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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-100920_2103/ukb-d-100920_2103.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-100920_2103/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 15:26:24 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-100920_2103/ukb-d-100920_2103.vcf.gz ...
Read summary statistics for 13352661 SNPs.
Dropped 12393 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, 1283466 SNPs remain.
After merging with regression SNP LD, 1283466 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0063 (0.0081)
Lambda GC: 1.0009
Mean Chi^2: 1.0047
Intercept: 1.0111 (0.0056)
Ratio: 2.3687 (1.1911)
Analysis finished at Mon Nov 25 15:28:27 2019
Total time elapsed: 2.0m:2.96s
{
"af_correlation": 0.9518,
"inflation_factor": 0.9996,
"mean_EFFECT": 0,
"n": 51427,
"n_snps": 13352661,
"n_clumped_hits": 0,
"n_p_sig": 0,
"n_mono": 0,
"n_ns": 1243739,
"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": 507386,
"n_est": 51660.4076,
"ratio_se_n": 1.0023,
"mean_diff": 0,
"ratio_diff": 27.9072,
"sd_y_est1": 0.4029,
"sd_y_est2": 0.4039,
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1283466,
"ldsc_nsnp_merge_regression_ld": 1283466,
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": 1.0111,
"ldsc_intercept_se": 0.0056,
"ldsc_lambda_gc": 1.0009,
"ldsc_mean_chisq": 1.0047,
"ldsc_ratio": 2.3617
}
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 | TRUE |
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 | 13340927 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 56638 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33224 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.053506e+00 | 6.184974e+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 | 7.900790e+07 | 5.592697e+07 | 3.02000e+02 | 3.289194e+07 | 7.010736e+07 | 1.148451e+08 | 2.492309e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.170000e-05 | 1.384240e-02 | -1.45628e-01 | -3.825300e-03 | -2.620000e-05 | 3.742000e-03 | 1.855890e-01 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.004880e-02 | 9.507000e-03 | 2.06840e-03 | 2.988100e-03 | 5.377700e-03 | 1.436280e-02 | 5.026970e-02 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.002059e-01 | 2.887593e-01 | 2.00000e-07 | 2.501618e-01 | 5.000806e-01 | 7.504832e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.002028e-01 | 2.887612e-01 | 2.00000e-07 | 2.501562e-01 | 5.000778e-01 | 7.504817e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.939749e-01 | 2.551748e-01 | 1.18680e-03 | 8.271500e-03 | 6.398840e-02 | 3.016160e-01 | 9.988130e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 507386 | 0.9620011 | NA | NA | NA | NA | NA | 1.986969e-01 | 2.476220e-01 | 0.00000e+00 | 6.190100e-03 | 8.746010e-02 | 3.127000e-01 | 1.000000e+00 | ▇▂▁▁▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.142700e+04 | 0.000000e+00 | 5.14270e+04 | 5.142700e+04 | 5.142700e+04 | 5.142700e+04 | 5.142700e+04 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | 0.0020087 | 0.0043738 | 0.6460528 | 0.6460516 | 0.1121000 | 0.1894970 | 51427 |
1 | 693731 | rs12238997 | A | G | -0.0005876 | 0.0041564 | 0.8875841 | 0.8875837 | 0.1168090 | 0.1417730 | 51427 |
1 | 707522 | rs371890604 | G | C | -0.0019126 | 0.0046617 | 0.6815959 | 0.6815943 | 0.0982930 | 0.1293930 | 51427 |
1 | 717587 | rs144155419 | G | A | -0.0042784 | 0.0112697 | 0.7042146 | 0.7042126 | 0.0154808 | 0.0045926 | 51427 |
1 | 723329 | rs189787166 | A | T | 0.0412768 | 0.0320295 | 0.1975040 | 0.1974982 | 0.0017973 | 0.0003994 | 51427 |
1 | 730087 | rs148120343 | T | C | -0.0000086 | 0.0057882 | 0.9988170 | 0.9988173 | 0.0570822 | 0.0127796 | 51427 |
1 | 731718 | rs142557973 | T | C | 0.0007261 | 0.0039498 | 0.8541511 | 0.8541501 | 0.1225210 | 0.1543530 | 51427 |
1 | 732032 | rs61770163 | A | C | 0.0008249 | 0.0042104 | 0.8446701 | 0.8446691 | 0.1216510 | 0.1555510 | 51427 |
1 | 734349 | rs141242758 | T | C | 0.0006811 | 0.0039519 | 0.8631719 | 0.8631714 | 0.1217650 | 0.1525560 | 51427 |
1 | 740284 | rs61770167 | C | T | 0.0110808 | 0.0172707 | 0.5211383 | 0.5211360 | 0.0062329 | 0.0023962 | 51427 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | 0.0003383 | 0.0046468 | 0.9419640 | 0.9419640 | 0.0542488 | 0.0309934 | 51427 |
23 | 154923374 | rs111332691 | T | A | 0.0055748 | 0.0050336 | 0.2680742 | 0.2680681 | 0.0445389 | 0.0116556 | 51427 |
23 | 154925045 | rs509981 | C | T | -0.0005779 | 0.0024198 | 0.8112360 | 0.8112345 | 0.2434190 | 0.3634440 | 51427 |
23 | 154925895 | rs538470 | C | T | -0.0003951 | 0.0024719 | 0.8730240 | 0.8730233 | 0.2401390 | 0.3634440 | 51427 |
23 | 154927581 | rs644138 | G | A | -0.0004641 | 0.0022761 | 0.8384360 | 0.8384350 | 0.2981050 | 0.4635760 | 51427 |
23 | 154929412 | rs557132 | C | T | -0.0005200 | 0.0024207 | 0.8299211 | 0.8299196 | 0.2432580 | 0.3568210 | 51427 |
23 | 154929637 | rs35185538 | CT | C | 0.0012889 | 0.0025222 | 0.6093475 | 0.6093440 | 0.2278210 | 0.3011920 | 51427 |
23 | 154929952 | rs4012982 | CAA | C | -0.0004727 | 0.0025468 | 0.8527580 | 0.8527573 | 0.2374290 | 0.3165560 | 51427 |
23 | 154930230 | rs781880 | A | G | -0.0004330 | 0.0024196 | 0.8579609 | 0.8579605 | 0.2438260 | 0.3618540 | 51427 |
23 | 154930487 | rs781879 | T | A | 0.0140646 | 0.0084135 | 0.0945954 | 0.0945889 | 0.0189843 | 0.1263580 | 51427 |
1 692794 rs530212009 CA C . PASS AF=0.1121 ES:SE:LP:AF:SS:ID 0.0020087:0.00437383:0.189732:0.1121:51427:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.116809 ES:SE:LP:AF:SS:ID -0.00058756:0.00415641:0.0517905:0.116809:51427:rs12238997
1 707522 rs371890604 G C . PASS AF=0.098293 ES:SE:LP:AF:SS:ID -0.00191263:0.00466167:0.166473:0.098293:51427:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0154808 ES:SE:LP:AF:SS:ID -0.00427843:0.0112697:0.152295:0.0154808:51427:rs144155419
1 723329 rs189787166 A T . PASS AF=0.00179726 ES:SE:LP:AF:SS:ID 0.0412768:0.0320295:0.704424:0.00179726:51427:rs189787166
1 730087 rs148120343 T C . PASS AF=0.0570822 ES:SE:LP:AF:SS:ID -8.5802e-06:0.00578822:0.000514075:0.0570822:51427:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122521 ES:SE:LP:AF:SS:ID 0.000726066:0.00394975:0.0684653:0.122521:51427:rs58276399
1 732032 rs61770163 A C . PASS AF=0.121651 ES:SE:LP:AF:SS:ID 0.000824927:0.00421043:0.0733129:0.121651:51427:rs61770163
1 734349 rs141242758 T C . PASS AF=0.121765 ES:SE:LP:AF:SS:ID 0.000681063:0.00395189:0.0639027:0.121765:51427:rs141242758
1 740284 rs61770167 C T . PASS AF=0.0062329 ES:SE:LP:AF:SS:ID 0.0110808:0.0172707:0.283047:0.0062329:51427:rs61770167
1 742813 rs112573343 C T . PASS AF=0.00176649 ES:SE:LP:AF:SS:ID 0.0255762:0.0358885:0.322337:0.00176649:51427:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.868613 ES:SE:LP:AF:SS:ID 0.00129549:0.00389028:0.131279:0.868613:51427:rs529266287
1 750230 rs190826124 G C . PASS AF=0.00158492 ES:SE:LP:AF:SS:ID -0.0631103:0.0349053:1.15116:0.00158492:51427:rs190826124
1 751343 rs28544273 T A . PASS AF=0.123957 ES:SE:LP:AF:SS:ID -0.0014259:0.00385387:0.147892:0.123957:51427:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.143385 ES:SE:LP:AF:SS:ID 0.0010106:0.00382363:0.101523:0.143385:51427:rs200141114
1 751756 rs28527770 T C . PASS AF=0.124126 ES:SE:LP:AF:SS:ID -0.00155212:0.00384747:0.163267:0.124126:51427:rs28527770
1 753405 rs3115860 C A . PASS AF=0.869933 ES:SE:LP:AF:SS:ID -0.00028435:0.00374973:0.0270787:0.869933:51427:rs3115860
1 753425 rs3131970 T C . PASS AF=0.874426 ES:SE:LP:AF:SS:ID 0.00144699:0.00380933:0.152393:0.874426:51427:rs3131970
1 753541 rs2073813 G A . PASS AF=0.129659 ES:SE:LP:AF:SS:ID -0.000216658:0.00375897:0.0204348:0.129659:51427:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0369164 ES:SE:LP:AF:SS:ID 0.00422137:0.00677037:0.27331:0.0369164:51427:rs12184325
1 754182 rs3131969 A G . PASS AF=0.869554 ES:SE:LP:AF:SS:ID -0.000143716:0.00374623:0.0134979:0.869554:51427:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869648 ES:SE:LP:AF:SS:ID -0.000130527:0.00374818:0.0122354:0.869648:51427:rs3131968
1 754334 rs3131967 T C . PASS AF=0.86957 ES:SE:LP:AF:SS:ID -0.000180863:0.00374622:0.0170534:0.86957:51427:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00531261 ES:SE:LP:AF:SS:ID -0.0251674:0.0187759:0.744445:0.00531261:51427:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00527727 ES:SE:LP:AF:SS:ID -0.0256005:0.0188252:0.759785:0.00527727:51427:rs142682604
1 755435 rs184270342 T G . PASS AF=0.0057746 ES:SE:LP:AF:SS:ID -0.0220994:0.0183606:0.640665:0.0057746:51427:rs184270342
1 755890 rs3115858 A T . PASS AF=0.869706 ES:SE:LP:AF:SS:ID -6.12056e-05:0.00374057:0.00570705:0.869706:51427:rs3115858
1 756434 rs61768170 G C . PASS AF=0.12702 ES:SE:LP:AF:SS:ID -0.00148498:0.00381497:0.156711:0.12702:51427:rs61768170
1 756604 rs3131962 A G . PASS AF=0.869213 ES:SE:LP:AF:SS:ID -7.35832e-05:0.00373074:0.0068884:0.869213:51427:rs3131962
1 757640 rs3115853 G A . PASS AF=0.868449 ES:SE:LP:AF:SS:ID -0.000342349:0.00372713:0.0330069:0.868449:51427:rs3115853
1 757734 rs4951929 C T . PASS AF=0.869419 ES:SE:LP:AF:SS:ID -0.000182214:0.00373485:0.0172364:0.869419:51427:rs4951929
1 757936 rs4951862 C A . PASS AF=0.869426 ES:SE:LP:AF:SS:ID -0.000180552:0.00373509:0.0170751:0.869426:51427:rs4951862
1 758144 rs3131956 A G . PASS AF=0.869437 ES:SE:LP:AF:SS:ID -0.000179853:0.00373527:0.0170069:0.869437:51427:rs3131956
1 758626 rs3131954 C T . PASS AF=0.869848 ES:SE:LP:AF:SS:ID 7.01467e-05:0.00374399:0.00654084:0.869848:51427:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0999077 ES:SE:LP:AF:SS:ID -0.000712133:0.00434175:0.0606225:0.0999077:51427:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00659027 ES:SE:LP:AF:SS:ID -0.0198472:0.0166767:0.630773:0.00659027:51427:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.87358 ES:SE:LP:AF:SS:ID 0.00160091:0.00379807:0.171735:0.87358:51427:rs3115851
1 761732 rs2286139 C T . PASS AF=0.86295 ES:SE:LP:AF:SS:ID 0.000287686:0.00372612:0.0275852:0.86295:51427:rs2286139
1 761752 rs1057213 C T . PASS AF=0.868667 ES:SE:LP:AF:SS:ID 1.8797e-05:0.00376266:0.00173456:0.868667:51427:rs1057213
1 762273 rs3115849 G A . PASS AF=0.8652 ES:SE:LP:AF:SS:ID 0.000928301:0.003761:0.0941793:0.8652:51427:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0992889 ES:SE:LP:AF:SS:ID -0.0029072:0.00451382:0.284385:0.0992889:51427:rs12095200
1 762589 rs3115848 G C . PASS AF=0.870459 ES:SE:LP:AF:SS:ID 0.00216565:0.00380326:0.24483:0.870459:51427:rs3115848
1 762592 rs3131950 C G . PASS AF=0.870459 ES:SE:LP:AF:SS:ID 0.00216569:0.00380326:0.244837:0.870459:51427:rs3131950
1 762601 rs3131949 T C . PASS AF=0.870456 ES:SE:LP:AF:SS:ID 0.00216448:0.00380328:0.24467:0.870456:51427:rs3131949
1 762632 rs3131948 T A . PASS AF=0.870829 ES:SE:LP:AF:SS:ID 0.00218851:0.00380544:0.247779:0.870829:51427:rs3131948
1 764191 rs7515915 T G . PASS AF=0.126636 ES:SE:LP:AF:SS:ID -0.00168534:0.00380969:0.181633:0.126636:51427:rs7515915
1 766007 rs61768174 A C . PASS AF=0.106247 ES:SE:LP:AF:SS:ID 0.000888846:0.00414882:0.0807336:0.106247:51427:rs61768174
1 766105 rs2519015 T A . PASS AF=0.854084 ES:SE:LP:AF:SS:ID 0.000460876:0.00372573:0.0450092:0.854084:51427:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00168817 ES:SE:LP:AF:SS:ID 0.0410374:0.032312:0.690204:0.00168817:51427:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.836377 ES:SE:LP:AF:SS:ID -0.00173193:0.00364873:0.197208:0.836377:51427:rs376645387