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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-30810_raw/ukb-d-30810_raw.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-30810_raw/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 14:54:48 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30810_raw/ukb-d-30810_raw.vcf.gz ...
Read summary statistics for 13585253 SNPs.
Dropped 12711 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, 1283502 SNPs remain.
After merging with regression SNP LD, 1283502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1064 (0.0099)
Lambda GC: 1.3905
Mean Chi^2: 1.7272
Intercept: 1.0782 (0.0131)
Ratio: 0.1075 (0.018)
Analysis finished at Mon Nov 25 14:57:06 2019
Total time elapsed: 2.0m:18.1s
{
"af_correlation": 0.9521,
"inflation_factor": 1.25,
"mean_EFFECT": 1.0585e-06,
"n": 314658,
"n_snps": 13585253,
"n_clumped_hits": 160,
"n_p_sig": 22506,
"n_mono": 0,
"n_ns": 1251740,
"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": 568957,
"n_est": 315878.9461,
"ratio_se_n": 1.0019,
"mean_diff": 4.6371e-06,
"ratio_diff": 4.23,
"sd_y_est1": 0.1555,
"sd_y_est2": 0.1559,
"r2_sum1": 0.0011,
"r2_sum2": 0.0475,
"r2_sum3": 0.0473,
"r2_sum4": 0.0473,
"ldsc_nsnp_merge_refpanel_ld": 1283502,
"ldsc_nsnp_merge_regression_ld": 1283502,
"ldsc_observed_scale_h2_beta": 0.1064,
"ldsc_observed_scale_h2_se": 0.0099,
"ldsc_intercept_beta": 1.0782,
"ldsc_intercept_se": 0.0131,
"ldsc_lambda_gc": 1.3905,
"ldsc_mean_chisq": 1.7272,
"ldsc_ratio": 0.1075
}
name | value |
---|---|
af_correlation | FALSE |
inflation_factor | TRUE |
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 |
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 | 13573206 | 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 | 33335 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.051268e+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 | 7.902543e+07 | 5.591517e+07 | 3.02000e+02 | 3.293043e+07 | 7.013909e+07 | 1.148604e+08 | 2.492309e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.100000e-06 | 2.378200e-03 | -4.47000e-02 | -6.982000e-04 | 9.000000e-07 | 7.033000e-04 | 3.339900e-02 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.647400e-03 | 1.589000e-03 | 3.22000e-04 | 4.691000e-04 | 8.643000e-04 | 2.367100e-03 | 8.009700e-03 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.625595e-01 | 2.994731e-01 | 0.00000e+00 | 1.937898e-01 | 4.507804e-01 | 7.217703e-01 | 1.000000e+00 | ▇▆▆▆▆ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.625590e-01 | 2.994734e-01 | 0.00000e+00 | 1.937871e-01 | 4.507830e-01 | 7.217651e-01 | 1.000000e+00 | ▇▆▆▆▆ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.908205e-01 | 2.544080e-01 | 1.00000e-03 | 7.434300e-03 | 6.004500e-02 | 2.953300e-01 | 9.990000e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 568957 | 0.9581195 | NA | NA | NA | NA | NA | 1.963466e-01 | 2.471050e-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 | 3.146580e+05 | 0.000000e+00 | 3.14658e+05 | 3.146580e+05 | 3.146580e+05 | 3.146580e+05 | 3.146580e+05 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | 0.0016247 | 0.0006869 | 0.0180210 | 0.0180222 | 0.1104900 | 0.1894970 | 314658 |
1 | 693731 | rs12238997 | A | G | 0.0012379 | 0.0006489 | 0.0564066 | 0.0564161 | 0.1158100 | 0.1417730 | 314658 |
1 | 707522 | rs371890604 | G | C | 0.0010534 | 0.0007301 | 0.1490799 | 0.1490890 | 0.0971780 | 0.1293930 | 314658 |
1 | 717587 | rs144155419 | G | A | 0.0013826 | 0.0017387 | 0.4265098 | 0.4265019 | 0.0157030 | 0.0045926 | 314658 |
1 | 723329 | rs189787166 | A | T | 0.0097079 | 0.0051391 | 0.0588898 | 0.0588882 | 0.0017313 | 0.0003994 | 314658 |
1 | 730087 | rs148120343 | T | C | 0.0018966 | 0.0009038 | 0.0358641 | 0.0358654 | 0.0564700 | 0.0127796 | 314658 |
1 | 731718 | rs142557973 | T | C | 0.0011296 | 0.0006155 | 0.0664753 | 0.0664722 | 0.1216900 | 0.1543530 | 314658 |
1 | 732032 | rs61770163 | A | C | 0.0011308 | 0.0006569 | 0.0851530 | 0.0851559 | 0.1210400 | 0.1555510 | 314658 |
1 | 734349 | rs141242758 | T | C | 0.0011538 | 0.0006158 | 0.0609818 | 0.0609899 | 0.1209100 | 0.1525560 | 314658 |
1 | 740284 | rs61770167 | C | T | -0.0005419 | 0.0028264 | 0.8479601 | 0.8479608 | 0.0057414 | 0.0023962 | 314658 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | 0.0007123 | 0.0007106 | 0.3161702 | 0.3161678 | 0.056080 | 0.0309934 | 314658 |
23 | 154923374 | rs111332691 | T | A | -0.0007787 | 0.0007776 | 0.3166402 | 0.3166388 | 0.045003 | 0.0116556 | 314658 |
23 | 154925045 | rs509981 | C | T | -0.0006173 | 0.0003754 | 0.1001000 | 0.1000963 | 0.245790 | 0.3634440 | 314658 |
23 | 154925895 | rs538470 | C | T | -0.0005673 | 0.0003840 | 0.1395501 | 0.1395556 | 0.242080 | 0.3634440 | 314658 |
23 | 154927581 | rs644138 | G | A | -0.0003857 | 0.0003531 | 0.2746800 | 0.2746743 | 0.302250 | 0.4635760 | 314658 |
23 | 154929412 | rs557132 | C | T | -0.0006512 | 0.0003755 | 0.0828934 | 0.0828896 | 0.245640 | 0.3568210 | 314658 |
23 | 154929637 | rs35185538 | CT | C | -0.0003563 | 0.0003918 | 0.3631700 | 0.3631662 | 0.230030 | 0.3011920 | 314658 |
23 | 154929952 | rs4012982 | CAA | C | -0.0007192 | 0.0003949 | 0.0685772 | 0.0685810 | 0.239560 | 0.3165560 | 314658 |
23 | 154930230 | rs781880 | A | G | -0.0006504 | 0.0003754 | 0.0832224 | 0.0832211 | 0.246010 | 0.3618540 | 314658 |
23 | 154930487 | rs781879 | T | A | -0.0006076 | 0.0012904 | 0.6377405 | 0.6377284 | 0.019470 | 0.1263580 | 314658 |
1 692794 rs530212009 CA C . PASS AF=0.11049 ES:SE:LP:AF:SS:ID 0.0016247:0.00068693:1.74422:0.11049:314658:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.11581 ES:SE:LP:AF:SS:ID 0.0012379:0.00064886:1.24867:0.11581:314658:rs12238997
1 707522 rs371890604 G C . PASS AF=0.097178 ES:SE:LP:AF:SS:ID 0.0010534:0.00073013:0.826581:0.097178:314658:rs371890604
1 717587 rs144155419 G A . PASS AF=0.015703 ES:SE:LP:AF:SS:ID 0.0013826:0.0017387:0.370071:0.015703:314658:rs144155419
1 723329 rs189787166 A T . PASS AF=0.0017313 ES:SE:LP:AF:SS:ID 0.0097079:0.0051391:1.22996:0.0017313:314658:rs189787166
1 730087 rs148120343 T C . PASS AF=0.05647 ES:SE:LP:AF:SS:ID 0.0018966:0.00090381:1.44534:0.05647:314658:rs148120343
1 731718 rs58276399 T C . PASS AF=0.12169 ES:SE:LP:AF:SS:ID 0.0011296:0.00061551:1.17734:0.12169:314658:rs58276399
1 732032 rs61770163 A C . PASS AF=0.12104 ES:SE:LP:AF:SS:ID 0.0011308:0.00065686:1.0698:0.12104:314658:rs61770163
1 734349 rs141242758 T C . PASS AF=0.12091 ES:SE:LP:AF:SS:ID 0.0011538:0.00061583:1.2148:0.12091:314658:rs141242758
1 740284 rs61770167 C T . PASS AF=0.0057414 ES:SE:LP:AF:SS:ID -0.00054188:0.0028264:0.0716246:0.0057414:314658:rs61770167
1 742813 rs112573343 C T . PASS AF=0.0018554 ES:SE:LP:AF:SS:ID 0.0020237:0.0053605:0.151324:0.0018554:314658:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.86978 ES:SE:LP:AF:SS:ID -0.0011946:0.00060712:1.30888:0.86978:314658:rs529266287
1 750230 rs190826124 G C . PASS AF=0.0015107 ES:SE:LP:AF:SS:ID -0.0069447:0.0055326:0.679023:0.0015107:314658:rs190826124
1 751343 rs28544273 T A . PASS AF=0.12287 ES:SE:LP:AF:SS:ID 0.001181:0.00060133:1.30508:0.12287:314658:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.14268 ES:SE:LP:AF:SS:ID 0.0012797:0.00059425:1.50469:0.14268:314658:rs200141114
1 751756 rs28527770 T C . PASS AF=0.12299 ES:SE:LP:AF:SS:ID 0.0011614:0.00060048:1.27497:0.12299:314658:rs28527770
1 753405 rs3115860 C A . PASS AF=0.87101 ES:SE:LP:AF:SS:ID -0.0011853:0.00058529:1.36799:0.87101:314658:rs3115860
1 753425 rs3131970 T C . PASS AF=0.87554 ES:SE:LP:AF:SS:ID -0.0011852:0.00059485:1.33428:0.87554:314658:rs3131970
1 753541 rs2073813 G A . PASS AF=0.12854 ES:SE:LP:AF:SS:ID 0.0012507:0.0005867:1.48117:0.12854:314658:rs2073813
1 754105 rs12184325 C T . PASS AF=0.036328 ES:SE:LP:AF:SS:ID -0.0016406:0.0010644:0.909248:0.036328:314658:rs12184325
1 754182 rs3131969 A G . PASS AF=0.8706 ES:SE:LP:AF:SS:ID -0.0012298:0.00058466:1.45058:0.8706:314658:rs3131969
1 754192 rs3131968 A G . PASS AF=0.87071 ES:SE:LP:AF:SS:ID -0.0011988:0.00058495:1.39341:0.87071:314658:rs3131968
1 754334 rs3131967 T C . PASS AF=0.8706 ES:SE:LP:AF:SS:ID -0.0012281:0.00058464:1.44766:0.8706:314658:rs3131967
1 754433 rs150578204 G A . PASS AF=0.0050258 ES:SE:LP:AF:SS:ID -0.0005188:0.003003:0.0640697:0.0050258:314658:rs150578204
1 754458 rs142682604 G T . PASS AF=0.0049925 ES:SE:LP:AF:SS:ID -0.00042747:0.0030111:0.0520225:0.0049925:314658:rs142682604
1 755435 rs184270342 T G . PASS AF=0.0055162 ES:SE:LP:AF:SS:ID 0.001389:0.0029238:0.197411:0.0055162:314658:rs184270342
1 755890 rs3115858 A T . PASS AF=0.87069 ES:SE:LP:AF:SS:ID -0.0011743:0.00058367:1.35431:0.87069:314658:rs3115858
1 756434 rs61768170 G C . PASS AF=0.12588 ES:SE:LP:AF:SS:ID 0.0012196:0.00059546:1.39198:0.12588:314658:rs61768170
1 756604 rs3131962 A G . PASS AF=0.87026 ES:SE:LP:AF:SS:ID -0.0011666:0.00058227:1.34568:0.87026:314658:rs3131962
1 757640 rs3115853 G A . PASS AF=0.86954 ES:SE:LP:AF:SS:ID -0.0012387:0.00058175:1.47843:0.86954:314658:rs3115853
1 757734 rs4951929 C T . PASS AF=0.87041 ES:SE:LP:AF:SS:ID -0.0012064:0.00058276:1.41522:0.87041:314658:rs4951929
1 757936 rs4951862 C A . PASS AF=0.87041 ES:SE:LP:AF:SS:ID -0.0012063:0.00058281:1.41495:0.87041:314658:rs4951862
1 758144 rs3131956 A G . PASS AF=0.87042 ES:SE:LP:AF:SS:ID -0.0012113:0.00058282:1.42382:0.87042:314658:rs3131956
1 758626 rs3131954 C T . PASS AF=0.87087 ES:SE:LP:AF:SS:ID -0.0011954:0.0005843:1.38956:0.87087:314658:rs3131954
1 759293 rs10157329 T A . PASS AF=0.098764 ES:SE:LP:AF:SS:ID 0.0014732:0.00067911:1.52203:0.098764:314658:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.0063964 ES:SE:LP:AF:SS:ID 5.7954e-05:0.0026426:0.00766744:0.0063964:314658:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.87471 ES:SE:LP:AF:SS:ID -0.0012579:0.00059287:1.47025:0.87471:314658:rs3115851
1 761732 rs2286139 C T . PASS AF=0.86414 ES:SE:LP:AF:SS:ID -0.0011895:0.00058157:1.38901:0.86414:314658:rs2286139
1 761752 rs1057213 C T . PASS AF=0.86954 ES:SE:LP:AF:SS:ID -0.0013061:0.0005871:1.58324:0.86954:314658:rs1057213
1 762273 rs3115849 G A . PASS AF=0.86649 ES:SE:LP:AF:SS:ID -0.0012827:0.00058722:1.53862:0.86649:314658:rs3115849
1 762485 rs12095200 C A . PASS AF=0.098748 ES:SE:LP:AF:SS:ID 0.0012999:0.0007028:1.19129:0.098748:314658:rs12095200
1 762589 rs3115848 G C . PASS AF=0.87165 ES:SE:LP:AF:SS:ID -0.0012212:0.00059388:1.40054:0.87165:314658:rs3115848
1 762592 rs3131950 C G . PASS AF=0.87165 ES:SE:LP:AF:SS:ID -0.0012211:0.00059388:1.40049:0.87165:314658:rs3131950
1 762601 rs3131949 T C . PASS AF=0.87165 ES:SE:LP:AF:SS:ID -0.0012221:0.00059389:1.40222:0.87165:314658:rs3131949
1 762632 rs3131948 T A . PASS AF=0.87201 ES:SE:LP:AF:SS:ID -0.0012103:0.00059422:1.38023:0.87201:314658:rs3131948
1 764191 rs7515915 T G . PASS AF=0.12549 ES:SE:LP:AF:SS:ID 0.0012296:0.00059465:1.41264:0.12549:314658:rs7515915
1 766007 rs61768174 A C . PASS AF=0.10534 ES:SE:LP:AF:SS:ID 0.0013241:0.0006477:1.38802:0.10534:314658:rs61768174
1 766105 rs2519015 T A . PASS AF=0.85548 ES:SE:LP:AF:SS:ID -0.0011572:0.00058131:1.33235:0.85548:314658:rs2519015
1 767393 rs538667473 A C . PASS AF=0.0016488 ES:SE:LP:AF:SS:ID 0.010058:0.0051535:1.29269:0.0016488:314658:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.83826 ES:SE:LP:AF:SS:ID -0.00033032:0.00057177:0.249137:0.83826:314658:rs376645387