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}
*********************************************************************
* 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-22630_9/ukb-d-22630_9.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-22630_9/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 16:39:30 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22630_9/ukb-d-22630_9.vcf.gz ...
Read summary statistics for 13531002 SNPs.
Dropped 12637 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, 1283494 SNPs remain.
After merging with regression SNP LD, 1283494 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0276 (0.0156)
Lambda GC: 1.0031
Mean Chi^2: 1.0047
Intercept: 0.9909 (0.0053)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:42:16 2019
Total time elapsed: 2.0m:45.76s
{
"af_correlation": 0.952,
"inflation_factor": 1.0059,
"mean_EFFECT": 0.0001,
"n": 25697,
"n_snps": 13531002,
"n_clumped_hits": 0,
"n_p_sig": 0,
"n_mono": 0,
"n_ns": 1249835,
"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": 555297,
"n_est": 25876.1221,
"ratio_se_n": 1.0035,
"mean_diff": 0.0001,
"ratio_diff": 11.8966,
"sd_y_est1": 0.392,
"sd_y_est2": 0.3934,
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1283494,
"ldsc_nsnp_merge_regression_ld": 1283494,
"ldsc_observed_scale_h2_beta": 0.0276,
"ldsc_observed_scale_h2_se": 0.0156,
"ldsc_intercept_beta": 0.9909,
"ldsc_intercept_se": 0.0053,
"ldsc_lambda_gc": 1.0031,
"ldsc_mean_chisq": 1.0047,
"ldsc_ratio": -1.9362
}
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 |
General metrics
af_correlation
: Correlation coefficient between AF
and AF_reference
.inflation_factor
(lambda
): Genomic inflation factor.mean_EFFECT
: Mean of EFFECT
size.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 below 5e-8
.n_mono
: Number of monomorphic (MAF == 1
or MAF == 0
) SNPs.n_ns
: Number of SNPs with nonsense values:
A, C, G or T
.< 0
or > 1
.<= 0
or = Infinity
).< 0
or > 1
.n_mac
: Number of cases where MAC
(\(2 \times N \times MAF\)) is less than 6
.is_snpid_unique
: true
if the combination of ID
REF
ALT
is unique and therefore no duplication in snpid.n_miss_<*>
: Number of NA
observations 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 expect ratio_se_n
to 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.
ratio_diff
: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean of diff
and the mean of diff2
(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.
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.
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.
r2 metrics
Sum of variance explained, calculated from the clumped top hits sample.
r2_sum<*>
: r2
statistics under various assumptions
1
: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).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
: NOT is_snpid_unique
.mean_EFFECT_nonfinite
: mean(EFFECT)
is NA
, NaN
, or Inf
.mean_EFFECT_05
: abs(mean(EFFECT))
> 0.5.mean_EFFECT_01
: abs(mean(EFFECT))
> 0.1.mean_chisq
: ldsc_mean_chisq
> 1.3 or ldsc_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<*>
> 0.5Plots
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 | 13519028 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 56985 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33309 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.051469e+00 | 6.184688e+00 | 1.0000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.902182e+07 | 5.591791e+07 | 3.0200e+02 | 3.292010e+07 | 7.013031e+07 | 1.148571e+08 | 2.492309e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 6.490000e-05 | 1.994260e-02 | -2.9595e-01 | -5.207200e-03 | 8.080000e-05 | 5.427600e-03 | 1.944780e-01 | ▁▁▅▇▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.437950e-02 | 1.384620e-02 | 2.7690e-03 | 4.132300e-03 | 7.571700e-03 | 2.059900e-02 | 8.023660e-02 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.992198e-01 | 2.887535e-01 | 2.0000e-07 | 2.487190e-01 | 4.987283e-01 | 7.493867e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.992136e-01 | 2.887573e-01 | 2.0000e-07 | 2.487083e-01 | 4.987216e-01 | 7.493841e-01 | 9.999999e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.915411e-01 | 2.545891e-01 | 1.0000e-03 | 7.623900e-03 | 6.088630e-02 | 2.968220e-01 | 9.990000e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 555297 | 0.9589611 | NA | NA | NA | NA | NA | 1.968893e-01 | 2.472270e-01 | 0.0000e+00 | 5.790700e-03 | 8.506390e-02 | 3.091390e-01 | 1.000000e+00 | ▇▂▁▁▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.569700e+04 | 0.000000e+00 | 2.5697e+04 | 2.569700e+04 | 2.569700e+04 | 2.569700e+04 | 2.569700e+04 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | 0.0000617 | 0.0060154 | 0.9918140 | 0.9918142 | 0.1121430 | 0.1894970 | 25697 |
1 | 693731 | rs12238997 | A | G | 0.0015357 | 0.0057446 | 0.7892199 | 0.7892173 | 0.1165660 | 0.1417730 | 25697 |
1 | 707522 | rs371890604 | G | C | 0.0003260 | 0.0064670 | 0.9597959 | 0.9597954 | 0.0975760 | 0.1293930 | 25697 |
1 | 717587 | rs144155419 | G | A | -0.0001001 | 0.0152414 | 0.9947580 | 0.9947580 | 0.0160183 | 0.0045926 | 25697 |
1 | 723329 | rs189787166 | A | T | -0.0170680 | 0.0422338 | 0.6861199 | 0.6861162 | 0.0019672 | 0.0003994 | 25697 |
1 | 730087 | rs148120343 | T | C | 0.0052008 | 0.0078900 | 0.5097943 | 0.5097889 | 0.0579332 | 0.0127796 | 25697 |
1 | 731718 | rs142557973 | T | C | 0.0022606 | 0.0054442 | 0.6779802 | 0.6779769 | 0.1229090 | 0.1543530 | 25697 |
1 | 732032 | rs61770163 | A | C | 0.0052809 | 0.0058001 | 0.3625760 | 0.3625671 | 0.1227700 | 0.1555510 | 25697 |
1 | 734349 | rs141242758 | T | C | 0.0022208 | 0.0054474 | 0.6835071 | 0.6835029 | 0.1221900 | 0.1525560 | 25697 |
1 | 740284 | rs61770167 | C | T | 0.0303856 | 0.0258137 | 0.2391630 | 0.2391511 | 0.0054168 | 0.0023962 | 25697 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | -0.0024286 | 0.0060752 | 0.6893345 | 0.6893318 | 0.0569276 | 0.0309934 | 25697 |
23 | 154923374 | rs111332691 | T | A | 0.0012544 | 0.0067291 | 0.8521179 | 0.8521164 | 0.0445188 | 0.0116556 | 25697 |
23 | 154925045 | rs509981 | C | T | -0.0046017 | 0.0032614 | 0.1582720 | 0.1582605 | 0.2412010 | 0.3634440 | 25697 |
23 | 154925895 | rs538470 | C | T | -0.0054428 | 0.0033329 | 0.1024679 | 0.1024559 | 0.2377450 | 0.3634440 | 25697 |
23 | 154927581 | rs644138 | G | A | -0.0044302 | 0.0030557 | 0.1471259 | 0.1471126 | 0.2986200 | 0.4635760 | 25697 |
23 | 154929412 | rs557132 | C | T | -0.0045797 | 0.0032629 | 0.1604531 | 0.1604411 | 0.2409870 | 0.3568210 | 25697 |
23 | 154929637 | rs35185538 | CT | C | -0.0046404 | 0.0033998 | 0.1722999 | 0.1722873 | 0.2268160 | 0.3011920 | 25697 |
23 | 154929952 | rs4012982 | CAA | C | -0.0051786 | 0.0034346 | 0.1316240 | 0.1316121 | 0.2348550 | 0.3165560 | 25697 |
23 | 154930230 | rs781880 | A | G | -0.0048395 | 0.0032607 | 0.1377730 | 0.1377608 | 0.2415200 | 0.3618540 | 25697 |
23 | 154930487 | rs781879 | T | A | -0.0050852 | 0.0113155 | 0.6531471 | 0.6531441 | 0.0189835 | 0.1263580 | 25697 |
1 692794 rs530212009 CA C . PASS AF=0.112143 ES:SE:LP:AF:SS:ID 6.17157e-05:0.00601545:0.00356977:0.112143:25697:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.116566 ES:SE:LP:AF:SS:ID 0.00153569:0.00574461:0.102802:0.116566:25697:rs12238997
1 707522 rs371890604 G C . PASS AF=0.097576 ES:SE:LP:AF:SS:ID 0.000326006:0.00646705:0.0178211:0.097576:25697:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0160183 ES:SE:LP:AF:SS:ID -0.000100135:0.0152414:0.00228256:0.0160183:25697:rs144155419
1 723329 rs189787166 A T . PASS AF=0.00196719 ES:SE:LP:AF:SS:ID -0.017068:0.0422338:0.1636:0.00196719:25697:rs189787166
1 730087 rs148120343 T C . PASS AF=0.0579332 ES:SE:LP:AF:SS:ID 0.00520083:0.00789001:0.292605:0.0579332:25697:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122909 ES:SE:LP:AF:SS:ID 0.00226057:0.0054442:0.168783:0.122909:25697:rs58276399
1 732032 rs61770163 A C . PASS AF=0.12277 ES:SE:LP:AF:SS:ID 0.00528091:0.00580011:0.440601:0.12277:25697:rs61770163
1 734349 rs141242758 T C . PASS AF=0.12219 ES:SE:LP:AF:SS:ID 0.00222083:0.00544738:0.165257:0.12219:25697:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00541682 ES:SE:LP:AF:SS:ID 0.0303856:0.0258137:0.621306:0.00541682:25697:rs61770167
1 742813 rs112573343 C T . PASS AF=0.00179627 ES:SE:LP:AF:SS:ID -0.0711088:0.048201:0.853388:0.00179627:25697:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.867932 ES:SE:LP:AF:SS:ID -0.00114448:0.00534735:0.0806457:0.867932:25697:rs529266287
1 750230 rs190826124 G C . PASS AF=0.0017537 ES:SE:LP:AF:SS:ID -0.00884032:0.0447329:0.0739973:0.0017537:25697:rs190826124
1 751343 rs28544273 T A . PASS AF=0.12446 ES:SE:LP:AF:SS:ID 0.00390969:0.00530425:0.336227:0.12446:25697:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.143673 ES:SE:LP:AF:SS:ID 0.00514735:0.0052585:0.484581:0.143673:25697:rs200141114
1 751756 rs28527770 T C . PASS AF=0.124586 ES:SE:LP:AF:SS:ID 0.00408665:0.00529757:0.356088:0.124586:25697:rs28527770
1 753405 rs3115860 C A . PASS AF=0.869298 ES:SE:LP:AF:SS:ID -0.0034469:0.00516825:0.296865:0.869298:25697:rs3115860
1 753425 rs3131970 T C . PASS AF=0.873888 ES:SE:LP:AF:SS:ID -0.0032244:0.00524832:0.26843:0.873888:25697:rs3131970
1 753541 rs2073813 G A . PASS AF=0.130223 ES:SE:LP:AF:SS:ID 0.00320365:0.00518415:0.270349:0.130223:25697:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0356073 ES:SE:LP:AF:SS:ID 0.000443784:0.00947955:0.0165266:0.0356073:25697:rs12184325
1 754182 rs3131969 A G . PASS AF=0.86893 ES:SE:LP:AF:SS:ID -0.00296166:0.00516451:0.246926:0.86893:25697:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869072 ES:SE:LP:AF:SS:ID -0.00323257:0.00516745:0.274409:0.869072:25697:rs3131968
1 754334 rs3131967 T C . PASS AF=0.868931 ES:SE:LP:AF:SS:ID -0.00297105:0.00516433:0.247881:0.868931:25697:rs3131967
1 754433 rs150578204 G A . PASS AF=0.0049226 ES:SE:LP:AF:SS:ID 0.0120813:0.0270556:0.183617:0.0049226:25697:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00489216 ES:SE:LP:AF:SS:ID 0.0125878:0.0271194:0.192104:0.00489216:25697:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00561735 ES:SE:LP:AF:SS:ID 0.00559255:0.0253333:0.0833976:0.00561735:25697:rs184270342
1 755890 rs3115858 A T . PASS AF=0.868988 ES:SE:LP:AF:SS:ID -0.00363275:0.00515418:0.317917:0.868988:25697:rs3115858
1 756434 rs61768170 G C . PASS AF=0.127576 ES:SE:LP:AF:SS:ID 0.00321223:0.00525643:0.266694:0.127576:25697:rs61768170
1 756604 rs3131962 A G . PASS AF=0.868487 ES:SE:LP:AF:SS:ID -0.00389377:0.00514078:0.347947:0.868487:25697:rs3131962
1 757640 rs3115853 G A . PASS AF=0.867984 ES:SE:LP:AF:SS:ID -0.00333431:0.00514046:0.286865:0.867984:25697:rs3115853
1 757734 rs4951929 C T . PASS AF=0.868672 ES:SE:LP:AF:SS:ID -0.00382074:0.00514482:0.339412:0.868672:25697:rs4951929
1 757936 rs4951862 C A . PASS AF=0.868677 ES:SE:LP:AF:SS:ID -0.00381874:0.00514512:0.339164:0.868677:25697:rs4951862
1 758144 rs3131956 A G . PASS AF=0.868677 ES:SE:LP:AF:SS:ID -0.00382015:0.00514513:0.339321:0.868677:25697:rs3131956
1 758626 rs3131954 C T . PASS AF=0.86918 ES:SE:LP:AF:SS:ID -0.00369222:0.00516042:0.323934:0.86918:25697:rs3131954
1 759293 rs10157329 T A . PASS AF=0.09951 ES:SE:LP:AF:SS:ID 0.00243801:0.00601322:0.164211:0.09951:25697:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00646211 ES:SE:LP:AF:SS:ID 0.0177672:0.0230419:0.35589:0.00646211:25697:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.873078 ES:SE:LP:AF:SS:ID -0.00272599:0.00523273:0.220111:0.873078:25697:rs3115851
1 761732 rs2286139 C T . PASS AF=0.862503 ES:SE:LP:AF:SS:ID -0.00235227:0.00513424:0.189199:0.862503:25697:rs2286139
1 761752 rs1057213 C T . PASS AF=0.867879 ES:SE:LP:AF:SS:ID -0.00298407:0.00518403:0.24805:0.867879:25697:rs1057213
1 762273 rs3115849 G A . PASS AF=0.86493 ES:SE:LP:AF:SS:ID -0.00441288:0.00518971:0.403228:0.86493:25697:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0994497 ES:SE:LP:AF:SS:ID 0.00028324:0.00621763:0.0160735:0.0994497:25697:rs12095200
1 762589 rs3115848 G C . PASS AF=0.870274 ES:SE:LP:AF:SS:ID -0.00402364:0.0052489:0.353258:0.870274:25697:rs3115848
1 762592 rs3131950 C G . PASS AF=0.870274 ES:SE:LP:AF:SS:ID -0.00402435:0.0052489:0.353338:0.870274:25697:rs3131950
1 762601 rs3131949 T C . PASS AF=0.870271 ES:SE:LP:AF:SS:ID -0.00402628:0.00524891:0.35355:0.870271:25697:rs3131949
1 762632 rs3131948 T A . PASS AF=0.870593 ES:SE:LP:AF:SS:ID -0.00398287:0.00524999:0.348651:0.870593:25697:rs3131948
1 764191 rs7515915 T G . PASS AF=0.12718 ES:SE:LP:AF:SS:ID 0.00304408:0.00525114:0.250169:0.12718:25697:rs7515915
1 766007 rs61768174 A C . PASS AF=0.106621 ES:SE:LP:AF:SS:ID 0.00240895:0.00570841:0.171967:0.106621:25697:rs61768174
1 766105 rs2519015 T A . PASS AF=0.853855 ES:SE:LP:AF:SS:ID -0.003248:0.00511843:0.27925:0.853855:25697:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00184915 ES:SE:LP:AF:SS:ID -0.0189989:0.0424946:0.183882:0.00184915:25697:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.838998 ES:SE:LP:AF:SS:ID -0.00459112:0.00507285:0.437166:0.838998:25697:rs376645387