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/folkersen-pqtl-gwas-import/processed/PROT-b-6/PROT-b-6.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/folkersen-pqtl-gwas-import/processed/PROT-b-6/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Mon Oct 28 22:10:21 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/folkersen-pqtl-gwas-import/processed/PROT-b-6/PROT-b-6.vcf.gz ...
Read summary statistics for 5135036 SNPs.
Dropped 1 SNPs with duplicated rs numbers.
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, 759193 SNPs remain.
After merging with regression SNP LD, 759193 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2535 (0.2264)
Lambda GC: 1.0032
Mean Chi^2: 1.0145
Intercept: 0.9947 (0.0087)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Oct 28 22:11:12 2019
Total time elapsed: 50.81sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9563,
"inflation_factor": 1.0103,
"mean_EFFECT": 0.0101,
"n": "-Inf",
"n_snps": 5135036,
"n_clumped_hits": 5,
"n_p_sig": 1059,
"n_mono": 545,
"n_ns": 317497,
"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": 377170,
"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": 759193,
"ldsc_nsnp_merge_regression_ld": 759193,
"ldsc_observed_scale_h2_beta": 0.2535,
"ldsc_observed_scale_h2_se": 0.2264,
"ldsc_intercept_beta": 0.9947,
"ldsc_intercept_se": 0.0087,
"ldsc_lambda_gc": 1.0032,
"ldsc_mean_chisq": 1.0145,
"ldsc_ratio": -0.3655
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | TRUE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | FALSE |
| 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 | 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 | 58 | 0 | 5135032 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 3 | 0 | 80 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 3 | 0 | 80 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 5135036 | 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 | 8.356760e+00 | 5.629048e+00 | 1.0000 | 3.000000e+00 | 7.000000e+00 | 1.200000e+01 | 2.200000e+01 | ▇▅▃▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.977423e+07 | 5.495317e+07 | 29422.0000 | 3.532730e+07 | 7.050636e+07 | 1.143548e+08 | 2.492183e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.012730e-02 | 2.822365e-01 | -13.5856 | -3.520000e-02 | 1.200000e-03 | 3.870000e-02 | 9.815700e+00 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.340463e-01 | 2.420272e-01 | 0.0233 | 3.380000e-02 | 4.740000e-02 | 1.089000e-01 | 3.351800e+00 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.985568e-01 | 2.885636e-01 | 0.0000 | 2.491002e-01 | 4.978001e-01 | 7.485003e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.983954e-01 | 2.886590e-01 | 0.0000 | 2.487865e-01 | 4.976063e-01 | 7.484755e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.781589e-01 | 2.817943e-01 | 0.0000 | 3.560000e-02 | 1.762000e-01 | 4.617000e-01 | 1.000000e+00 | ▇▃▂▂▁ |
| numeric | AF_reference | 377170 | 0.9265497 | NA | NA | NA | NA | NA | NA | NA | 2.522964e-01 | 2.538675e-01 | 0.0000 | 3.654150e-02 | 1.659350e-01 | 4.039540e-01 | 1.000000e+00 | ▇▃▂▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 780785 | rs2977612 | T | A | -0.0663 | 0.0464 | 0.1534999 | 0.1530389 | 0.8252 | 0.669329 | NA |
| 1 | 782981 | rs6594026 | C | T | 0.0653 | 0.0458 | 0.1534999 | 0.1539364 | 0.1534 | 0.297923 | NA |
| 1 | 783318 | rs6686696 | A | G | 0.1024 | 0.0718 | 0.1535999 | 0.1538153 | 0.0799 | 0.183107 | NA |
| 1 | 785050 | rs2905062 | G | A | -0.0485 | 0.0340 | 0.1534999 | 0.1537326 | 0.8365 | 0.626997 | NA |
| 1 | 785989 | rs2980300 | T | C | -0.0538 | 0.0377 | 0.1534999 | 0.1535638 | 0.8083 | 0.626997 | NA |
| 1 | 787121 | rs12077234 | T | A | 0.0851 | 0.0596 | 0.1534999 | 0.1533344 | 0.1319 | NA | NA |
| 1 | 787399 | rs2905055 | G | T | -0.0659 | 0.0461 | 0.1533999 | 0.1528603 | 0.8001 | 0.646366 | NA |
| 1 | 787685 | rs2905054 | G | T | -0.0630 | 0.0442 | 0.1534999 | 0.1540591 | 0.7668 | 0.622204 | NA |
| 1 | 787844 | rs2905053 | C | T | -0.0685 | 0.0480 | 0.1534999 | 0.1535559 | 0.8114 | 0.651757 | NA |
| 1 | 790758 | 1_790758_GTA_G | G | GTA | -0.0728 | 0.0510 | 0.1534999 | 0.1534499 | 0.7799 | NA | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51163039 | rs715584 | G | T | -0.0052 | 0.0301 | 0.8632999 | 0.8628421 | 0.4131 | 0.4736420 | NA |
| 22 | 51163138 | rs715586 | C | T | 0.0427 | 0.0361 | 0.2378001 | 0.2368783 | 0.1273 | 0.0902556 | NA |
| 22 | 51163910 | rs192700691 | C | T | -0.0578 | 0.1074 | 0.5903003 | 0.5904562 | 0.0304 | 0.0295527 | NA |
| 22 | 51164109 | rs5770995 | G | C | -0.0116 | 0.0283 | 0.6813998 | 0.6818837 | 0.4411 | 0.5109820 | NA |
| 22 | 51164115 | rs5770996 | C | T | -0.0114 | 0.0285 | 0.6892996 | 0.6891565 | 0.4446 | 0.5147760 | NA |
| 22 | 51164287 | rs6009957 | T | C | -0.0307 | 0.0273 | 0.2619003 | 0.2607831 | 0.3052 | 0.4155350 | NA |
| 22 | 51165664 | rs8137951 | G | A | -0.0286 | 0.0266 | 0.2819000 | 0.2822906 | 0.2954 | 0.4063500 | NA |
| 22 | 51171693 | rs756638 | G | A | 0.0217 | 0.0387 | 0.5756003 | 0.5749860 | 0.3046 | 0.3049120 | NA |
| 22 | 51175626 | rs3810648 | A | G | -0.0170 | 0.0604 | 0.7788001 | 0.7783599 | 0.0735 | 0.1084270 | NA |
| 22 | 51178090 | rs2285395 | G | A | -0.0007 | 0.0573 | 0.9900000 | 0.9902530 | 0.0481 | 0.0666933 | NA |
bcf preview
1 780785 rs2977612 T A . PASS AF=0.8252 ES:SE:LP:AF:ID -0.0663:0.0464:0.813892:0.8252:rs2977612
1 782981 rs6594026 C T . PASS AF=0.1534 ES:SE:LP:AF:ID 0.0653:0.0458:0.813892:0.1534:rs6594026
1 783318 rs6686696 A G . PASS AF=0.0799 ES:SE:LP:AF:ID 0.1024:0.0718:0.813609:0.0799:rs6686696
1 785050 rs2905062 G A . PASS AF=0.8365 ES:SE:LP:AF:ID -0.0485:0.034:0.813892:0.8365:rs2905062
1 785989 rs2980300 T C . PASS AF=0.8083 ES:SE:LP:AF:ID -0.0538:0.0377:0.813892:0.8083:rs2980300
1 787121 rs12077234 T A . PASS AF=0.1319 ES:SE:LP:AF:ID 0.0851:0.0596:0.813892:0.1319:rs12077234
1 787399 rs2905055 G T . PASS AF=0.8001 ES:SE:LP:AF:ID -0.0659:0.0461:0.814175:0.8001:rs2905055
1 787685 rs2905054 G T . PASS AF=0.7668 ES:SE:LP:AF:ID -0.063:0.0442:0.813892:0.7668:rs2905054
1 787844 rs2905053 C T . PASS AF=0.8114 ES:SE:LP:AF:ID -0.0685:0.048:0.813892:0.8114:rs2905053
1 790758 1_790758_GTA_G G GTA . PASS AF=0.7799 ES:SE:LP:AF:ID -0.0728:0.051:0.813892:0.7799:1_790758_GTA_G
1 1108637 rs4970421 G A . PASS AF=0.0713 ES:SE:LP:AF:ID 0.0355:0.0758:0.194092:0.0713:rs4970421
1 1112982 rs6671609 C T . PASS AF=0.1436 ES:SE:LP:AF:ID 0.0033:0.0601:0.0192696:0.1436:rs6671609
1 1115994 rs13376597 G A . PASS AF=0.1429 ES:SE:LP:AF:ID -0.0026:0.0581:0.0157878:0.1429:rs13376597
1 1116231 rs13374146 T C . PASS AF=0.0678 ES:SE:LP:AF:ID 0.0173:0.0613:0.10902:0.0678:rs13374146
1 1117398 rs12097586 A G . PASS AF=0.4246 ES:SE:LP:AF:ID -0.0244:0.0438:0.238222:0.4246:rs12097586
1 1117486 rs13376670 A G . PASS AF=0.1481 ES:SE:LP:AF:ID -0.0017:0.0571:0.0106837:0.1481:rs13376670
1 1118275 rs61733845 C T . PASS AF=0.05 ES:SE:LP:AF:ID 0.0273:0.0576:0.196338:0.05:rs61733845
1 1118578 rs111290899 G A . PASS AF=0.0504 ES:SE:LP:AF:ID 0.0264:0.0589:0.184688:0.0504:rs111290899
1 1119657 rs4560982 G C . PASS AF=0.4012 ES:SE:LP:AF:ID -0.0288:0.0392:0.335264:0.4012:rs4560982
1 1119858 rs1320565 C T . PASS AF=0.1126 ES:SE:LP:AF:ID 0.0352:0.0604:0.251734:0.1126:rs1320565
1 1120431 rs1320571 G A . PASS AF=0.0525 ES:SE:LP:AF:ID 0.025:0.0551:0.186886:0.0525:rs1320571
1 1121014 rs3813204 G A . PASS AF=0.1364 ES:SE:LP:AF:ID -0.075:0.0571:0.723308:0.1364:rs3813204
1 1121341 rs4297230 C T . PASS AF=0.1422 ES:SE:LP:AF:ID -0.0726:0.0557:0.715569:0.1422:rs4297230
1 1121358 rs80057011 A C . PASS AF=0.0928 ES:SE:LP:AF:ID -0.0463:0.0656:0.318036:0.0928:rs80057011
1 1121480 rs12063663 T C . PASS AF=0.0923 ES:SE:LP:AF:ID -0.0469:0.0654:0.324588:0.0923:rs12063663
1 1121625 rs4081334 C G . PASS AF=0.1418 ES:SE:LP:AF:ID -0.0719:0.0552:0.714893:0.1418:rs4081334
1 1121657 rs11260548 T C . PASS AF=0.2302 ES:SE:LP:AF:ID -0.0473:0.0371:0.693361:0.2302:rs11260548
1 1121715 rs4081333 C T . PASS AF=0.0882 ES:SE:LP:AF:ID -0.052:0.0644:0.377682:0.0882:rs4081333
1 1121794 rs11260549 G A . PASS AF=0.1326 ES:SE:LP:AF:ID -0.0706:0.055:0.700275:0.1326:rs11260549
1 1121835 rs57346441 C CTG . PASS AF=0.2304 ES:SE:LP:AF:ID -0.0471:0.0363:0.709298:0.2304:1_1121835_C_CTG
1 1122024 rs4314833 T C . PASS AF=0.1279 ES:SE:LP:AF:ID -0.0736:0.0561:0.72262:0.1279:rs4314833
1 1122196 rs4634847 A G . PASS AF=0.1342 ES:SE:LP:AF:ID -0.0725:0.0547:0.731188:0.1342:rs4634847
1 1122283 rs12064046 T G . PASS AF=0.0862 ES:SE:LP:AF:ID -0.0525:0.0639:0.386158:0.0862:rs12064046
1 1122319 rs7415847 C T . PASS AF=0.1199 ES:SE:LP:AF:ID -0.0752:0.0599:0.679023:0.1199:rs7415847
1 1122468 rs7545694 T C . PASS AF=0.2031 ES:SE:LP:AF:ID -0.0534:0.04:0.740884:0.2031:rs7545694
1 1122516 rs11260551 G A . PASS AF=0.1274 ES:SE:LP:AF:ID -0.0726:0.0559:0.712422:0.1274:rs11260551
1 1122539 rs12063897 A G . PASS AF=0.0866 ES:SE:LP:AF:ID -0.0512:0.0631:0.379552:0.0866:rs12063897
1 1122915 rs28595293 A G . PASS AF=0.2718 ES:SE:LP:AF:ID -0.0267:0.032:0.394479:0.2718:rs28595293
1 1122916 rs28460227 A G . PASS AF=0.0856 ES:SE:LP:AF:ID -0.0506:0.0632:0.373147:0.0856:rs28460227
1 1122937 rs28648687 G A . PASS AF=0.0856 ES:SE:LP:AF:ID -0.0505:0.0632:0.372429:0.0856:rs28648687
1 1123106 rs12401472 G A . PASS AF=0.128 ES:SE:LP:AF:ID -0.072:0.0555:0.711974:0.128:rs12401472
1 1123434 rs12066716 T A . PASS AF=0.1323 ES:SE:LP:AF:ID -0.0099:0.0537:0.0688983:0.1323:rs12066716
1 1124257 rs10907172 A G . PASS AF=0.1273 ES:SE:LP:AF:ID -0.0717:0.0552:0.711974:0.1273:rs10907172
1 1124399 rs10907173 C G . PASS AF=0.1324 ES:SE:LP:AF:ID -0.0703:0.054:0.713768:0.1324:rs10907173
1 1124663 rs6684820 G A . PASS AF=0.2737 ES:SE:LP:AF:ID -0.0263:0.0313:0.397289:0.2737:rs6684820
1 1124819 rs6694487 C T . PASS AF=0.0867 ES:SE:LP:AF:ID -0.0519:0.0625:0.390833:0.0867:rs6694487
1 1124891 rs61768485 G A . PASS AF=0.1266 ES:SE:LP:AF:ID -0.0714:0.055:0.71108:0.1266:rs61768485
1 1125110 rs12124436 T C . PASS AF=0.1248 ES:SE:LP:AF:ID -0.0721:0.0548:0.726073:0.1248:rs12124436
1 1125220 rs12065129 C T . PASS AF=0.0864 ES:SE:LP:AF:ID -0.0519:0.062:0.395126:0.0864:rs12065129
1 1125348 rs12029885 T C . PASS AF=0.1261 ES:SE:LP:AF:ID -0.0717:0.0552:0.711974:0.1261:rs12029885