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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"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-D12/ukb-d-D12_data.json --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/b37/human_g1k_v37.fasta; 1.1.1",
"file_date": "2019-11-25T17:03:51.886314",
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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/ukb-d-import/processed/ukb-d-D12/ukb-d-D12.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/ukb-d-import/processed/ukb-d-D12/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Mon Nov 25 17:47:16 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-D12/ukb-d-D12.vcf.gz ...
Read summary statistics for 13217520 SNPs.
Dropped 12192 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, 1283439 SNPs remain.
After merging with regression SNP LD, 1283439 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0129 (0.0015)
Lambda GC: 1.0806
Mean Chi^2: 1.0958
Intercept: 1.0058 (0.0057)
Ratio: 0.0603 (0.0595)
Analysis finished at Mon Nov 25 17:49:31 2019
Total time elapsed: 2.0m:15.1sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9515,
"inflation_factor": 1.0571,
"mean_EFFECT": -3.1266e-07,
"n": 361194,
"n_snps": 13217520,
"n_clumped_hits": 14,
"n_p_sig": 521,
"n_mono": 0,
"n_ns": 1238289,
"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": 477979,
"n_est": 362478.1624,
"ratio_se_n": 1.0018,
"mean_diff": -1.9188e-06,
"ratio_diff": 6.3793,
"sd_y_est1": 0.1617,
"sd_y_est2": 0.1619,
"r2_sum1": 0.0001,
"r2_sum2": 0.0019,
"r2_sum3": 0.0019,
"r2_sum4": 0.0019,
"ldsc_nsnp_merge_refpanel_ld": 1283439,
"ldsc_nsnp_merge_regression_ld": 1283439,
"ldsc_observed_scale_h2_beta": 0.0129,
"ldsc_observed_scale_h2_se": 0.0015,
"ldsc_intercept_beta": 1.0058,
"ldsc_intercept_se": 0.0057,
"ldsc_lambda_gc": 1.0806,
"ldsc_mean_chisq": 1.0958,
"ldsc_ratio": 0.0605
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | FALSE |
| is_snpid_non_unique | TRUE |
| 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 | 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 | 94 | 0 | 13205986 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 56339 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33118 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.056096e+00 | 6.185556e+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 | 7.899155e+07 | 5.592601e+07 | 3.02000e+02 | 3.287560e+07 | 7.008043e+07 | 1.148185e+08 | 2.492309e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -3.000000e-07 | 2.035200e-03 | -2.12823e-02 | -5.904000e-04 | -5.400000e-06 | 5.773000e-04 | 3.302890e-02 | ▁▇▃▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.478800e-03 | 1.382900e-03 | 3.12800e-04 | 4.508000e-04 | 8.004000e-04 | 2.109100e-03 | 7.672600e-03 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.909887e-01 | 2.907658e-01 | 0.00000e+00 | 2.370828e-01 | 4.880159e-01 | 7.424667e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.909883e-01 | 2.907661e-01 | 0.00000e+00 | 2.370827e-01 | 4.880150e-01 | 7.424674e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.958273e-01 | 2.555997e-01 | 1.28610e-03 | 8.783200e-03 | 6.642390e-02 | 3.053420e-01 | 9.987140e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 477979 | 0.9638375 | NA | NA | NA | NA | NA | 2.001349e-01 | 2.479322e-01 | 0.00000e+00 | 6.589500e-03 | 8.945690e-02 | 3.152960e-01 | 1.000000e+00 | ▇▂▁▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.611940e+05 | 0.000000e+00 | 3.61194e+05 | 3.611940e+05 | 3.611940e+05 | 3.611940e+05 | 3.611940e+05 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 692794 | rs530212009 | CA | C | 0.0010321 | 0.0006663 | 0.1213769 | 0.1213747 | 0.1106400 | 0.1894970 | 361194 |
| 1 | 693731 | rs12238997 | A | G | 0.0007847 | 0.0006295 | 0.2125690 | 0.2125677 | 0.1158300 | 0.1417730 | 361194 |
| 1 | 707522 | rs371890604 | G | C | 0.0016804 | 0.0007077 | 0.0175821 | 0.0175815 | 0.0973034 | 0.1293930 | 361194 |
| 1 | 717587 | rs144155419 | G | A | 0.0001558 | 0.0016888 | 0.9264750 | 0.9264742 | 0.0156880 | 0.0045926 | 361194 |
| 1 | 723329 | rs189787166 | A | T | -0.0072516 | 0.0049827 | 0.1455731 | 0.1455719 | 0.0017336 | 0.0003994 | 361194 |
| 1 | 730087 | rs148120343 | T | C | 0.0018877 | 0.0008770 | 0.0313697 | 0.0313691 | 0.0564602 | 0.0127796 | 361194 |
| 1 | 731718 | rs142557973 | T | C | 0.0006103 | 0.0005971 | 0.3067157 | 0.3067154 | 0.1217380 | 0.1543530 | 361194 |
| 1 | 732032 | rs61770163 | A | C | 0.0010516 | 0.0006369 | 0.0986961 | 0.0986928 | 0.1211710 | 0.1555510 | 361194 |
| 1 | 734349 | rs141242758 | T | C | 0.0006204 | 0.0005974 | 0.2990233 | 0.2990227 | 0.1209650 | 0.1525560 | 361194 |
| 1 | 740284 | rs61770167 | C | T | 0.0009225 | 0.0027330 | 0.7357106 | 0.7357116 | 0.0057851 | 0.0023962 | 361194 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154923311 | rs141127553 | C | T | -0.0005690 | 0.0006898 | 0.4094265 | 0.4094260 | 0.0561667 | 0.0309934 | 361194 |
| 23 | 154923374 | rs111332691 | T | A | -0.0002565 | 0.0007581 | 0.7351027 | 0.7351024 | 0.0447862 | 0.0116556 | 361194 |
| 23 | 154925045 | rs509981 | C | T | -0.0000752 | 0.0003647 | 0.8367320 | 0.8367322 | 0.2456060 | 0.3634440 | 361194 |
| 23 | 154925895 | rs538470 | C | T | 0.0000596 | 0.0003731 | 0.8730920 | 0.8730917 | 0.2419150 | 0.3634440 | 361194 |
| 23 | 154927581 | rs644138 | G | A | -0.0001932 | 0.0003430 | 0.5731786 | 0.5731780 | 0.3021620 | 0.4635760 | 361194 |
| 23 | 154929412 | rs557132 | C | T | -0.0000769 | 0.0003649 | 0.8330081 | 0.8330079 | 0.2454590 | 0.3568210 | 361194 |
| 23 | 154929637 | rs35185538 | CT | C | -0.0000267 | 0.0003808 | 0.9440789 | 0.9440793 | 0.2296970 | 0.3011920 | 361194 |
| 23 | 154929952 | rs4012982 | CAA | C | -0.0001087 | 0.0003837 | 0.7770179 | 0.7770173 | 0.2394250 | 0.3165560 | 361194 |
| 23 | 154930230 | rs781880 | A | G | -0.0000224 | 0.0003648 | 0.9510311 | 0.9510307 | 0.2458690 | 0.3618540 | 361194 |
| 23 | 154930487 | rs781879 | T | A | -0.0009510 | 0.0012514 | 0.4472816 | 0.4472815 | 0.0195623 | 0.1263580 | 361194 |
bcf preview
1 692794 rs530212009 CA C . PASS AF=0.11064 ES:SE:LP:AF:SS:ID 0.00103207:0.000666269:0.915864:0.11064:361194:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.11583 ES:SE:LP:AF:SS:ID 0.000784748:0.000629543:0.6725:0.11583:361194:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0973034 ES:SE:LP:AF:SS:ID 0.00168038:0.000707732:1.75493:0.0973034:361194:rs371890604
1 717587 rs144155419 G A . PASS AF=0.015688 ES:SE:LP:AF:SS:ID 0.000155849:0.00168884:0.0331663:0.015688:361194:rs144155419
1 723329 rs189787166 A T . PASS AF=0.00173363 ES:SE:LP:AF:SS:ID -0.00725161:0.00498272:0.836919:0.00173363:361194:rs189787166
1 730087 rs148120343 T C . PASS AF=0.0564602 ES:SE:LP:AF:SS:ID 0.00188769:0.000877033:1.50349:0.0564602:361194:rs148120343
1 731718 rs58276399 T C . PASS AF=0.121738 ES:SE:LP:AF:SS:ID 0.000610278:0.00059706:0.513264:0.121738:361194:rs58276399
1 732032 rs61770163 A C . PASS AF=0.121171 ES:SE:LP:AF:SS:ID 0.00105163:0.000636879:1.0057:0.121171:361194:rs61770163
1 734349 rs141242758 T C . PASS AF=0.120965 ES:SE:LP:AF:SS:ID 0.0006204:0.000597382:0.524295:0.120965:361194:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00578512 ES:SE:LP:AF:SS:ID 0.000922504:0.00273304:0.133293:0.00578512:361194:rs61770167
1 742813 rs112573343 C T . PASS AF=0.00187787 ES:SE:LP:AF:SS:ID -0.000775653:0.00516161:0.0552465:0.00187787:361194:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.869742 ES:SE:LP:AF:SS:ID -0.000927788:0.000588923:0.93868:0.869742:361194:rs529266287
1 750230 rs190826124 G C . PASS AF=0.00153021 ES:SE:LP:AF:SS:ID 0.00407541:0.00533151:0.352002:0.00153021:361194:rs190826124
1 751343 rs28544273 T A . PASS AF=0.122916 ES:SE:LP:AF:SS:ID 0.000912244:0.00058325:0.928847:0.122916:361194:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.142712 ES:SE:LP:AF:SS:ID 0.000748079:0.000576512:0.711243:0.142712:361194:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123031 ES:SE:LP:AF:SS:ID 0.0009204:0.000582438:0.942905:0.123031:361194:rs28527770
1 753405 rs3115860 C A . PASS AF=0.87089 ES:SE:LP:AF:SS:ID -0.00084097:0.000567567:0.858807:0.87089:361194:rs3115860
1 753425 rs3131970 T C . PASS AF=0.875472 ES:SE:LP:AF:SS:ID -0.000998952:0.000576972:1.0789:0.875472:361194:rs3131970
1 753541 rs2073813 G A . PASS AF=0.128631 ES:SE:LP:AF:SS:ID 0.000805349:0.000568991:0.804233:0.128631:361194:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0363613 ES:SE:LP:AF:SS:ID -0.000770994:0.00103228:0.34186:0.0363613:361194:rs12184325
1 754182 rs3131969 A G . PASS AF=0.870484 ES:SE:LP:AF:SS:ID -0.000804951:0.000566977:0.807742:0.870484:361194:rs3131969
1 754192 rs3131968 A G . PASS AF=0.870589 ES:SE:LP:AF:SS:ID -0.000793972:0.000567236:0.791564:0.870589:361194:rs3131968
1 754334 rs3131967 T C . PASS AF=0.870481 ES:SE:LP:AF:SS:ID -0.000818956:0.000566956:0.827967:0.870481:361194:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00504367 ES:SE:LP:AF:SS:ID 0.00620479:0.00291065:1.48112:0.00504367:361194:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00501064 ES:SE:LP:AF:SS:ID 0.00622804:0.00291844:1.48359:0.00501064:361194:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00558665 ES:SE:LP:AF:SS:ID -0.00301305:0.00281904:0.544925:0.00558665:361194:rs184270342
1 755890 rs3115858 A T . PASS AF=0.870563 ES:SE:LP:AF:SS:ID -0.000856037:0.000565958:0.884732:0.870563:361194:rs3115858
1 756434 rs61768170 G C . PASS AF=0.125985 ES:SE:LP:AF:SS:ID 0.000890981:0.000577485:0.910572:0.125985:361194:rs61768170
1 756604 rs3131962 A G . PASS AF=0.870127 ES:SE:LP:AF:SS:ID -0.00086303:0.000564596:0.898356:0.870127:361194:rs3131962
1 757640 rs3115853 G A . PASS AF=0.869414 ES:SE:LP:AF:SS:ID -0.000798807:0.000564082:0.804817:0.869414:361194:rs3115853
1 757734 rs4951929 C T . PASS AF=0.870281 ES:SE:LP:AF:SS:ID -0.000871167:0.000565082:0.909544:0.870281:361194:rs4951929
1 757936 rs4951862 C A . PASS AF=0.870287 ES:SE:LP:AF:SS:ID -0.000870848:0.000565122:0.908966:0.870287:361194:rs4951862
1 758144 rs3131956 A G . PASS AF=0.870295 ES:SE:LP:AF:SS:ID -0.000866458:0.00056514:0.902278:0.870295:361194:rs3131956
1 758626 rs3131954 C T . PASS AF=0.870739 ES:SE:LP:AF:SS:ID -0.000860268:0.000566579:0.889659:0.870739:361194:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0988442 ES:SE:LP:AF:SS:ID 0.000816509:0.0006584:0.667715:0.0988442:361194:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00647588 ES:SE:LP:AF:SS:ID -0.00252949:0.00254673:0.494039:0.00647588:361194:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.874635 ES:SE:LP:AF:SS:ID -0.000933842:0.000575023:0.981404:0.874635:361194:rs3115851
1 761732 rs2286139 C T . PASS AF=0.864027 ES:SE:LP:AF:SS:ID -0.000785114:0.000563896:0.785604:0.864027:361194:rs2286139
1 761752 rs1057213 C T . PASS AF=0.869425 ES:SE:LP:AF:SS:ID -0.000880612:0.00056937:0.913818:0.869425:361194:rs1057213
1 762273 rs3115849 G A . PASS AF=0.866371 ES:SE:LP:AF:SS:ID -0.00100425:0.000569485:1.10886:0.866371:361194:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0987831 ES:SE:LP:AF:SS:ID 0.000244339:0.000681783:0.142633:0.0987831:361194:rs12095200
1 762589 rs3115848 G C . PASS AF=0.871556 ES:SE:LP:AF:SS:ID -0.000921678:0.000575973:0.960376:0.871556:361194:rs3115848
1 762592 rs3131950 C G . PASS AF=0.871556 ES:SE:LP:AF:SS:ID -0.000921666:0.000575973:0.960356:0.871556:361194:rs3131950
1 762601 rs3131949 T C . PASS AF=0.871555 ES:SE:LP:AF:SS:ID -0.000922215:0.000575984:0.961169:0.871555:361194:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871929 ES:SE:LP:AF:SS:ID -0.000878823:0.000576313:0.89523:0.871929:361194:rs3131948
1 764191 rs7515915 T G . PASS AF=0.125562 ES:SE:LP:AF:SS:ID 0.000886313:0.000576768:0.905284:0.125562:361194:rs7515915
1 766007 rs61768174 A C . PASS AF=0.105428 ES:SE:LP:AF:SS:ID 0.000633253:0.000627891:0.504182:0.105428:361194:rs61768174
1 766105 rs2519015 T A . PASS AF=0.855376 ES:SE:LP:AF:SS:ID -0.000773757:0.000563684:0.769927:0.855376:361194:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00165444 ES:SE:LP:AF:SS:ID -0.00659808:0.00499343:0.729589:0.00165444:361194:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.838358 ES:SE:LP:AF:SS:ID 0.00104237:0.000555329:1.21814:0.838358:361194:rs376645387