimates:
odds ratio
1.395672
-----------------------
major and minor bases - Method1:
-4 -3 -2 -1 SNP site 1 2 3 4
minor base 427 417 475 437 616 486 439 427 446
major base 198651 198715 198656 198645 198492 198500 198681 198693 198546
-----------------------
major and minor bases - Method2:
-4 -3 -2 -1 SNP site 1 2 3 4
minor base 75 76 96 73 114 86 79 80 89
major base 38022 38021 38001 38024 37983 38011 38018 38017 38008
----------------------
Running jackknife for Method1 (could be slow)
Running jackknife for Method2 (could be slow)
$est
Method1 Method2
Contamination 0.03837625 0.03380983
llh 1034.078 483.5145
SE 0.002630455 0.003900376
Interpretation of outputfiles
Both methods shows a highly significant pvalue, and estimate the level of contamination to be approx 3%.
Method
The method is described in the supplementary of Rasmussen2011