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-1284/ieu-a-1284.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-1284/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 09:06:45 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1284/ieu-a-1284.vcf.gz ...
Read summary statistics for 5873093 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, 1105952 SNPs remain.
After merging with regression SNP LD, 1105952 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0835 (0.0078)
Lambda GC: 1.2728
Mean Chi^2: 1.397
Intercept: 1.1464 (0.0113)
Ratio: 0.3688 (0.0285)
Analysis finished at Wed Feb 5 09:07:45 2020
Total time elapsed: 59.8sQC metrics
Metrics
Metrics
{
"af_correlation": 0.8847,
"inflation_factor": 1.2488,
"mean_EFFECT": 0,
"n": 143658,
"n_snps": 5873093,
"n_clumped_hits": 69,
"n_p_sig": 4001,
"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": 13,
"n_miss_AF_reference": 65926,
"n_est": 139578.2209,
"ratio_se_n": 0.9857,
"mean_diff": -1.1631e-06,
"ratio_diff": 1.05,
"sd_y_est1": 1.0187,
"sd_y_est2": 1.0041,
"r2_sum1": 0.0282,
"r2_sum2": 0.0272,
"r2_sum3": 0.028,
"r2_sum4": 0.0259,
"ldsc_nsnp_merge_refpanel_ld": 1105952,
"ldsc_nsnp_merge_regression_ld": 1105952,
"ldsc_observed_scale_h2_beta": 0.0835,
"ldsc_observed_scale_h2_se": 0.0078,
"ldsc_intercept_beta": 1.1464,
"ldsc_intercept_se": 0.0113,
"ldsc_lambda_gc": 1.2728,
"ldsc_mean_chisq": 1.397,
"ldsc_ratio": 0.3688
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | TRUE |
| n | FALSE |
| is_snpid_non_unique | FALSE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | TRUE |
| n_p_sig | TRUE |
| miss_EFFECT | FALSE |
| miss_SE | FALSE |
| miss_PVAL | FALSE |
| ldsc_ratio | FALSE |
| 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 | 57 | 0 | 5873093 | 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 | 8.575870e+00 | 5.709816e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.944957e+07 | 5.627051e+07 | 8.28000e+02 | 3.314966e+07 | 7.041405e+07 | 1.152050e+08 | 2.492026e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.200000e-05 | 8.821800e-03 | -8.76400e-01 | -4.162000e-03 | 8.300000e-06 | 4.176000e-03 | 4.984000e-01 | ▁▁▁▇▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 6.630500e-03 | 4.704800e-03 | 3.69700e-03 | 4.043000e-03 | 4.912000e-03 | 7.341000e-03 | 4.162000e-01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.631280e-01 | 2.989897e-01 | 0.00000e+00 | 1.950999e-01 | 4.510005e-01 | 7.223006e-01 | 1.000000e+00 | ▇▆▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.631280e-01 | 2.989897e-01 | 0.00000e+00 | 1.950910e-01 | 4.509553e-01 | 7.222533e-01 | 9.999998e-01 | ▇▆▆▆▆ |
| numeric | AF | 13 | 0.9999978 | NA | NA | NA | NA | NA | 3.155587e-01 | 2.708626e-01 | 1.00000e-04 | 8.310000e-02 | 2.340000e-01 | 4.980000e-01 | 9.999000e-01 | ▇▃▂▂▂ |
| numeric | AF_reference | 65926 | 0.9887749 | NA | NA | NA | NA | NA | 3.012504e-01 | 2.417380e-01 | 0.00000e+00 | 1.022360e-01 | 2.348240e-01 | 4.596650e-01 | 1.000000e+00 | ▇▅▃▂▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.436580e+05 | 0.000000e+00 | 1.43658e+05 | 1.436580e+05 | 1.436580e+05 | 1.436580e+05 | 1.436580e+05 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 752566 | rs3094315 | G | A | -0.001455 | 0.005150 | 0.7774993 | 0.7775415 | 0.8438 | 0.7182510 | 143658 |
| 1 | 845635 | rs117086422 | C | T | 0.002806 | 0.005750 | 0.6256004 | 0.6255498 | 0.1402 | 0.1585460 | 143658 |
| 1 | 846078 | rs28612348 | C | T | 0.002756 | 0.005756 | 0.6319999 | 0.6320776 | 0.1419 | 0.1617410 | 143658 |
| 1 | 846808 | rs4475691 | C | T | 0.002793 | 0.005347 | 0.6015005 | 0.6014274 | 0.1411 | 0.2547920 | 143658 |
| 1 | 846864 | rs950122 | G | C | 0.002795 | 0.005348 | 0.6012000 | 0.6012350 | 0.1411 | 0.2228430 | 143658 |
| 1 | 847228 | rs3905286 | C | T | 0.003558 | 0.005409 | 0.5107002 | 0.5106714 | 0.1391 | 0.2426120 | 143658 |
| 1 | 847491 | rs28407778 | G | A | 0.003453 | 0.005411 | 0.5234003 | 0.5233796 | 0.1394 | 0.2519970 | 143658 |
| 1 | 847983 | rs79932038 | C | T | 0.022430 | 0.011910 | 0.0595594 | 0.0596609 | 0.0318 | 0.0015974 | 143658 |
| 1 | 848090 | rs4246505 | G | A | 0.003598 | 0.005409 | 0.5060006 | 0.5059305 | 0.1389 | 0.1711260 | 143658 |
| 1 | 848445 | rs4626817 | G | A | 0.003598 | 0.005409 | 0.5060006 | 0.5059305 | 0.1389 | 0.2505990 | 143658 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51164287 | rs6009957 | T | C | 0.002289 | 0.003932 | 0.5605005 | 0.5604680 | 0.4010 | 0.4155350 | 143658 |
| 22 | 51165390 | rs76268556 | C | T | 0.022130 | 0.007899 | 0.0050900 | 0.0050847 | 0.0772 | 0.0515176 | 143658 |
| 22 | 51165664 | rs8137951 | G | A | 0.002284 | 0.003870 | 0.5550000 | 0.5550694 | 0.3924 | 0.4063500 | 143658 |
| 22 | 51169045 | rs8140772 | C | T | 0.019970 | 0.006658 | 0.0027070 | 0.0027051 | 0.0903 | 0.0632987 | 143658 |
| 22 | 51171497 | rs2301584 | G | A | -0.001291 | 0.004308 | 0.7644006 | 0.7644251 | 0.2496 | 0.2533950 | 143658 |
| 22 | 51171667 | rs41281537 | G | A | 0.018720 | 0.006528 | 0.0041420 | 0.0041354 | 0.0910 | 0.0577077 | 143658 |
| 22 | 51171693 | rs756638 | G | A | 0.010970 | 0.005884 | 0.0622601 | 0.0622686 | 0.1129 | 0.3049120 | 143658 |
| 22 | 51172460 | rs5770824 | T | C | 0.019230 | 0.006724 | 0.0042320 | 0.0042377 | 0.0984 | 0.0684904 | 143658 |
| 22 | 51175626 | rs3810648 | A | G | -0.021570 | 0.018200 | 0.2358001 | 0.2359523 | 0.0104 | 0.1084270 | 143658 |
| 22 | 51178090 | rs2285395 | G | A | -0.017980 | 0.018280 | 0.3253000 | 0.3253178 | 0.0103 | 0.0666933 | 143658 |
bcf preview
1 752566 rs3094315 G A . PASS AF=0.8438 ES:SE:LP:AF:SS:ID -0.001455:0.00515:0.1093:0.8438:143658:rs3094315
1 845635 rs117086422 C T . PASS AF=0.1402 ES:SE:LP:AF:SS:ID 0.002806:0.00575:0.203703:0.1402:143658:rs117086422
1 846078 rs28612348 C T . PASS AF=0.1419 ES:SE:LP:AF:SS:ID 0.002756:0.005756:0.199283:0.1419:143658:rs28612348
1 846808 rs4475691 C T . PASS AF=0.1411 ES:SE:LP:AF:SS:ID 0.002793:0.005347:0.220764:0.1411:143658:rs4475691
1 846864 rs950122 G C . PASS AF=0.1411 ES:SE:LP:AF:SS:ID 0.002795:0.005348:0.220981:0.1411:143658:rs950122
1 847228 rs3905286 C T . PASS AF=0.1391 ES:SE:LP:AF:SS:ID 0.003558:0.005409:0.291834:0.1391:143658:rs3905286
1 847491 rs28407778 G A . PASS AF=0.1394 ES:SE:LP:AF:SS:ID 0.003453:0.005411:0.281166:0.1394:143658:rs28407778
1 847983 rs79932038 C T . PASS AF=0.0318 ES:SE:LP:AF:SS:ID 0.02243:0.01191:1.22505:0.0318:143658:rs79932038
1 848090 rs4246505 G A . PASS AF=0.1389 ES:SE:LP:AF:SS:ID 0.003598:0.005409:0.295849:0.1389:143658:rs4246505
1 848445 rs4626817 G A . PASS AF=0.1389 ES:SE:LP:AF:SS:ID 0.003598:0.005409:0.295849:0.1389:143658:rs4626817
1 848456 rs11507767 A G . PASS AF=0.1389 ES:SE:LP:AF:SS:ID 0.003599:0.005409:0.296021:0.1389:143658:rs11507767
1 848738 rs3829741 C T . PASS AF=0.1392 ES:SE:LP:AF:SS:ID 0.003491:0.00541:0.285084:0.1392:143658:rs3829741
1 850062 rs28723578 A T . PASS AF=0.1389 ES:SE:LP:AF:SS:ID 0.003488:0.005489:0.279675:0.1389:143658:rs28723578
1 850123 rs28622257 C T . PASS AF=0.1372 ES:SE:LP:AF:SS:ID 0.003539:0.005475:0.285586:0.1372:143658:rs28622257
1 850373 rs151325546 A G . PASS AF=0.0375 ES:SE:LP:AF:SS:ID 0.01885:0.01:1.22526:0.0375:143658:rs151325546
1 851190 rs28609852 G A . PASS AF=0.1389 ES:SE:LP:AF:SS:ID 0.003522:0.0054:0.288868:0.1389:143658:rs28609852
1 851204 rs28552953 G C . PASS AF=0.1389 ES:SE:LP:AF:SS:ID 0.003522:0.005399:0.288868:0.1389:143658:rs28552953
1 852664 rs28605311 C T . PASS AF=0.1388 ES:SE:LP:AF:SS:ID 0.003525:0.005398:0.28929:0.1388:143658:rs28605311
1 852758 rs4970462 G C . PASS AF=0.1388 ES:SE:LP:AF:SS:ID 0.003526:0.005398:0.289375:0.1388:143658:rs4970462
1 853089 rs78738176 G C . PASS AF=0.0378 ES:SE:LP:AF:SS:ID 0.01866:0.009884:1.22834:0.0378:143658:rs78738176
1 853239 rs4970380 A G . PASS AF=0.1388 ES:SE:LP:AF:SS:ID 0.003531:0.005397:0.289883:0.1388:143658:rs4970380
1 853596 rs191666748 A G . PASS AF=0.0378 ES:SE:LP:AF:SS:ID 0.01862:0.009865:1.22834:0.0378:143658:rs191666748
1 854250 rs7537756 A G . PASS AF=0.1766 ES:SE:LP:AF:SS:ID 0.007422:0.004869:0.89449:0.1766:143658:rs7537756
1 854793 rs80174979 A C . PASS AF=0.0378 ES:SE:LP:AF:SS:ID 0.01861:0.009854:1.229:0.0378:143658:rs80174979
1 857177 rs28409649 T C . PASS AF=0.4594 ES:SE:LP:AF:SS:ID -0.00438:0.003884:0.585863:0.4594:143658:rs28409649
1 858040 rs4970460 C A . PASS AF=0.1732 ES:SE:LP:AF:SS:ID 0.00429:0.005786:0.338755:0.1732:143658:rs4970460
1 858051 rs4970459 C T . PASS AF=0.1732 ES:SE:LP:AF:SS:ID 0.004285:0.005787:0.338187:0.1732:143658:rs4970459
1 858801 rs7418179 A G . PASS AF=0.4063 ES:SE:LP:AF:SS:ID 0.002994:0.004053:0.337053:0.4063:143658:rs7418179
1 859404 rs71509444 C G . PASS AF=0.5782 ES:SE:LP:AF:SS:ID 0.007756:0.00412:1.22352:0.5782:143658:rs71509444
1 859690 rs71509445 C G . PASS AF=0.5313 ES:SE:LP:AF:SS:ID 0.004611:0.004059:0.59193:0.5313:143658:rs71509445
1 859701 rs71509446 C G . PASS AF=0.5038 ES:SE:LP:AF:SS:ID 0.00487:0.004204:0.607831:0.5038:143658:rs71509446
1 860416 rs61464428 G A . PASS AF=0.4175 ES:SE:LP:AF:SS:ID 0.003228:0.004072:0.368759:0.4175:143658:rs61464428
1 860461 rs57465118 G A . PASS AF=0.5388 ES:SE:LP:AF:SS:ID 0.00427:0.003846:0.573651:0.5388:143658:rs57465118
1 860521 rs57924093 C A . PASS AF=0.5353 ES:SE:LP:AF:SS:ID 0.004235:0.003813:0.573977:0.5353:143658:rs57924093
1 860688 rs60837925 G A . PASS AF=0.4283 ES:SE:LP:AF:SS:ID 0.002685:0.004132:0.287434:0.4283:143658:rs60837925
1 860778 rs61338526 A G . PASS AF=0.5071 ES:SE:LP:AF:SS:ID 0.004576:0.004013:0.594824:0.5071:143658:rs61338526
1 860857 rs141034733 G A . PASS AF=0.0457 ES:SE:LP:AF:SS:ID 0.01985:0.01011:1.30417:0.0457:143658:rs141034733
1 861008 rs28521172 G C . PASS AF=0.5404 ES:SE:LP:AF:SS:ID 0.004202:0.003768:0.577082:0.5404:143658:rs28521172
1 861630 rs2879816 G A . PASS AF=0.4066 ES:SE:LP:AF:SS:ID 0.002996:0.003968:0.346498:0.4066:143658:rs2879816
1 861808 rs13302982 A G . PASS AF=0.5404 ES:SE:LP:AF:SS:ID 0.004191:0.003763:0.576263:0.5404:143658:rs13302982
1 862072 rs76842830 C T . PASS AF=0.0374 ES:SE:LP:AF:SS:ID 0.01916:0.01016:1.22695:0.0374:143658:rs76842830
1 862093 rs13303291 T C . PASS AF=0.5403 ES:SE:LP:AF:SS:ID 0.004237:0.003809:0.575118:0.5403:143658:rs13303291
1 862124 rs13303101 A G . PASS AF=0.54 ES:SE:LP:AF:SS:ID 0.004346:0.003917:0.573164:0.54:143658:rs13303101
1 862383 rs6680268 C T . PASS AF=0.5397 ES:SE:LP:AF:SS:ID 0.00443:0.004002:0.571379:0.5397:143658:rs6680268
1 862389 rs6693546 A G . PASS AF=0.5397 ES:SE:LP:AF:SS:ID 0.004433:0.004004:0.571541:0.5397:143658:rs6693546
1 863124 rs4040604 G T . PASS AF=0.5421 ES:SE:LP:AF:SS:ID 0.0046:0.004199:0.563201:0.5421:143658:rs4040604
1 876499 rs4372192 A G . PASS AF=0.9472 ES:SE:LP:AF:SS:ID -0.0103:0.009716:0.538952:0.9472:143658:rs4372192
1 879676 rs6605067 G A . PASS AF=0.9453 ES:SE:LP:AF:SS:ID -0.01001:0.00956:0.530031:0.9453:143658:rs6605067
1 879687 rs2839 T C . PASS AF=0.9454 ES:SE:LP:AF:SS:ID -0.01:0.009556:0.530031:0.9454:143658:rs2839
1 880238 rs3748592 A G . PASS AF=0.9454 ES:SE:LP:AF:SS:ID -0.01:0.009551:0.530178:0.9454:143658:rs3748592