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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-20534/ukb-d-20534.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-20534/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 17:16:23 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20534/ukb-d-20534.vcf.gz ...
Read summary statistics for 13149722 SNPs.
Dropped 12098 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, 1283416 SNPs remain.
After merging with regression SNP LD, 1283416 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0398 (0.0106)
Lambda GC: 1.0331
Mean Chi^2: 1.0351
Intercept: 0.9996 (0.0062)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:18:34 2019
Total time elapsed: 2.0m:11.18s
{
"af_correlation": 0.9514,
"inflation_factor": 1.0249,
"mean_EFFECT": -6.244e-06,
"n": 45540,
"n_snps": 13149722,
"n_clumped_hits": 1,
"n_p_sig": 1,
"n_mono": 0,
"n_ns": 1235281,
"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": 462882,
"n_est": 45649.3335,
"ratio_se_n": 1.0012,
"mean_diff": -0,
"ratio_diff": 10.5702,
"sd_y_est1": 0.4034,
"sd_y_est2": 0.4039,
"r2_sum1": 0.0001,
"r2_sum2": 0.0007,
"r2_sum3": 0.0007,
"r2_sum4": 0.0007,
"ldsc_nsnp_merge_refpanel_ld": 1283416,
"ldsc_nsnp_merge_regression_ld": 1283416,
"ldsc_observed_scale_h2_beta": 0.0398,
"ldsc_observed_scale_h2_se": 0.0106,
"ldsc_intercept_beta": 0.9996,
"ldsc_intercept_se": 0.0062,
"ldsc_lambda_gc": 1.0331,
"ldsc_mean_chisq": 1.0351,
"ldsc_ratio": -0.0114
}
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 | 13138277 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 56161 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33048 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.056793e+00 | 6.185413e+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 | 7.898155e+07 | 5.592813e+07 | 3.02000e+02 | 3.285790e+07 | 7.006102e+07 | 1.148129e+08 | 2.492309e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -6.200000e-06 | 1.404220e-02 | -1.47263e-01 | -4.049500e-03 | -4.370000e-05 | 3.956800e-03 | 1.802460e-01 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.024870e-02 | 9.525500e-03 | 2.29150e-03 | 3.162400e-03 | 5.579400e-03 | 1.459060e-02 | 4.966610e-02 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.960088e-01 | 2.893867e-01 | 0.00000e+00 | 2.448511e-01 | 4.947206e-01 | 7.461257e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.960053e-01 | 2.893888e-01 | 0.00000e+00 | 2.448451e-01 | 4.947169e-01 | 7.461232e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.967957e-01 | 2.558357e-01 | 1.33630e-03 | 9.061600e-03 | 6.774330e-02 | 3.071920e-01 | 9.986640e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 462882 | 0.9647991 | NA | NA | NA | NA | NA | 2.008937e-01 | 2.480960e-01 | 0.00000e+00 | 6.789100e-03 | 9.059600e-02 | 3.166930e-01 | 1.000000e+00 | ▇▂▁▁▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.554000e+04 | 0.000000e+00 | 4.55400e+04 | 4.554000e+04 | 4.554000e+04 | 4.554000e+04 | 4.554000e+04 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | 0.0093747 | 0.0046613 | 0.0443098 | 0.0443040 | 0.1119100 | 0.1894970 | 45540 |
1 | 693731 | rs12238997 | A | G | 0.0121169 | 0.0043976 | 0.0058652 | 0.0058627 | 0.1172340 | 0.1417730 | 45540 |
1 | 707522 | rs371890604 | G | C | 0.0090316 | 0.0049298 | 0.0669545 | 0.0669474 | 0.0989953 | 0.1293930 | 45540 |
1 | 717587 | rs144155419 | G | A | 0.0251592 | 0.0118856 | 0.0342831 | 0.0342785 | 0.0156843 | 0.0045926 | 45540 |
1 | 723329 | rs189787166 | A | T | 0.0234167 | 0.0345126 | 0.4974598 | 0.4974565 | 0.0017920 | 0.0003994 | 45540 |
1 | 730087 | rs148120343 | T | C | 0.0071040 | 0.0061418 | 0.2474161 | 0.2474103 | 0.0568549 | 0.0127796 | 45540 |
1 | 731718 | rs142557973 | T | C | 0.0105634 | 0.0041715 | 0.0113360 | 0.0113330 | 0.1231910 | 0.1543530 | 45540 |
1 | 732032 | rs61770163 | A | C | 0.0114835 | 0.0044449 | 0.0097832 | 0.0097802 | 0.1226120 | 0.1555510 | 45540 |
1 | 734349 | rs141242758 | T | C | 0.0104369 | 0.0041723 | 0.0123726 | 0.0123686 | 0.1225270 | 0.1525560 | 45540 |
1 | 740284 | rs61770167 | C | T | 0.0123017 | 0.0187964 | 0.5128106 | 0.5128084 | 0.0060200 | 0.0023962 | 45540 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | 0.0066060 | 0.0050594 | 0.1916691 | 0.1916620 | 0.0559848 | 0.0309934 | 45540 |
23 | 154923374 | rs111332691 | T | A | -0.0070233 | 0.0056236 | 0.2117069 | 0.2117011 | 0.0435881 | 0.0116556 | 45540 |
23 | 154925045 | rs509981 | C | T | -0.0000726 | 0.0026712 | 0.9783290 | 0.9783286 | 0.2457860 | 0.3634440 | 45540 |
23 | 154925895 | rs538470 | C | T | 0.0003940 | 0.0027318 | 0.8853111 | 0.8853110 | 0.2422210 | 0.3634440 | 45540 |
23 | 154927581 | rs644138 | G | A | 0.0016158 | 0.0025119 | 0.5200463 | 0.5200439 | 0.3022470 | 0.4635760 | 45540 |
23 | 154929412 | rs557132 | C | T | -0.0001246 | 0.0026718 | 0.9628169 | 0.9628171 | 0.2456640 | 0.3568210 | 45540 |
23 | 154929637 | rs35185538 | CT | C | -0.0010502 | 0.0027921 | 0.7068203 | 0.7068193 | 0.2296840 | 0.3011920 | 45540 |
23 | 154929952 | rs4012982 | CAA | C | 0.0005625 | 0.0028159 | 0.8416771 | 0.8416758 | 0.2394930 | 0.3165560 | 45540 |
23 | 154930230 | rs781880 | A | G | 0.0000667 | 0.0026712 | 0.9800740 | 0.9800738 | 0.2460210 | 0.3618540 | 45540 |
23 | 154930487 | rs781879 | T | A | 0.0095118 | 0.0091376 | 0.2979038 | 0.2978990 | 0.0193766 | 0.1263580 | 45540 |
1 692794 rs530212009 CA C . PASS AF=0.11191 ES:SE:LP:AF:SS:ID 0.00937474:0.00466126:1.3535:0.11191:45540:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.117234 ES:SE:LP:AF:SS:ID 0.0121169:0.00439757:2.23172:0.117234:45540:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0989953 ES:SE:LP:AF:SS:ID 0.00903158:0.00492983:1.17422:0.0989953:45540:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0156843 ES:SE:LP:AF:SS:ID 0.0251592:0.0118856:1.46492:0.0156843:45540:rs144155419
1 723329 rs189787166 A T . PASS AF=0.00179196 ES:SE:LP:AF:SS:ID 0.0234167:0.0345126:0.303242:0.00179196:45540:rs189787166
1 730087 rs148120343 T C . PASS AF=0.0568549 ES:SE:LP:AF:SS:ID 0.00710399:0.0061418:0.606572:0.0568549:45540:rs148120343
1 731718 rs58276399 T C . PASS AF=0.123191 ES:SE:LP:AF:SS:ID 0.0105634:0.00417153:1.94554:0.123191:45540:rs58276399
1 732032 rs61770163 A C . PASS AF=0.122612 ES:SE:LP:AF:SS:ID 0.0114835:0.00444493:2.00952:0.122612:45540:rs61770163
1 734349 rs141242758 T C . PASS AF=0.122527 ES:SE:LP:AF:SS:ID 0.0104369:0.00417234:1.90754:0.122527:45540:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00602 ES:SE:LP:AF:SS:ID 0.0123017:0.0187964:0.290043:0.00602:45540:rs61770167
1 742813 rs112573343 C T . PASS AF=0.0018522 ES:SE:LP:AF:SS:ID -0.0392695:0.0364911:0.54995:0.0018522:45540:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.868242 ES:SE:LP:AF:SS:ID -0.00782939:0.00410698:1.24711:0.868242:45540:rs529266287
1 750230 rs190826124 G C . PASS AF=0.00162197 ES:SE:LP:AF:SS:ID -0.00027402:0.0364109:0.0026158:0.00162197:45540:rs190826124
1 751343 rs28544273 T A . PASS AF=0.124643 ES:SE:LP:AF:SS:ID 0.0090284:0.00406606:1.57848:0.124643:45540:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.144077 ES:SE:LP:AF:SS:ID 0.00791625:0.00402772:1.30654:0.144077:45540:rs200141114
1 751756 rs28527770 T C . PASS AF=0.124737 ES:SE:LP:AF:SS:ID 0.00894031:0.00406065:1.55765:0.124737:45540:rs28527770
1 753405 rs3115860 C A . PASS AF=0.868906 ES:SE:LP:AF:SS:ID -0.0085563:0.00395802:1.51369:0.868906:45540:rs3115860
1 753425 rs3131970 T C . PASS AF=0.873626 ES:SE:LP:AF:SS:ID -0.00864813:0.00402218:1.50098:0.873626:45540:rs3131970
1 753541 rs2073813 G A . PASS AF=0.130541 ES:SE:LP:AF:SS:ID 0.00873327:0.00396802:1.55678:0.130541:45540:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0370334 ES:SE:LP:AF:SS:ID -0.000578339:0.00718837:0.0287817:0.0370334:45540:rs12184325
1 754182 rs3131969 A G . PASS AF=0.868516 ES:SE:LP:AF:SS:ID -0.00869899:0.00395389:1.55589:0.868516:45540:rs3131969
1 754192 rs3131968 A G . PASS AF=0.868563 ES:SE:LP:AF:SS:ID -0.00856404:0.00395456:1.5179:0.868563:45540:rs3131968
1 754334 rs3131967 T C . PASS AF=0.868519 ES:SE:LP:AF:SS:ID -0.00871003:0.00395378:1.55905:0.868519:45540:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00523349 ES:SE:LP:AF:SS:ID -0.00847186:0.0200627:0.172094:0.00523349:45540:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00520469 ES:SE:LP:AF:SS:ID -0.00869295:0.0201075:0.176847:0.00520469:45540:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00579021 ES:SE:LP:AF:SS:ID 0.00617864:0.019374:0.125059:0.00579021:45540:rs184270342
1 755890 rs3115858 A T . PASS AF=0.868542 ES:SE:LP:AF:SS:ID -0.00857668:0.00394638:1.52633:0.868542:45540:rs3115858
1 756434 rs61768170 G C . PASS AF=0.127831 ES:SE:LP:AF:SS:ID 0.00872041:0.00402716:1.51766:0.127831:45540:rs61768170
1 756604 rs3131962 A G . PASS AF=0.868061 ES:SE:LP:AF:SS:ID -0.00868477:0.00393642:1.56272:0.868061:45540:rs3131962
1 757640 rs3115853 G A . PASS AF=0.867535 ES:SE:LP:AF:SS:ID -0.00881834:0.00393472:1.6017:0.867535:45540:rs3115853
1 757734 rs4951929 C T . PASS AF=0.868251 ES:SE:LP:AF:SS:ID -0.00859608:0.00393987:1.53569:0.868251:45540:rs4951929
1 757936 rs4951862 C A . PASS AF=0.868258 ES:SE:LP:AF:SS:ID -0.00859857:0.00394015:1.53621:0.868258:45540:rs4951862
1 758144 rs3131956 A G . PASS AF=0.868261 ES:SE:LP:AF:SS:ID -0.00859674:0.00394018:1.53568:0.868261:45540:rs3131956
1 758626 rs3131954 C T . PASS AF=0.868695 ES:SE:LP:AF:SS:ID -0.00853405:0.00395054:1.51201:0.868695:45540:rs3131954
1 759293 rs10157329 T A . PASS AF=0.100503 ES:SE:LP:AF:SS:ID 0.00720166:0.00458723:0.933913:0.100503:45540:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00682163 ES:SE:LP:AF:SS:ID 0.00794792:0.0174013:0.188521:0.00682163:45540:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.872853 ES:SE:LP:AF:SS:ID -0.00822642:0.00401202:1.39441:0.872853:45540:rs3115851
1 761732 rs2286139 C T . PASS AF=0.862109 ES:SE:LP:AF:SS:ID -0.00887042:0.00393356:1.61737:0.862109:45540:rs2286139
1 761752 rs1057213 C T . PASS AF=0.867419 ES:SE:LP:AF:SS:ID -0.00849052:0.00397288:1.48687:0.867419:45540:rs1057213
1 762273 rs3115849 G A . PASS AF=0.864621 ES:SE:LP:AF:SS:ID -0.00769197:0.00397753:1.2746:0.864621:45540:rs3115849
1 762485 rs12095200 C A . PASS AF=0.100688 ES:SE:LP:AF:SS:ID 0.00937279:0.00474199:1.31787:0.100688:45540:rs12095200
1 762589 rs3115848 G C . PASS AF=0.869686 ES:SE:LP:AF:SS:ID -0.00801456:0.00401992:1.33545:0.869686:45540:rs3115848
1 762592 rs3131950 C G . PASS AF=0.869686 ES:SE:LP:AF:SS:ID -0.00801486:0.00401992:1.33553:0.869686:45540:rs3131950
1 762601 rs3131949 T C . PASS AF=0.869682 ES:SE:LP:AF:SS:ID -0.00801629:0.00401993:1.3359:0.869682:45540:rs3131949
1 762632 rs3131948 T A . PASS AF=0.870001 ES:SE:LP:AF:SS:ID -0.00809614:0.00402158:1.35554:0.870001:45540:rs3131948
1 764191 rs7515915 T G . PASS AF=0.127405 ES:SE:LP:AF:SS:ID 0.00835205:0.00402454:1.42061:0.127405:45540:rs7515915
1 766007 rs61768174 A C . PASS AF=0.107055 ES:SE:LP:AF:SS:ID 0.00728467:0.0043771:1.01743:0.107055:45540:rs61768174
1 766105 rs2519015 T A . PASS AF=0.853126 ES:SE:LP:AF:SS:ID -0.00816649:0.00392945:1.42378:0.853126:45540:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00171256 ES:SE:LP:AF:SS:ID 0.0267431:0.0346076:0.35687:0.00171256:45540:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.837478 ES:SE:LP:AF:SS:ID -0.002926:0.00390905:0.3428:0.837478:45540:rs376645387