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"file_date": "2019-11-25T16:20:41.907133",
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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-4979/ukb-d-4979.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-4979/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 17:17:55 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-4979/ukb-d-4979.vcf.gz ...
Read summary statistics for 13567321 SNPs.
Dropped 12685 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, 1283503 SNPs remain.
After merging with regression SNP LD, 1283503 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0416 (0.0049)
Lambda GC: 1.1031
Mean Chi^2: 1.1033
Intercept: 1.009 (0.0065)
Ratio: 0.0874 (0.0626)
Analysis finished at Mon Nov 25 17:20:10 2019
Total time elapsed: 2.0m:15.18s
{
"af_correlation": 0.9521,
"inflation_factor": 1.073,
"mean_EFFECT": -0,
"n": 113356,
"n_snps": 13567321,
"n_clumped_hits": 0,
"n_p_sig": 0,
"n_mono": 0,
"n_ns": 1251197,
"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": 563058,
"n_est": 113800.4773,
"ratio_se_n": 1.002,
"mean_diff": -0,
"ratio_diff": 53.6227,
"sd_y_est1": 0.5006,
"sd_y_est2": 0.5016,
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1283503,
"ldsc_nsnp_merge_regression_ld": 1283503,
"ldsc_observed_scale_h2_beta": 0.0416,
"ldsc_observed_scale_h2_se": 0.0049,
"ldsc_intercept_beta": 1.009,
"ldsc_intercept_se": 0.0065,
"ldsc_lambda_gc": 1.1031,
"ldsc_mean_chisq": 1.1033,
"ldsc_ratio": 0.0871
}
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 | 1.000000 | 3 | 94 | 0 | 13555300 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.000000 | 1 | 100 | 0 | 57051 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.000000 | 1 | 342 | 0 | 33328 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.000000 | NA | NA | NA | NA | NA | 9.051388e+00 | 6.184971e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
numeric | POS | 0 | 1.000000 | NA | NA | NA | NA | NA | 7.902457e+07 | 5.591678e+07 | 3.02000e+02 | 3.292789e+07 | 7.013742e+07 | 1.148559e+08 | 2.492309e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.000000 | NA | NA | NA | NA | NA | -3.330000e-05 | 1.229920e-02 | -1.44083e-01 | -3.391200e-03 | -2.210000e-05 | 3.333800e-03 | 1.535130e-01 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.000000 | NA | NA | NA | NA | NA | 8.799800e-03 | 8.479900e-03 | 1.72820e-03 | 2.513700e-03 | 4.623500e-03 | 1.263570e-02 | 4.343030e-02 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.000000 | NA | NA | NA | NA | NA | 4.894756e-01 | 2.911709e-01 | 1.00000e-07 | 2.350190e-01 | 4.847625e-01 | 7.418686e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.000000 | NA | NA | NA | NA | NA | 4.894742e-01 | 2.911718e-01 | 1.00000e-07 | 2.350168e-01 | 4.847618e-01 | 7.418674e-01 | 9.999999e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.000000 | NA | NA | NA | NA | NA | 1.910649e-01 | 2.544623e-01 | 1.00000e-03 | 7.507000e-03 | 6.031960e-02 | 2.958290e-01 | 9.990000e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 563058 | 0.958499 | NA | NA | NA | NA | NA | 1.965142e-01 | 2.471414e-01 | 0.00000e+00 | 5.790700e-03 | 8.446490e-02 | 3.085060e-01 | 1.000000e+00 | ▇▂▁▁▁ |
numeric | N | 0 | 1.000000 | NA | NA | NA | NA | NA | 1.133560e+05 | 0.000000e+00 | 1.13356e+05 | 1.133560e+05 | 1.133560e+05 | 1.133560e+05 | 1.133560e+05 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | 0.0037370 | 0.0036785 | 0.3096877 | 0.3096846 | 0.1115570 | 0.1894970 | 113356 |
1 | 693731 | rs12238997 | A | G | 0.0054204 | 0.0034793 | 0.1192609 | 0.1192580 | 0.1168090 | 0.1417730 | 113356 |
1 | 707522 | rs371890604 | G | C | 0.0042662 | 0.0039024 | 0.2743039 | 0.2743011 | 0.0981383 | 0.1293930 | 113356 |
1 | 717587 | rs144155419 | G | A | 0.0065994 | 0.0093747 | 0.4814620 | 0.4814601 | 0.0156670 | 0.0045926 | 113356 |
1 | 723329 | rs189787166 | A | T | -0.0118718 | 0.0278440 | 0.6698399 | 0.6698395 | 0.0016865 | 0.0003994 | 113356 |
1 | 730087 | rs148120343 | T | C | 0.0016814 | 0.0048474 | 0.7286903 | 0.7286902 | 0.0569312 | 0.0127796 | 113356 |
1 | 731718 | rs142557973 | T | C | 0.0048709 | 0.0033030 | 0.1403011 | 0.1402972 | 0.1226070 | 0.1543530 | 113356 |
1 | 732032 | rs61770163 | A | C | 0.0048065 | 0.0035191 | 0.1719939 | 0.1719920 | 0.1221310 | 0.1555510 | 113356 |
1 | 734349 | rs141242758 | T | C | 0.0048678 | 0.0033054 | 0.1408410 | 0.1408379 | 0.1218150 | 0.1525560 | 113356 |
1 | 740284 | rs61770167 | C | T | 0.0002134 | 0.0148117 | 0.9885070 | 0.9885074 | 0.0059857 | 0.0023962 | 113356 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | -0.0009645 | 0.0038537 | 0.8023700 | 0.8023695 | 0.0550274 | 0.0309934 | 113356 |
23 | 154923374 | rs111332691 | T | A | 0.0022028 | 0.0042082 | 0.6006549 | 0.6006549 | 0.0442279 | 0.0116556 | 113356 |
23 | 154925045 | rs509981 | C | T | 0.0004529 | 0.0020205 | 0.8226500 | 0.8226491 | 0.2440180 | 0.3634440 | 113356 |
23 | 154925895 | rs538470 | C | T | 0.0003857 | 0.0020660 | 0.8518970 | 0.8518968 | 0.2404880 | 0.3634440 | 113356 |
23 | 154927581 | rs644138 | G | A | 0.0002675 | 0.0019005 | 0.8880579 | 0.8880576 | 0.2994530 | 0.4635760 | 113356 |
23 | 154929412 | rs557132 | C | T | 0.0004077 | 0.0020213 | 0.8401641 | 0.8401633 | 0.2438350 | 0.3568210 | 113356 |
23 | 154929637 | rs35185538 | CT | C | -0.0004567 | 0.0021085 | 0.8285141 | 0.8285141 | 0.2278850 | 0.3011920 | 113356 |
23 | 154929952 | rs4012982 | CAA | C | -0.0003204 | 0.0021262 | 0.8802049 | 0.8802053 | 0.2380420 | 0.3165560 | 113356 |
23 | 154930230 | rs781880 | A | G | 0.0002074 | 0.0020208 | 0.9182539 | 0.9182541 | 0.2443310 | 0.3618540 | 113356 |
23 | 154930487 | rs781879 | T | A | 0.0017148 | 0.0070150 | 0.8068849 | 0.8068844 | 0.0191514 | 0.1263580 | 113356 |
1 692794 rs530212009 CA C . PASS AF=0.111557 ES:SE:LP:AF:SS:ID 0.00373695:0.00367852:0.509076:0.111557:113356:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.116809 ES:SE:LP:AF:SS:ID 0.00542037:0.00347929:0.923502:0.116809:113356:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0981383 ES:SE:LP:AF:SS:ID 0.00426618:0.00390243:0.561768:0.0981383:113356:rs371890604
1 717587 rs144155419 G A . PASS AF=0.015667 ES:SE:LP:AF:SS:ID 0.00659937:0.00937469:0.317438:0.015667:113356:rs144155419
1 723329 rs189787166 A T . PASS AF=0.00168651 ES:SE:LP:AF:SS:ID -0.0118718:0.027844:0.174029:0.00168651:113356:rs189787166
1 730087 rs148120343 T C . PASS AF=0.0569312 ES:SE:LP:AF:SS:ID 0.00168141:0.0048474:0.137457:0.0569312:113356:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122607 ES:SE:LP:AF:SS:ID 0.00487093:0.00330303:0.852939:0.122607:113356:rs58276399
1 732032 rs61770163 A C . PASS AF=0.122131 ES:SE:LP:AF:SS:ID 0.00480651:0.00351911:0.764487:0.122131:113356:rs61770163
1 734349 rs141242758 T C . PASS AF=0.121815 ES:SE:LP:AF:SS:ID 0.00486779:0.0033054:0.851271:0.121815:113356:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00598574 ES:SE:LP:AF:SS:ID 0.000213353:0.0148117:0.00502025:0.00598574:113356:rs61770167
1 742813 rs112573343 C T . PASS AF=0.00178751 ES:SE:LP:AF:SS:ID 0.0357798:0.0296078:0.644217:0.00178751:113356:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.868772 ES:SE:LP:AF:SS:ID -0.00613261:0.00325686:1.22398:0.868772:113356:rs529266287
1 750230 rs190826124 G C . PASS AF=0.00158738 ES:SE:LP:AF:SS:ID 0.00688078:0.028816:0.0908324:0.00158738:113356:rs190826124
1 751343 rs28544273 T A . PASS AF=0.123785 ES:SE:LP:AF:SS:ID 0.00617358:0.00322643:1.25419:0.123785:113356:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.143326 ES:SE:LP:AF:SS:ID 0.00587083:0.00319574:1.17914:0.143326:113356:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123903 ES:SE:LP:AF:SS:ID 0.00613612:0.0032218:1.24535:0.123903:113356:rs28527770
1 753405 rs3115860 C A . PASS AF=0.869987 ES:SE:LP:AF:SS:ID -0.00638385:0.00313808:1.37755:0.869987:113356:rs3115860
1 753425 rs3131970 T C . PASS AF=0.874681 ES:SE:LP:AF:SS:ID -0.00599728:0.00319109:1.22044:0.874681:113356:rs3131970
1 753541 rs2073813 G A . PASS AF=0.129585 ES:SE:LP:AF:SS:ID 0.00600744:0.00314514:1.25083:0.129585:113356:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0366809 ES:SE:LP:AF:SS:ID 0.00508908:0.00568084:0.431395:0.0366809:113356:rs12184325
1 754182 rs3131969 A G . PASS AF=0.869597 ES:SE:LP:AF:SS:ID -0.00647596:0.00313498:1.41052:0.869597:113356:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869719 ES:SE:LP:AF:SS:ID -0.00647005:0.0031366:1.4074:0.869719:113356:rs3131968
1 754334 rs3131967 T C . PASS AF=0.869595 ES:SE:LP:AF:SS:ID -0.00649299:0.00313484:1.41636:0.869595:113356:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00512344 ES:SE:LP:AF:SS:ID 0.0297809:0.0160086:1.20173:0.00512344:113356:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00509021 ES:SE:LP:AF:SS:ID 0.0300929:0.0160509:1.21598:0.00509021:113356:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00546505 ES:SE:LP:AF:SS:ID -0.012275:0.0157321:0.361267:0.00546505:113356:rs184270342
1 755890 rs3115858 A T . PASS AF=0.869706 ES:SE:LP:AF:SS:ID -0.00639168:0.00312956:1.38596:0.869706:113356:rs3115858
1 756434 rs61768170 G C . PASS AF=0.126875 ES:SE:LP:AF:SS:ID 0.00635399:0.00319351:1.33132:0.126875:113356:rs61768170
1 756604 rs3131962 A G . PASS AF=0.869283 ES:SE:LP:AF:SS:ID -0.00657027:0.00312225:1.4516:0.869283:113356:rs3131962
1 757640 rs3115853 G A . PASS AF=0.868493 ES:SE:LP:AF:SS:ID -0.00677802:0.00311851:1.52657:0.868493:113356:rs3115853
1 757734 rs4951929 C T . PASS AF=0.869434 ES:SE:LP:AF:SS:ID -0.00657278:0.00312482:1.45061:0.869434:113356:rs4951929
1 757936 rs4951862 C A . PASS AF=0.869441 ES:SE:LP:AF:SS:ID -0.00657256:0.00312504:1.45037:0.869441:113356:rs4951862
1 758144 rs3131956 A G . PASS AF=0.86945 ES:SE:LP:AF:SS:ID -0.00659891:0.00312514:1.45933:0.86945:113356:rs3131956
1 758626 rs3131954 C T . PASS AF=0.869882 ES:SE:LP:AF:SS:ID -0.00656939:0.00313321:1.44342:0.869882:113356:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0996929 ES:SE:LP:AF:SS:ID 0.00513782:0.00363391:0.802973:0.0996929:113356:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00627435 ES:SE:LP:AF:SS:ID -0.00814089:0.0142765:0.245252:0.00627435:113356:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.873803 ES:SE:LP:AF:SS:ID -0.00661557:0.0031807:1.42555:0.873803:113356:rs3115851
1 761732 rs2286139 C T . PASS AF=0.863151 ES:SE:LP:AF:SS:ID -0.00649022:0.00311901:1.42656:0.863151:113356:rs2286139
1 761752 rs1057213 C T . PASS AF=0.868603 ES:SE:LP:AF:SS:ID -0.00659602:0.00314908:1.44117:0.868603:113356:rs1057213
1 762273 rs3115849 G A . PASS AF=0.865373 ES:SE:LP:AF:SS:ID -0.00565969:0.0031488:1.14102:0.865373:113356:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0993746 ES:SE:LP:AF:SS:ID 0.00953537:0.0037754:1.93744:0.0993746:113356:rs12095200
1 762589 rs3115848 G C . PASS AF=0.87063 ES:SE:LP:AF:SS:ID -0.00610535:0.00318514:1.25756:0.87063:113356:rs3115848
1 762592 rs3131950 C G . PASS AF=0.87063 ES:SE:LP:AF:SS:ID -0.00610496:0.00318514:1.25744:0.87063:113356:rs3131950
1 762601 rs3131949 T C . PASS AF=0.870632 ES:SE:LP:AF:SS:ID -0.00612215:0.00318531:1.26273:0.870632:113356:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871005 ES:SE:LP:AF:SS:ID -0.00637134:0.00318699:1.34111:0.871005:113356:rs3131948
1 764191 rs7515915 T G . PASS AF=0.126447 ES:SE:LP:AF:SS:ID 0.00620729:0.00318943:1.28708:0.126447:113356:rs7515915
1 766007 rs61768174 A C . PASS AF=0.106176 ES:SE:LP:AF:SS:ID 0.005894:0.00346816:1.04946:0.106176:113356:rs61768174
1 766105 rs2519015 T A . PASS AF=0.854535 ES:SE:LP:AF:SS:ID -0.00523607:0.00311908:1.03054:0.854535:113356:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00158503 ES:SE:LP:AF:SS:ID -0.00994325:0.0280624:0.140805:0.00158503:113356:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.837873 ES:SE:LP:AF:SS:ID -0.000824181:0.00306618:0.103426:0.837873:113356:rs376645387