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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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/ieu-a-import/processed/ieu-a-1081/ieu-a-1081.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/ieu-a-import/processed/ieu-a-1081/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Wed Feb 5 11:33:15 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1081/ieu-a-1081.vcf.gz ...
Read summary statistics for 277902 SNPs.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 273456 SNPs remain.
After merging with regression SNP LD, 273456 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0052 (0.0904)
Lambda GC: 1.0069
Mean Chi^2: 1.0065
Intercept: 1.0059 (0.0081)
Ratio: 0.9132 (1.2547)
Analysis finished at Wed Feb 5 11:33:26 2020
Total time elapsed: 10.69sQC metrics
Metrics
Metrics
{
"af_correlation": 0.901,
"inflation_factor": 1.0114,
"mean_EFFECT": -0.0019,
"n": 5983,
"n_snps": 277902,
"n_clumped_hits": 1,
"n_p_sig": 2,
"n_mono": 0,
"n_ns": 0,
"n_mac": 0,
"is_snpid_unique": true,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 1523,
"n_est": 5932.8311,
"ratio_se_n": 0.9958,
"mean_diff": 0.0017,
"ratio_diff": 7.3296,
"sd_y_est1": 4.374,
"sd_y_est2": 4.3557,
"r2_sum1": 0.1165,
"r2_sum2": 0.0061,
"r2_sum3": 0.0061,
"r2_sum4": 0.0061,
"ldsc_nsnp_merge_refpanel_ld": 273456,
"ldsc_nsnp_merge_regression_ld": 273456,
"ldsc_observed_scale_h2_beta": 0.0052,
"ldsc_observed_scale_h2_se": 0.0904,
"ldsc_intercept_beta": 1.0059,
"ldsc_intercept_se": 0.0081,
"ldsc_lambda_gc": 1.0069,
"ldsc_mean_chisq": 1.0065,
"ldsc_ratio": 0.9077
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | TRUE |
| is_snpid_non_unique | FALSE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | FALSE |
| n_p_sig | FALSE |
| miss_EFFECT | FALSE |
| miss_SE | FALSE |
| miss_PVAL | FALSE |
| ldsc_ratio | TRUE |
| ldsc_intercept_beta | FALSE |
| 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 | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 0 | 1.0000000 | 3 | 30 | 0 | 277902 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.870951e+00 | 5.858931e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▃▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.826565e+07 | 5.661605e+07 | 2.75640e+04 | 3.139125e+07 | 6.887509e+07 | 1.148308e+08 | 2.492107e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -1.934200e-03 | 1.061744e-01 | -7.88522e-01 | -6.762470e-02 | -9.579000e-04 | 6.473530e-02 | 7.204390e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.017040e-01 | 2.582270e-02 | 6.73018e-02 | 8.272310e-02 | 9.168540e-02 | 1.129408e-01 | 3.751430e-01 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.978997e-01 | 2.895269e-01 | 0.00000e+00 | 2.466538e-01 | 4.975589e-01 | 7.486654e-01 | 9.999935e-01 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.978997e-01 | 2.895269e-01 | 0.00000e+00 | 2.466541e-01 | 4.975589e-01 | 7.486660e-01 | 9.999935e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.982212e-01 | 2.505565e-01 | 3.16550e-02 | 1.792160e-01 | 3.501595e-01 | 5.925247e-01 | 9.669060e-01 | ▇▆▅▃▂ |
| numeric | AF_reference | 1523 | 0.9945197 | NA | NA | NA | NA | NA | 4.002327e-01 | 2.381874e-01 | 3.39460e-03 | 2.002800e-01 | 3.576280e-01 | 5.814700e-01 | 9.892170e-01 | ▆▇▆▅▂ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.983000e+03 | 0.000000e+00 | 5.98300e+03 | 5.983000e+03 | 5.983000e+03 | 5.983000e+03 | 5.983000e+03 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 1005806 | rs3934834 | C | T | -0.1563460 | 0.1250920 | 0.2113552 | 0.2113550 | 0.136072 | 0.223442 | 5983 |
| 1 | 1021415 | rs3737728 | A | G | -0.0458677 | 0.0869825 | 0.5979708 | 0.5979707 | 0.749223 | 0.812700 | 5983 |
| 1 | 1030565 | rs6687776 | C | T | 0.0973262 | 0.1103870 | 0.3779480 | 0.3779489 | 0.143079 | 0.306709 | 5983 |
| 1 | 1031540 | rs9651273 | A | G | -0.0062857 | 0.0857427 | 0.9415600 | 0.9415603 | 0.743051 | 0.881989 | 5983 |
| 1 | 1048955 | rs4970405 | A | G | 0.0586434 | 0.1230670 | 0.6337077 | 0.6337068 | 0.111120 | 0.110623 | 5983 |
| 1 | 1049950 | rs12726255 | A | G | 0.0877123 | 0.1105720 | 0.4276259 | 0.4276266 | 0.144108 | 0.289736 | 5983 |
| 1 | 1064979 | rs2298217 | C | T | 0.1021980 | 0.1016210 | 0.3145734 | 0.3145705 | 0.158750 | 0.164736 | 5983 |
| 1 | 1094738 | rs4970362 | A | G | 0.0080655 | 0.0847725 | 0.9242009 | 0.9242013 | 0.671114 | 0.604034 | 5983 |
| 1 | 1099342 | rs9660710 | A | C | -0.0752941 | 0.1493690 | 0.6142045 | 0.6142043 | 0.939391 | 0.829872 | 5983 |
| 1 | 1106473 | rs4970420 | G | A | 0.0361969 | 0.0983813 | 0.7129285 | 0.7129295 | 0.194042 | 0.550319 | 5983 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51109992 | rs9628185 | T | C | 0.0422032 | 0.0793098 | 0.5946357 | 0.5946353 | 0.5116210 | 0.4053510 | 5983 |
| 22 | 51121521 | rs7284093 | C | T | 0.0511623 | 0.1050890 | 0.6263657 | 0.6263665 | 0.1716300 | 0.0485224 | 5983 |
| 22 | 51123505 | rs9616816 | G | A | 0.0823368 | 0.0928926 | 0.3754205 | 0.3754206 | 0.2121580 | 0.3783950 | 5983 |
| 22 | 51147015 | rs2040487 | A | G | -0.0143710 | 0.0791250 | 0.8558773 | 0.8558778 | 0.4326850 | 0.4556710 | 5983 |
| 22 | 51163138 | rs715586 | C | T | 0.0796789 | 0.1080330 | 0.4607942 | 0.4607927 | 0.1560880 | 0.0902556 | 5983 |
| 22 | 51165664 | rs8137951 | G | A | 0.0360516 | 0.0877084 | 0.6810437 | 0.6810437 | 0.2895070 | 0.4063500 | 5983 |
| 22 | 51171693 | rs756638 | G | A | 0.0984933 | 0.0840269 | 0.2411315 | 0.2411313 | 0.2920750 | 0.3049120 | 5983 |
| 22 | 51175626 | rs3810648 | A | G | 0.3172360 | 0.1442060 | 0.0278157 | 0.0278154 | 0.0747168 | 0.1084270 | 5983 |
| 22 | 51178090 | rs2285395 | G | A | 0.2975080 | 0.1527970 | 0.0515252 | 0.0515251 | 0.0704060 | 0.0666933 | 5983 |
| 23 | 51666786 | rs14115 | A | G | 0.1183350 | 0.1713650 | 0.4898521 | 0.4898524 | 0.0496214 | NA | 5983 |
bcf preview
1 1005806 rs3934834 C T . PASS AF=0.136072 ES:SE:LP:AF:SS:ID -0.156346:0.125092:0.674987:0.136072:5983:rs3934834
1 1021415 rs3737728 A G . PASS AF=0.749223 ES:SE:LP:AF:SS:ID -0.0458677:0.0869825:0.22332:0.749223:5983:rs3737728
1 1030565 rs6687776 C T . PASS AF=0.143079 ES:SE:LP:AF:SS:ID 0.0973262:0.110387:0.422568:0.143079:5983:rs6687776
1 1031540 rs9651273 A G . PASS AF=0.743051 ES:SE:LP:AF:SS:ID -0.0062857:0.0857427:0.026152:0.743051:5983:rs9651273
1 1048955 rs4970405 A G . PASS AF=0.11112 ES:SE:LP:AF:SS:ID 0.0586434:0.123067:0.198111:0.11112:5983:rs4970405
1 1049950 rs12726255 A G . PASS AF=0.144108 ES:SE:LP:AF:SS:ID 0.0877123:0.110572:0.368936:0.144108:5983:rs12726255
1 1064979 rs2298217 C T . PASS AF=0.15875 ES:SE:LP:AF:SS:ID 0.102198:0.101621:0.502278:0.15875:5983:rs2298217
1 1094738 rs4970362 A G . PASS AF=0.671114 ES:SE:LP:AF:SS:ID 0.0080655:0.0847725:0.0342336:0.671114:5983:rs4970362
1 1099342 rs9660710 A C . PASS AF=0.939391 ES:SE:LP:AF:SS:ID -0.0752941:0.149369:0.211687:0.939391:5983:rs9660710
1 1106473 rs4970420 G A . PASS AF=0.194042 ES:SE:LP:AF:SS:ID 0.0361969:0.0983813:0.146954:0.194042:5983:rs4970420
1 1119858 rs1320565 C T . PASS AF=0.08378 ES:SE:LP:AF:SS:ID -0.136288:0.159881:0.404534:0.08378:5983:rs1320565
1 1121794 rs11260549 G A . PASS AF=0.144525 ES:SE:LP:AF:SS:ID -0.17665:0.127904:0.776649:0.144525:5983:rs11260549
1 1135242 rs9729550 A C . PASS AF=0.291841 ES:SE:LP:AF:SS:ID -0.126775:0.0925426:0.767726:0.291841:5983:rs9729550
1 1152631 rs11721 C A . PASS AF=0.078548 ES:SE:LP:AF:SS:ID 0.226647:0.132965:1.05415:0.078548:5983:rs11721
1 1156131 rs2887286 T C . PASS AF=0.176749 ES:SE:LP:AF:SS:ID -0.0171838:0.102955:0.0617586:0.176749:5983:rs2887286
1 1158277 rs3813199 G A . PASS AF=0.095036 ES:SE:LP:AF:SS:ID 0.194995:0.126008:0.914542:0.095036:5983:rs3813199
1 1162435 rs3766186 C A . PASS AF=0.091374 ES:SE:LP:AF:SS:ID 0.187029:0.128452:0.837474:0.091374:5983:rs3766186
1 1163804 rs7515488 C T . PASS AF=0.146067 ES:SE:LP:AF:SS:ID 0.0680357:0.109693:0.271563:0.146067:5983:rs7515488
1 1172907 rs715643 C T . PASS AF=0.053548 ES:SE:LP:AF:SS:ID 0.0611667:0.161695:0.151676:0.053548:5983:rs715643
1 1176597 rs6675798 T C . PASS AF=0.0904553 ES:SE:LP:AF:SS:ID 0.162144:0.131714:0.660923:0.0904553:5983:rs6675798
1 1211292 rs6685064 C T . PASS AF=0.074717 ES:SE:LP:AF:SS:ID -0.0966783:0.168653:0.246813:0.074717:5983:rs6685064
1 1314015 rs2649588 C T . PASS AF=0.941089 ES:SE:LP:AF:SS:ID 0.103242:0.173463:0.258278:0.941089:5983:rs2649588
1 1425700 rs819980 T C . PASS AF=0.0839415 ES:SE:LP:AF:SS:ID -0.0864362:0.166121:0.219798:0.0839415:5983:rs819980
1 1478180 rs3766178 T C . PASS AF=0.25121 ES:SE:LP:AF:SS:ID 0.119178:0.0863828:0.775479:0.25121:5983:rs3766178
1 1486834 rs3128342 C A . PASS AF=0.408215 ES:SE:LP:AF:SS:ID 0.0545345:0.0806727:0.301863:0.408215:5983:rs3128342
1 1493727 rs880051 G A . PASS AF=0.211571 ES:SE:LP:AF:SS:ID 0.0331818:0.0932597:0.141468:0.211571:5983:rs880051
1 1497824 rs2296716 C T . PASS AF=0.102089 ES:SE:LP:AF:SS:ID 0.0155289:0.122898:0.046023:0.102089:5983:rs2296716
1 1505255 rs6603793 C T . PASS AF=0.282715 ES:SE:LP:AF:SS:ID 0.105458:0.0847855:0.670471:0.282715:5983:rs6603793
1 1706160 rs7531583 A G . PASS AF=0.792666 ES:SE:LP:AF:SS:ID 0.0070347:0.0971174:0.0258314:0.792666:5983:rs7531583
1 1781220 rs6681938 T C . PASS AF=0.285946 ES:SE:LP:AF:SS:ID 0.0125595:0.0864258:0.053323:0.285946:5983:rs6681938
1 1801034 rs4648592 G A . PASS AF=0.28907 ES:SE:LP:AF:SS:ID 0.12605:0.0908184:0.782104:0.28907:5983:rs4648592
1 1810090 rs7525092 C T . PASS AF=0.28907 ES:SE:LP:AF:SS:ID 0.121491:0.0908452:0.742054:0.28907:5983:rs7525092
1 1844046 rs2474460 C T . PASS AF=0.495148 ES:SE:LP:AF:SS:ID -0.0999255:0.0820069:0.65163:0.495148:5983:rs2474460
1 1888193 rs3820011 C A . PASS AF=0.28704 ES:SE:LP:AF:SS:ID 0.0754262:0.0910994:0.389663:0.28704:5983:rs3820011
1 1892325 rs2803291 T C . PASS AF=0.82761 ES:SE:LP:AF:SS:ID 0.0256214:0.101127:0.0969145:0.82761:5983:rs2803291
1 2026361 rs12755035 G A . PASS AF=0.134321 ES:SE:LP:AF:SS:ID 0.147651:0.121814:0.646907:0.134321:5983:rs12755035
1 2026749 rs884080 A G . PASS AF=0.427156 ES:SE:LP:AF:SS:ID -0.0044289:0.0792607:0.0197969:0.427156:5983:rs884080
1 2033256 rs908742 G A . PASS AF=0.29379 ES:SE:LP:AF:SS:ID -0.104933:0.0859801:0.653061:0.29379:5983:rs908742
1 2058023 rs3128291 A G . PASS AF=0.886321 ES:SE:LP:AF:SS:ID -0.26974:0.113645:1.75401:0.886321:5983:rs3128291
1 2096638 rs3052 C T . PASS AF=0.108078 ES:SE:LP:AF:SS:ID 0.200462:0.121497:1.00456:0.108078:5983:rs3052
1 2113565 rs262688 T G . PASS AF=0.248291 ES:SE:LP:AF:SS:ID -0.0301399:0.0914075:0.129828:0.248291:5983:rs262688
1 2119833 rs2460002 A G . PASS AF=0.651429 ES:SE:LP:AF:SS:ID 0.0150125:0.0841968:0.066267:0.651429:5983:rs2460002
1 2140261 rs6665593 G A . PASS AF=0.130448 ES:SE:LP:AF:SS:ID 0.0136555:0.116732:0.0424529:0.130448:5983:rs6665593
1 2156362 rs2460000 A G . PASS AF=0.64712 ES:SE:LP:AF:SS:ID 0.0359465:0.0834824:0.176025:0.64712:5983:rs2460000
1 2195117 rs7547453 C T . PASS AF=0.36506 ES:SE:LP:AF:SS:ID 0.0261378:0.0764293:0.135275:0.36506:5983:rs7547453
1 2199057 rs11588312 C T . PASS AF=0.06662 ES:SE:LP:AF:SS:ID -0.198126:0.178239:0.574596:0.06662:5983:rs11588312
1 2204755 rs7553178 G A . PASS AF=0.685318 ES:SE:LP:AF:SS:ID -0.0077471:0.0801532:0.0347974:0.685318:5983:rs7553178
1 2211849 rs10910047 A G . PASS AF=0.595973 ES:SE:LP:AF:SS:ID -0.0151111:0.07981:0.0706692:0.595973:5983:rs10910047
1 2220649 rs2017143 C T . PASS AF=0.458096 ES:SE:LP:AF:SS:ID 0.0079258:0.0841943:0.0338581:0.458096:5983:rs2017143
1 2231463 rs903916 C T . PASS AF=0.311047 ES:SE:LP:AF:SS:ID -0.111183:0.0864965:0.701912:0.311047:5983:rs903916