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/ukb-d-import/processed/ukb-d-30060_irnt/ukb-d-30060_irnt.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-30060_irnt/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 15:34:26 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30060_irnt/ukb-d-30060_irnt.vcf.gz ...
Read summary statistics for 13586284 SNPs.
Dropped 12710 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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0515 (0.0052)
Lambda GC: 1.2101
Mean Chi^2: 1.4042
Intercept: 1.0503 (0.0103)
Ratio: 0.1244 (0.0255)
Analysis finished at Mon Nov 25 15:37:14 2019
Total time elapsed: 2.0m:47.79sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9521,
"inflation_factor": 1.1457,
"mean_EFFECT": -0.0001,
"n": 350468,
"n_snps": 13586284,
"n_clumped_hits": 102,
"n_p_sig": 25653,
"n_mono": 0,
"n_ns": 1251793,
"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": 569194,
"n_est": 351801.6685,
"ratio_se_n": 1.0019,
"mean_diff": -5.3299e-07,
"ratio_diff": 1.6093,
"sd_y_est1": 0.9942,
"sd_y_est2": 0.9961,
"r2_sum1": 0.031,
"r2_sum2": 0.0314,
"r2_sum3": 0.0313,
"r2_sum4": 0.0312,
"ldsc_nsnp_merge_refpanel_ld": 1283504,
"ldsc_nsnp_merge_regression_ld": 1283504,
"ldsc_observed_scale_h2_beta": 0.0515,
"ldsc_observed_scale_h2_se": 0.0052,
"ldsc_intercept_beta": 1.0503,
"ldsc_intercept_se": 0.0103,
"ldsc_lambda_gc": 1.2101,
"ldsc_mean_chisq": 1.4042,
"ldsc_ratio": 0.1244
}
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 | 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 | 94 | 0 | 13574238 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 57080 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33337 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.051339e+00 | 6.184983e+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 | 7.902519e+07 | 5.591483e+07 | 3.02000e+02 | 3.293108e+07 | 7.013882e+07 | 1.148590e+08 | 2.492309e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -5.120000e-05 | 1.428870e-02 | -4.31476e-01 | -4.011000e-03 | 1.600000e-06 | 3.970800e-03 | 2.178070e-01 | ▁▁▁▇▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.978800e-03 | 9.625900e-03 | 1.95180e-03 | 2.841000e-03 | 5.235300e-03 | 1.434070e-02 | 4.880060e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.771581e-01 | 2.958540e-01 | 0.00000e+00 | 2.154870e-01 | 4.703173e-01 | 7.336890e-01 | 1.000000e+00 | ▇▇▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.771576e-01 | 2.958542e-01 | 0.00000e+00 | 2.154861e-01 | 4.703168e-01 | 7.336892e-01 | 9.999998e-01 | ▇▇▆▆▆ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.908060e-01 | 2.544034e-01 | 1.00000e-03 | 7.430500e-03 | 6.003400e-02 | 2.953170e-01 | 9.990000e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 569194 | 0.9581052 | NA | NA | NA | NA | NA | 1.963357e-01 | 2.471015e-01 | 0.00000e+00 | 5.591000e-03 | 8.426520e-02 | 3.081070e-01 | 1.000000e+00 | ▇▂▁▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.504680e+05 | 0.000000e+00 | 3.50468e+05 | 3.504680e+05 | 3.504680e+05 | 3.504680e+05 | 3.504680e+05 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 692794 | rs530212009 | CA | C | 0.0046497 | 0.0041572 | 0.2633662 | 0.2633653 | 0.1106780 | 0.1894970 | 350468 |
| 1 | 693731 | rs12238997 | A | G | 0.0032146 | 0.0039280 | 0.4131502 | 0.4131501 | 0.1158590 | 0.1417730 | 350468 |
| 1 | 707522 | rs371890604 | G | C | 0.0045566 | 0.0044174 | 0.3023020 | 0.3023018 | 0.0972848 | 0.1293930 | 350468 |
| 1 | 717587 | rs144155419 | G | A | 0.0002951 | 0.0105286 | 0.9776370 | 0.9776374 | 0.0157163 | 0.0045926 | 350468 |
| 1 | 723329 | rs189787166 | A | T | -0.0299040 | 0.0312008 | 0.3378431 | 0.3378425 | 0.0017252 | 0.0003994 | 350468 |
| 1 | 730087 | rs148120343 | T | C | 0.0045053 | 0.0054706 | 0.4101965 | 0.4101962 | 0.0564948 | 0.0127796 | 350468 |
| 1 | 731718 | rs142557973 | T | C | 0.0035344 | 0.0037252 | 0.3427433 | 0.3427411 | 0.1217820 | 0.1543530 | 350468 |
| 1 | 732032 | rs61770163 | A | C | 0.0015267 | 0.0039743 | 0.7008676 | 0.7008672 | 0.1211760 | 0.1555510 | 350468 |
| 1 | 734349 | rs141242758 | T | C | 0.0034666 | 0.0037272 | 0.3523344 | 0.3523327 | 0.1210110 | 0.1525560 | 350468 |
| 1 | 740284 | rs61770167 | C | T | -0.0172292 | 0.0170525 | 0.3123237 | 0.3123218 | 0.0057872 | 0.0023962 | 350468 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154923311 | rs141127553 | C | T | -0.0010327 | 0.0043029 | 0.8103389 | 0.8103380 | 0.0561527 | 0.0309934 | 350468 |
| 23 | 154923374 | rs111332691 | T | A | 0.0029982 | 0.0047301 | 0.5261784 | 0.5261774 | 0.0447915 | 0.0116556 | 350468 |
| 23 | 154925045 | rs509981 | C | T | -0.0005966 | 0.0022763 | 0.7932626 | 0.7932621 | 0.2454610 | 0.3634440 | 350468 |
| 23 | 154925895 | rs538470 | C | T | -0.0002690 | 0.0023283 | 0.9080361 | 0.9080362 | 0.2418080 | 0.3634440 | 350468 |
| 23 | 154927581 | rs644138 | G | A | -0.0007337 | 0.0021405 | 0.7317673 | 0.7317664 | 0.3020090 | 0.4635760 | 350468 |
| 23 | 154929412 | rs557132 | C | T | -0.0005339 | 0.0022769 | 0.8146039 | 0.8146031 | 0.2453150 | 0.3568210 | 350468 |
| 23 | 154929637 | rs35185538 | CT | C | -0.0008803 | 0.0023766 | 0.7110825 | 0.7110830 | 0.2295390 | 0.3011920 | 350468 |
| 23 | 154929952 | rs4012982 | CAA | C | -0.0006241 | 0.0023948 | 0.7943941 | 0.7943940 | 0.2392710 | 0.3165560 | 350468 |
| 23 | 154930230 | rs781880 | A | G | -0.0006447 | 0.0022766 | 0.7770340 | 0.7770336 | 0.2457260 | 0.3618540 | 350468 |
| 23 | 154930487 | rs781879 | T | A | -0.0023013 | 0.0078124 | 0.7683233 | 0.7683223 | 0.0195300 | 0.1263580 | 350468 |
bcf preview
1 692794 rs530212009 CA C . PASS AF=0.110678 ES:SE:LP:AF:SS:ID 0.00464968:0.00415717:0.57944:0.110678:350468:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.115859 ES:SE:LP:AF:SS:ID 0.00321457:0.00392805:0.383892:0.115859:350468:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0972848 ES:SE:LP:AF:SS:ID 0.00455655:0.00441736:0.519559:0.0972848:350468:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0157163 ES:SE:LP:AF:SS:ID 0.000295128:0.0105286:0.00982237:0.0157163:350468:rs144155419
1 723329 rs189787166 A T . PASS AF=0.00172521 ES:SE:LP:AF:SS:ID -0.029904:0.0312008:0.471285:0.00172521:350468:rs189787166
1 730087 rs148120343 T C . PASS AF=0.0564948 ES:SE:LP:AF:SS:ID 0.00450532:0.00547062:0.387008:0.0564948:350468:rs148120343
1 731718 rs58276399 T C . PASS AF=0.121782 ES:SE:LP:AF:SS:ID 0.00353437:0.00372524:0.465031:0.121782:350468:rs58276399
1 732032 rs61770163 A C . PASS AF=0.121176 ES:SE:LP:AF:SS:ID 0.00152672:0.00397428:0.154364:0.121176:350468:rs61770163
1 734349 rs141242758 T C . PASS AF=0.121011 ES:SE:LP:AF:SS:ID 0.0034666:0.00372723:0.453045:0.121011:350468:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00578721 ES:SE:LP:AF:SS:ID -0.0172292:0.0170525:0.505395:0.00578721:350468:rs61770167
1 742813 rs112573343 C T . PASS AF=0.00188412 ES:SE:LP:AF:SS:ID -0.0163704:0.0321842:0.21396:0.00188412:350468:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.869712 ES:SE:LP:AF:SS:ID -0.0012016:0.0036748:0.128613:0.869712:350468:rs529266287
1 750230 rs190826124 G C . PASS AF=0.00153229 ES:SE:LP:AF:SS:ID -0.0373549:0.0332437:0.583103:0.00153229:350468:rs190826124
1 751343 rs28544273 T A . PASS AF=0.122939 ES:SE:LP:AF:SS:ID 0.00208865:0.00363919:0.247174:0.122939:350468:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.142741 ES:SE:LP:AF:SS:ID 0.00153323:0.00359738:0.173953:0.142741:350468:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123056 ES:SE:LP:AF:SS:ID 0.00190034:0.0036341:0.221103:0.123056:350468:rs28527770
1 753405 rs3115860 C A . PASS AF=0.870848 ES:SE:LP:AF:SS:ID -0.0019261:0.00354129:0.231722:0.870848:350468:rs3115860
1 753425 rs3131970 T C . PASS AF=0.875447 ES:SE:LP:AF:SS:ID -0.000951507:0.00360002:0.101525:0.875447:350468:rs3131970
1 753541 rs2073813 G A . PASS AF=0.128673 ES:SE:LP:AF:SS:ID 0.0022359:0.00355017:0.276688:0.128673:350468:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0363371 ES:SE:LP:AF:SS:ID 0.00969956:0.00644568:0.878204:0.0363371:350468:rs12184325
1 754182 rs3131969 A G . PASS AF=0.870442 ES:SE:LP:AF:SS:ID -0.00212581:0.00353757:0.261307:0.870442:350468:rs3131969
1 754192 rs3131968 A G . PASS AF=0.870543 ES:SE:LP:AF:SS:ID -0.00212064:0.00353913:0.260396:0.870543:350468:rs3131968
1 754334 rs3131967 T C . PASS AF=0.870437 ES:SE:LP:AF:SS:ID -0.00210427:0.00353743:0.258109:0.870437:350468:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00504303 ES:SE:LP:AF:SS:ID -0.0229095:0.0181723:0.683141:0.00504303:350468:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00500992 ES:SE:LP:AF:SS:ID -0.0237902:0.0182207:0.717453:0.00500992:350468:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00558066 ES:SE:LP:AF:SS:ID -0.0286148:0.017601:0.982946:0.00558066:350468:rs184270342
1 755890 rs3115858 A T . PASS AF=0.870521 ES:SE:LP:AF:SS:ID -0.00192923:0.00353123:0.232964:0.870521:350468:rs3115858
1 756434 rs61768170 G C . PASS AF=0.126016 ES:SE:LP:AF:SS:ID 0.00195275:0.00360343:0.230712:0.126016:350468:rs61768170
1 756604 rs3131962 A G . PASS AF=0.870084 ES:SE:LP:AF:SS:ID -0.00234178:0.00352271:0.295677:0.870084:350468:rs3131962
1 757640 rs3115853 G A . PASS AF=0.869362 ES:SE:LP:AF:SS:ID -0.00244903:0.00351937:0.312908:0.869362:350468:rs3115853
1 757734 rs4951929 C T . PASS AF=0.870238 ES:SE:LP:AF:SS:ID -0.00223515:0.00352576:0.278919:0.870238:350468:rs4951929
1 757936 rs4951862 C A . PASS AF=0.870244 ES:SE:LP:AF:SS:ID -0.00223379:0.00352601:0.278687:0.870244:350468:rs4951862
1 758144 rs3131956 A G . PASS AF=0.870252 ES:SE:LP:AF:SS:ID -0.00221998:0.00352612:0.276569:0.870252:350468:rs3131956
1 758626 rs3131954 C T . PASS AF=0.870695 ES:SE:LP:AF:SS:ID -0.00194043:0.0035351:0.234279:0.870695:350468:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0988399 ES:SE:LP:AF:SS:ID 0.00297433:0.00410902:0.328683:0.0988399:350468:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00647163 ES:SE:LP:AF:SS:ID -0.0193098:0.0159015:0.648552:0.00647163:350468:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.874603 ES:SE:LP:AF:SS:ID -0.0012683:0.00358787:0.140431:0.874603:350468:rs3115851
1 761732 rs2286139 C T . PASS AF=0.863992 ES:SE:LP:AF:SS:ID -0.00274554:0.00351842:0.361315:0.863992:350468:rs2286139
1 761752 rs1057213 C T . PASS AF=0.869375 ES:SE:LP:AF:SS:ID -0.0015401:0.00355256:0.177415:0.869375:350468:rs1057213
1 762273 rs3115849 G A . PASS AF=0.866334 ES:SE:LP:AF:SS:ID -0.00181968:0.00355338:0.21568:0.866334:350468:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0987509 ES:SE:LP:AF:SS:ID 0.00251272:0.00425531:0.255815:0.0987509:350468:rs12095200
1 762589 rs3115848 G C . PASS AF=0.871518 ES:SE:LP:AF:SS:ID -0.00147422:0.0035938:0.166438:0.871518:350468:rs3115848
1 762592 rs3131950 C G . PASS AF=0.871517 ES:SE:LP:AF:SS:ID -0.00147402:0.0035938:0.166412:0.871517:350468:rs3131950
1 762601 rs3131949 T C . PASS AF=0.871517 ES:SE:LP:AF:SS:ID -0.00148122:0.00359387:0.167345:0.871517:350468:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871888 ES:SE:LP:AF:SS:ID -0.00127195:0.00359591:0.140533:0.871888:350468:rs3131948
1 764191 rs7515915 T G . PASS AF=0.125597 ES:SE:LP:AF:SS:ID 0.00195337:0.00359876:0.231159:0.125597:350468:rs7515915
1 766007 rs61768174 A C . PASS AF=0.105426 ES:SE:LP:AF:SS:ID 0.00426001:0.00391838:0.557591:0.105426:350468:rs61768174
1 766105 rs2519015 T A . PASS AF=0.855333 ES:SE:LP:AF:SS:ID -0.00159378:0.0035175:0.186768:0.855333:350468:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00164754 ES:SE:LP:AF:SS:ID -0.0274059:0.0312548:0.419568:0.00164754:350468:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.838287 ES:SE:LP:AF:SS:ID 0.00159472:0.00346483:0.190217:0.838287:350468:rs376645387