Summary
Summary {data-width=650}
Manhattan plot
manhattan_plot
QQ plot
qq_plot
AF plot
af_plot
P-Z plot
pz_plot
beta_std plot
beta_std_plot
Metadata
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"file_date": "2019-10-27T07:27:46.687834",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST007236/EBI-a-GCST007236_data.json --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/hg38/hg38.fa; 1.1.1",
"reference": "file:/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/b37/human_g1k_v37.fasta",
"bcftools_annotateVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
"bcftools_annotateCommand": "annotate -a /mnt/storage/home/gh13047/mr-eve/vcf-reference-datasets/dbsnp/dbsnp.v153.b37.vcf.gz -c ID -o /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST007236/EBI-a-GCST007236.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST007236/EBI-a-GCST007236_data.vcf.gz; Date=Sun Oct 27 07:49:06 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST007236/ebi-a-GCST007236.vcf.gz; Date=Sun May 10 11:02:21 2020"
}
LDSC
*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call:
./ldsc.py \
--h2 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST007236/EBI-a-GCST007236.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST007236/ldsc.txt \
--snplist /data/ref/snplist.gz \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Sun Oct 27 08:13:57 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST007236/EBI-a-GCST007236.vcf.gz ...
and extracting SNPs specified in /data/ref/snplist.gz ...
Traceback (most recent call last):
File "./ldsc/ldsc.py", line 647, in <module>
sumstats.estimate_h2(args, log)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
args, log, args.h2)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 246, in _read_ld_sumstats
sumstats = _read_sumstats(args, log, fh, alleles=alleles, dropna=dropna)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 165, in _read_sumstats
sumstats = ps.sumstats(fh, alleles=alleles, dropna=dropna, slh=args.snplist)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 85, in sumstats
x = read_vcf(fh, alleles, slh)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 161, in read_vcf
with gzip.open(slh) as f:
File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 34, in open
return GzipFile(filename, mode, compresslevel)
File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 94, in __init__
fileobj = self.myfileobj = __builtin__.open(filename, mode or 'rb')
IOError: [Errno 2] No such file or directory: '/data/ref/snplist.gz'
Analysis finished at Sun Oct 27 08:15:27 2019
Total time elapsed: 1.0m:30.7sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9583,
"inflation_factor": "NA",
"mean_EFFECT": 0.6682,
"n": "-Inf",
"n_snps": 13578410,
"n_clumped_hits": 431,
"n_p_sig": 2240,
"n_mono": 0,
"n_ns": 5449249,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 747941,
"n_est": "NA",
"ratio_se_n": "NA",
"mean_diff": "NaN",
"ratio_diff": "NaN",
"sd_y_est1": "NaN",
"sd_y_est2": "NA",
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": "NA",
"ldsc_nsnp_merge_regression_ld": "NA",
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": "NA",
"ldsc_intercept_se": "NA",
"ldsc_lambda_gc": "NA",
"ldsc_mean_chisq": "NA",
"ldsc_ratio": "NA"
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | TRUE |
| n | TRUE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | TRUE |
| mean_EFFECT_01 | TRUE |
| mean_chisq | TRUE |
| n_p_sig | TRUE |
| miss_EFFECT | FALSE |
| miss_SE | FALSE |
| miss_PVAL | FALSE |
| ldsc_ratio | TRUE |
| ldsc_intercept_beta | TRUE |
| n_clumped_hits | FALSE |
| r2_sum1 | FALSE |
| r2_sum2 | FALSE |
| r2_sum3 | FALSE |
| r2_sum4 | FALSE |
Definitions
General metrics
af_correlation: Correlation coefficient betweenAFandAF_reference.inflation_factor(lambda): Genomic inflation factor.mean_EFFECT: Mean ofEFFECTsize.n: Maximum value of reported sample size across all SNPs, \(n\).n_clumped_hits: Number of clumped hits.n_snps: Number of SNPsn_p_sig: Number of SNPs with pvalue below5e-8.n_mono: Number of monomorphic (MAF == 1orMAF == 0) SNPs.n_ns: Number of SNPs with nonsense values:- alleles other than
A, C, G or T. - P-values
< 0or> 1. - negative or infinite standard errors (
<= 0or= Infinity). - infinite beta estimates or allele frequencies
< 0or> 1.
- alleles other than
n_mac: Number of cases whereMAC(\(2 \times N \times MAF\)) is less than6.is_snpid_unique:trueif the combination ofIDREFALTis unique and therefore no duplication in snpid.n_miss_<*>: Number ofNAobservations for<*>column.
se_n metrics
n_est: Estimated sample size value, \(\widehat{n}\).ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expectratio_se_nto be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.- \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
- \({z}_j = \frac{\beta_j}{{se}_j}\),
- and \(\beta_j\) is the reported effect size.
ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean ofdiffand the mean ofdiff2(expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.- \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
- \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.- \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
- \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
- and \({se}_j\) is the reported standard error.
sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.- \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
- \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),
r2 metrics
Sum of variance explained, calculated from the clumped top hits sample.
r2_sum<*>:r2statistics under various assumptions1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).
LDSC metrics
Metrics from LD regression
ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.ldsc_observed_scale_h2_{beta,se}Coefficient value and SE for total observed scale h2.ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.ldsc_lambda_gc: Lambda GC statistics.ldsc_mean_chisq: Mean \(\chi^2\) statistics.ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).
Flags
When a metric needs attention, the flag should return TRUE.
af_correlation:abs(af_correlation)< 0.7.inflation_factor:inflation_factor> 1.2.n:n(max reported sample size) < 10000.is_snpid_non_unique: NOTis_snpid_unique.mean_EFFECT_nonfinite:mean(EFFECT)isNA,NaN, orInf.mean_EFFECT_05:abs(mean(EFFECT))> 0.5.mean_EFFECT_01:abs(mean(EFFECT))> 0.1.mean_chisq:ldsc_mean_chisq> 1.3 orldsc_mean_chisq< 0.7.n_p_sig:n_p_sig> 1000.miss_<*>:n_miss_<*>/n_snps> 0.01.ldsc_ratio:ldsc_ratio> 0.5ldsc_intercept_beta:ldsc_intercept_beta> 1.5n_clumped_hits:n_clumped_hits> 1000r2_sum<*>:r2_sum<*>> 0.5
Plots
- Manhattan plot
- Red line: \(-log_{10}^{5 \times 10^{-8}}\)
- Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
- QQ plot
- AF plot
- P-Z plot
- beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)
Diagnostics
Details
Summary stats
| skim_type | skim_variable | n_missing | complete_rate | character.min | character.max | character.empty | character.n_unique | character.whitespace | logical.mean | logical.count | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 0 | 1.0000000 | 3 | 59 | 0 | 13496359 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 45 | 0 | 24263 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 42 | 0 | 16804 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 13496471 | 0.0000000 | NA | NA | NA | NA | NA | NaN | : | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.723791e+00 | 5.850441e+00 | 1.0000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.885235e+07 | 5.624015e+07 | 1.1570e+03 | 3.252689e+07 | 6.955872e+07 | 1.145990e+08 | 2.492298e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 6.681628e-01 | 2.206493e-01 | -1.0000e+00 | 4.715870e-01 | 6.549480e-01 | 8.784310e-01 | 1.000000e+00 | ▁▁▁▆▇ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.832580e-02 | 5.861980e-02 | 9.4629e-03 | 1.403350e-02 | 2.992350e-02 | 8.802230e-02 | 3.111010e-01 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.182961e+00 | 2.374825e+00 | 0.0000e+00 | 1.152009e-01 | 5.146240e-01 | 1.505411e+00 | 6.018385e+02 | ▇▁▁▁▁ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.484000e-03 | 2.360430e-02 | 0.0000e+00 | 0.000000e+00 | 0.000000e+00 | 0.000000e+00 | 3.070978e-01 | ▇▁▁▁▁ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.752081e-01 | 2.491779e-01 | 7.0080e-04 | 5.786100e-03 | 4.364760e-02 | 2.572320e-01 | 9.992080e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 747941 | 0.9445825 | NA | NA | NA | NA | NA | NA | NA | 1.794197e-01 | 2.438676e-01 | 0.0000e+00 | 4.592600e-03 | 6.010380e-02 | 2.683710e-01 | 1.000000e+00 | ▇▂▁▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 55850 | rs191890754 | C | G | 0.374380 | 0.1097290 | 0.5886417 | 0.0006452 | 0.0050374 | NA | NA |
| 1 | 61743 | rs184286948 | G | C | 0.349813 | 0.2081040 | 1.1988499 | 0.0927721 | 0.0014630 | 0.0045926 | NA |
| 1 | 88188 | rs148331237 | C | A | 0.305173 | 0.0950864 | 1.7024682 | 0.0013300 | 0.0081978 | 0.0033946 | NA |
| 1 | 99719 | rs183898652 | C | T | 0.324218 | 0.1830260 | 3.4726179 | 0.0764890 | 0.0021039 | 0.0089856 | NA |
| 1 | 534540 | rs183186584 | G | T | 0.386841 | 0.1384060 | 1.2998014 | 0.0051904 | 0.0030403 | 0.0011981 | NA |
| 1 | 669228 | rs187185296 | G | A | 0.473190 | 0.1424030 | 2.2877523 | 0.0008909 | 0.0023126 | 0.0001997 | NA |
| 1 | 701131 | rs185335630 | A | C | 0.316222 | 0.1541090 | 0.7863774 | 0.0401758 | 0.0029933 | 0.0041933 | NA |
| 1 | 712583 | rs142048655 | T | C | 0.585035 | 0.1295310 | 0.3296477 | 0.0000063 | 0.0023907 | 0.0001997 | NA |
| 1 | 713337 | rs184249808 | G | A | 0.376975 | 0.1632120 | 1.5173194 | 0.0209033 | 0.0024171 | 0.0071885 | NA |
| 1 | 715211 | rs184426933 | C | G | 0.499511 | 0.1215050 | 0.0072905 | 0.0000394 | 0.0031305 | NA | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154902741 | rs187527392 | G | C | 0.380585 | 0.0157308 | 0.0233212 | 0.0000000 | 0.5777660 | NA | NA |
| 23 | 154902743 | rs192049455 | G | C | 0.387574 | 0.0156039 | 0.0548479 | 0.0000000 | 0.5812960 | NA | NA |
| 23 | 154903802 | rs138894319 | G | A | 0.733597 | 0.0206104 | 0.0351471 | 0.0000000 | 0.0802178 | 0.0185430 | NA |
| 23 | 154910802 | rs147364233 | C | T | 0.679735 | 0.0297552 | 0.1665559 | 0.0000000 | 0.0396267 | 0.1070200 | NA |
| 23 | 154914662 | rs181330040 | C | T | 0.869178 | 0.1189390 | 0.4559561 | 0.0000000 | 0.0017892 | NA | NA |
| 23 | 154915730 | rs143362946 | C | T | 0.893196 | 0.0326066 | 0.0016448 | 0.0000000 | 0.0247238 | 0.0307285 | NA |
| 23 | 154916845 | rs669237 | G | T | 0.885280 | 0.0118508 | 0.0020713 | 0.0000000 | 0.2457750 | 0.4166890 | NA |
| 23 | 154918383 | rs641588 | G | T | 0.886534 | 0.0118817 | 0.0043470 | 0.0000000 | 0.2424240 | 0.3565560 | NA |
| 23 | 154926315 | rs145589925 | A | C | 0.302740 | 0.1069070 | 0.0310077 | 0.0046286 | 0.0066350 | 0.0037086 | NA |
| 23 | 154929412 | rs557132 | C | T | 0.881486 | 0.0119407 | 0.0057314 | 0.0000000 | 0.2407430 | 0.3568210 | NA |
bcf preview
1 55850 rs191890754 C G . PASS AF=0.00503738 ES:SE:LP:AF:ID 0.37438:0.109729:0.230149:0.00503738:rs191890754
1 61743 rs184286948 G C . PASS AF=0.00146299 ES:SE:LP:AF:ID 0.349813:0.208104:-0.0787648:0.00146299:rs184286948
1 88188 rs148331237 C A . PASS AF=0.00819782 ES:SE:LP:AF:ID 0.305173:0.0950864:-0.231079:0.00819782:rs148331237
1 99719 rs183898652 C T . PASS AF=0.0021039 ES:SE:LP:AF:ID 0.324218:0.183026:-0.540657:0.0021039:rs183898652
1 534540 rs183186584 G T . PASS AF=0.00304029 ES:SE:LP:AF:ID 0.386841:0.138406:-0.113877:0.00304029:rs183186584
1 669228 rs187185296 G A . PASS AF=0.0023126 ES:SE:LP:AF:ID 0.47319:0.142403:-0.359409:0.0023126:rs187185296
1 701131 rs185335630 A C . PASS AF=0.00299333 ES:SE:LP:AF:ID 0.316222:0.154109:0.104369:0.00299333:rs185335630
1 712583 rs142048655 T C . PASS AF=0.0023907 ES:SE:LP:AF:ID 0.585035:0.129531:0.48195:0.0023907:rs142048655
1 713337 rs184249808 G A . PASS AF=0.0024171 ES:SE:LP:AF:ID 0.376975:0.163212:-0.181077:0.0024171:rs184249808
1 715211 rs184426933 C G . PASS AF=0.00313049 ES:SE:LP:AF:ID 0.499511:0.121505:2.13724:0.00313049:rs184426933
1 720468 rs187315357 G A . PASS AF=0.00377569 ES:SE:LP:AF:ID 0.363827:0.12849:-0.302424:0.00377569:rs187315357
1 723379 rs181223789 T A . PASS AF=0.00241745 ES:SE:LP:AF:ID 0.582859:0.129005:0.511315:0.00241745:rs181223789
1 736689 rs181876450 T C . PASS AF=0.00645792 ES:SE:LP:AF:ID 0.303149:0.108689:0.134345:0.00645792:rs181876450
1 745642 rs200097270 AC A . PASS AF=0.0141252 ES:SE:LP:AF:ID 0.305535:0.0738519:0.418791:0.0141252:rs200097270
1 748332 rs182373484 T C . PASS AF=0.00411936 ES:SE:LP:AF:ID 0.353748:0.126618:0.169099:0.00411936:rs182373484
1 748524 rs144265613 C T . PASS AF=0.0030819 ES:SE:LP:AF:ID 0.354413:0.142328:-0.419984:0.0030819:rs144265613
1 755435 rs184270342 T G . PASS AF=0.00143177 ES:SE:LP:AF:ID 0.581506:0.180259:-0.764179:0.00143177:rs184270342
1 767811 rs140378911 G C . PASS AF=0.0229196 ES:SE:LP:AF:ID 0.301416:0.0583518:0.922283:0.0229196:rs140378911
1 770281 rs188583355 T A . PASS AF=0.00215254 ES:SE:LP:AF:ID 0.419804:0.160753:0.328452:0.00215254:rs188583355
1 772172 rs141427868 C G . PASS AF=0.00137714 ES:SE:LP:AF:ID 0.315806:0.232257:0.114382:0.00137714:rs141427868
1 775426 rs2905037 G A . PASS AF=0.998058 ES:SE:LP:AF:ID 0.35343:0.185015:1.21957:0.998058:rs2905037
1 783632 rs193023236 G A . PASS AF=0.0030342 ES:SE:LP:AF:ID 0.326872:0.15418:0.00821502:0.0030342:rs193023236
1 789256 rs3131939 T C . PASS AF=0.989984 ES:SE:LP:AF:ID 0.323458:0.0847601:0.734216:0.989984:rs3131939
1 791932 rs149451138 C T . PASS AF=0.0035666 ES:SE:LP:AF:ID 0.304673:0.146634:-0.013166:0.0035666:rs149451138
1 793470 rs184843908 G A . PASS AF=0.0103438 ES:SE:LP:AF:ID 0.302945:0.0860253:1.30623:0.0103438:rs184843908
1 794319 rs186495636 G A . PASS AF=0.00144783 ES:SE:LP:AF:ID 0.349671:0.214841:0.367142:0.00144783:rs186495636
1 794368 rs191334345 G A . PASS AF=0.0018618 ES:SE:LP:AF:ID 0.528108:0.155663:0.12612:0.0018618:rs191334345
1 794787 rs183239437 A G . PASS AF=0.00199079 ES:SE:LP:AF:ID 0.370662:0.176137:1.47776:0.00199079:rs183239437
1 795131 rs187620961 G A . PASS AF=0.00216635 ES:SE:LP:AF:ID 0.423305:0.159573:0.329719:0.00216635:rs187620961
1 796298 rs143060708 C G . PASS AF=0.00302765 ES:SE:LP:AF:ID 0.380693:0.139629:1.02301:0.00302765:rs143060708
1 799346 rs184260340 C A . PASS AF=0.00265105 ES:SE:LP:AF:ID 0.304304:0.169821:1.01126:0.00265105:rs184260340
1 799389 rs187038627 G A . PASS AF=0.0091864 ES:SE:LP:AF:ID 0.319133:0.0888176:1.32913:0.0091864:rs187038627
1 801136 rs140609992 C T . PASS AF=0.00129571 ES:SE:LP:AF:ID 0.37602:0.218836:0.958256:0.00129571:rs140609992
1 801848 rs114911728 C A . PASS AF=0.00507533 ES:SE:LP:AF:ID 0.457065:0.0999171:1.47136:0.00507533:rs114911728
1 802671 rs191771620 T G . PASS AF=0.003486 ES:SE:LP:AF:ID 0.376492:0.132353:0.841553:0.003486:rs191771620
1 803192 rs190240504 C T . PASS AF=0.00267073 ES:SE:LP:AF:ID 0.468957:0.133352:-0.391803:0.00267073:rs190240504
1 809001 rs184951212 G A . PASS AF=0.00322111 ES:SE:LP:AF:ID 0.515872:0.117872:2.11274:0.00322111:rs184951212
1 810470 rs181485325 C A . PASS AF=0.00120633 ES:SE:LP:AF:ID 0.327783:0.238857:0.218073:0.00120633:rs181485325
1 810777 rs143204076 C G . PASS AF=0.0130197 ES:SE:LP:AF:ID 0.313919:0.0749837:-0.43058:0.0130197:rs143204076
1 812717 rs151199172 G T . PASS AF=0.00173359 ES:SE:LP:AF:ID 0.513626:0.160932:0.494497:0.00173359:rs151199172
1 819065 rs188466450 C T . PASS AF=0.0068528 ES:SE:LP:AF:ID 0.374311:0.0946198:0.500211:0.0068528:rs188466450
1 819467 rs187253977 T A . PASS AF=0.00151854 ES:SE:LP:AF:ID 0.306759:0.220291:1.12388:0.00151854:rs187253977
1 823790 rs143626389 G A . PASS AF=0.0209886 ES:SE:LP:AF:ID 0.311095:0.059865:2.44794:0.0209886:rs143626389
1 824357 rs80134645 C T . PASS AF=0.00289833 ES:SE:LP:AF:ID 0.652818:0.111692:2.67812:0.00289833:rs80134645
1 824666 rs140725574 C A . PASS AF=0.0047316 ES:SE:LP:AF:ID 0.401218:0.110035:1.97168:0.0047316:rs140725574
1 830791 rs184031231 C T . PASS AF=0.00704278 ES:SE:LP:AF:ID 0.316247:0.100482:-0.571112:0.00704278:rs184031231
1 834240 rs188158544 G A . PASS AF=0.00218954 ES:SE:LP:AF:ID 0.368178:0.173388:-0.42535:0.00218954:rs188158544
1 834830 rs116452738 G A . PASS AF=0.0121869 ES:SE:LP:AF:ID 0.392707:0.0709605:-0.437844:0.0121869:rs116452738
1 837096 rs144333274 C T . PASS AF=0.00684682 ES:SE:LP:AF:ID 0.322924:0.100812:-0.548135:0.00684682:rs144333274
1 837214 rs72631888 G C . PASS AF=0.0099436 ES:SE:LP:AF:ID 0.30113:0.088438:0.448115:0.0099436:rs72631888