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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-22601_31313060/ukb-d-22601_31313060.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-22601_31313060/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 15:01:33 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22601_31313060/ukb-d-22601_31313060.vcf.gz ...
Read summary statistics for 9408950 SNPs.
Dropped 6916 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, 1271753 SNPs remain.
After merging with regression SNP LD, 1271753 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0051 (0.0049)
Lambda GC: 0.9938
Mean Chi^2: 0.9993
Intercept: 1.0085 (0.006)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Nov 25 15:03:30 2019
Total time elapsed: 1.0m:56.35s
{
"af_correlation": 0.9383,
"inflation_factor": 0.9998,
"mean_EFFECT": -1.3299e-06,
"n": 89866,
"n_snps": 9408950,
"n_clumped_hits": 1,
"n_p_sig": 3,
"n_mono": 0,
"n_ns": 1044493,
"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": 188704,
"n_est": 89884.2913,
"ratio_se_n": 1.0001,
"mean_diff": -9.6805e-06,
"ratio_diff": 7.8227,
"sd_y_est1": 0.1086,
"sd_y_est2": 0.1086,
"r2_sum1": 4.0686e-06,
"r2_sum2": 0.0003,
"r2_sum3": 0.0003,
"r2_sum4": 0.0003,
"ldsc_nsnp_merge_refpanel_ld": 1271753,
"ldsc_nsnp_merge_regression_ld": 1271753,
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": 1.0085,
"ldsc_intercept_se": 0.006,
"ldsc_lambda_gc": 0.9938,
"ldsc_mean_chisq": 0.9993,
"ldsc_ratio": -12.1429
}
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 | 9402569 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 98 | 0 | 46057 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 29292 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.081077e+00 | 6.173807e+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 | 7.869328e+07 | 5.611290e+07 | 3.02000e+02 | 3.240928e+07 | 6.955594e+07 | 1.147135e+08 | 2.492297e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -1.300000e-06 | 1.084200e-03 | -9.40310e-03 | -5.462000e-04 | -4.500000e-06 | 5.317000e-04 | 1.258010e-02 | ▁▂▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.555000e-04 | 5.124000e-04 | 4.23600e-04 | 5.580000e-04 | 7.311000e-04 | 1.210200e-03 | 2.888200e-03 | ▇▂▂▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.995097e-01 | 2.890401e-01 | 0.00000e+00 | 2.488158e-01 | 5.000345e-01 | 7.500427e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.995080e-01 | 2.890412e-01 | 0.00000e+00 | 2.488132e-01 | 5.000326e-01 | 7.500423e-01 | 9.999999e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.688042e-01 | 2.626205e-01 | 1.16713e-02 | 5.003720e-02 | 1.697290e-01 | 4.268450e-01 | 9.883290e-01 | ▇▂▂▁▁ |
numeric | AF_reference | 188704 | 0.9799442 | NA | NA | NA | NA | NA | 2.681116e-01 | 2.534133e-01 | 0.00000e+00 | 5.750800e-02 | 1.843050e-01 | 4.213260e-01 | 1.000000e+00 | ▇▃▂▂▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.986600e+04 | 0.000000e+00 | 8.98660e+04 | 8.986600e+04 | 8.986600e+04 | 8.986600e+04 | 8.986600e+04 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | 0.0013004 | 0.0008948 | 0.1461618 | 0.1461577 | 0.1114870 | 0.1894970 | 89866 |
1 | 693731 | rs12238997 | A | G | 0.0012176 | 0.0008477 | 0.1508780 | 0.1508748 | 0.1164980 | 0.1417730 | 89866 |
1 | 707522 | rs371890604 | G | C | 0.0012192 | 0.0009530 | 0.2007779 | 0.2007750 | 0.0978285 | 0.1293930 | 89866 |
1 | 717587 | rs144155419 | G | A | -0.0000277 | 0.0022699 | 0.9902730 | 0.9902728 | 0.0158090 | 0.0045926 | 89866 |
1 | 730087 | rs148120343 | T | C | 0.0029188 | 0.0011754 | 0.0130188 | 0.0130173 | 0.0569661 | 0.0127796 | 89866 |
1 | 731718 | rs142557973 | T | C | 0.0013558 | 0.0008044 | 0.0918861 | 0.0918844 | 0.1223780 | 0.1543530 | 89866 |
1 | 732032 | rs61770163 | A | C | 0.0008598 | 0.0008576 | 0.3160887 | 0.3160864 | 0.1220530 | 0.1555510 | 89866 |
1 | 734349 | rs141242758 | T | C | 0.0013414 | 0.0008050 | 0.0956401 | 0.0956367 | 0.1216170 | 0.1525560 | 89866 |
1 | 749963 | rs529266287 | T | TAA | -0.0010756 | 0.0007920 | 0.1744271 | 0.1744217 | 0.8689590 | 0.7641770 | 89866 |
1 | 751343 | rs28544273 | T | A | 0.0011346 | 0.0007851 | 0.1484240 | 0.1484202 | 0.1236780 | 0.2426120 | 89866 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | 0.0021448 | 0.0009415 | 0.0227279 | 0.0227259 | 0.0553576 | 0.0309934 | 89866 |
23 | 154923374 | rs111332691 | T | A | 0.0012011 | 0.0010250 | 0.2412882 | 0.2412839 | 0.0449113 | 0.0116556 | 89866 |
23 | 154925045 | rs509981 | C | T | 0.0004002 | 0.0004943 | 0.4182366 | 0.4182344 | 0.2444280 | 0.3634440 | 89866 |
23 | 154925895 | rs538470 | C | T | 0.0004117 | 0.0005055 | 0.4153527 | 0.4153510 | 0.2408760 | 0.3634440 | 89866 |
23 | 154927581 | rs644138 | G | A | 0.0008658 | 0.0004650 | 0.0626109 | 0.0626076 | 0.3001910 | 0.4635760 | 89866 |
23 | 154929412 | rs557132 | C | T | 0.0004055 | 0.0004945 | 0.4122323 | 0.4122292 | 0.2442750 | 0.3568210 | 89866 |
23 | 154929637 | rs35185538 | CT | C | 0.0001277 | 0.0005164 | 0.8046600 | 0.8046593 | 0.2286930 | 0.3011920 | 89866 |
23 | 154929952 | rs4012982 | CAA | C | 0.0004676 | 0.0005204 | 0.3688663 | 0.3688634 | 0.2381980 | 0.3165560 | 89866 |
23 | 154930230 | rs781880 | A | G | 0.0004077 | 0.0004943 | 0.4095567 | 0.4095558 | 0.2447120 | 0.3618540 | 89866 |
23 | 154930487 | rs781879 | T | A | 0.0035587 | 0.0016768 | 0.0338189 | 0.0338164 | 0.0196791 | 0.1263580 | 89866 |
1 692794 rs530212009 CA C . PASS AF=0.111487 ES:SE:LP:AF:SS:ID 0.00130043:0.00089485:0.835166:0.111487:89866:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.116498 ES:SE:LP:AF:SS:ID 0.00121763:0.000847667:0.821374:0.116498:89866:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0978285 ES:SE:LP:AF:SS:ID 0.00121917:0.000952963:0.697284:0.0978285:89866:rs371890604
1 717587 rs144155419 G A . PASS AF=0.015809 ES:SE:LP:AF:SS:ID -2.76739e-05:0.00226992:0.00424506:0.015809:89866:rs144155419
1 730087 rs148120343 T C . PASS AF=0.0569661 ES:SE:LP:AF:SS:ID 0.00291884:0.00117539:1.88543:0.0569661:89866:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122378 ES:SE:LP:AF:SS:ID 0.00135583:0.000804389:1.03675:0.122378:89866:rs58276399
1 732032 rs61770163 A C . PASS AF=0.122053 ES:SE:LP:AF:SS:ID 0.00085975:0.000857578:0.500191:0.122053:89866:rs61770163
1 734349 rs141242758 T C . PASS AF=0.121617 ES:SE:LP:AF:SS:ID 0.00134142:0.000804988:1.01936:0.121617:89866:rs141242758
1 749963 rs529266287 T TAA . PASS AF=0.868959 ES:SE:LP:AF:SS:ID -0.00107563:0.000791992:0.758386:0.868959:89866:rs529266287
1 751343 rs28544273 T A . PASS AF=0.123678 ES:SE:LP:AF:SS:ID 0.00113464:0.000785145:0.828496:0.123678:89866:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.143191 ES:SE:LP:AF:SS:ID 0.00172725:0.000777326:1.58033:0.143191:89866:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123813 ES:SE:LP:AF:SS:ID 0.00116948:0.000784012:0.867123:0.123813:89866:rs28527770
1 753405 rs3115860 C A . PASS AF=0.869927 ES:SE:LP:AF:SS:ID -0.00105119:0.000763909:0.772612:0.869927:89866:rs3115860
1 753425 rs3131970 T C . PASS AF=0.87461 ES:SE:LP:AF:SS:ID -0.00102456:0.000776364:0.728291:0.87461:89866:rs3131970
1 753541 rs2073813 G A . PASS AF=0.12951 ES:SE:LP:AF:SS:ID 0.00112923:0.000766243:0.852144:0.12951:89866:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0357365 ES:SE:LP:AF:SS:ID -0.0013106:0.00140186:0.456127:0.0357365:89866:rs12184325
1 754182 rs3131969 A G . PASS AF=0.869574 ES:SE:LP:AF:SS:ID -0.00101708:0.000763237:0.738335:0.869574:89866:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869652 ES:SE:LP:AF:SS:ID -0.00097764:0.000763577:0.698042:0.869652:89866:rs3131968
1 754334 rs3131967 T C . PASS AF=0.86957 ES:SE:LP:AF:SS:ID -0.00101501:0.000763206:0.736257:0.86957:89866:rs3131967
1 755890 rs3115858 A T . PASS AF=0.869566 ES:SE:LP:AF:SS:ID -0.00108846:0.000761692:0.815292:0.869566:89866:rs3115858
1 756434 rs61768170 G C . PASS AF=0.126879 ES:SE:LP:AF:SS:ID 0.00115149:0.000777567:0.858115:0.126879:89866:rs61768170
1 756604 rs3131962 A G . PASS AF=0.869094 ES:SE:LP:AF:SS:ID -0.00105264:0.000759717:0.780203:0.869094:89866:rs3131962
1 757640 rs3115853 G A . PASS AF=0.868498 ES:SE:LP:AF:SS:ID -0.00103544:0.000759253:0.762846:0.868498:89866:rs3115853
1 757734 rs4951929 C T . PASS AF=0.869245 ES:SE:LP:AF:SS:ID -0.00107177:0.000760411:0.799418:0.869245:89866:rs4951929
1 757936 rs4951862 C A . PASS AF=0.869251 ES:SE:LP:AF:SS:ID -0.00107215:0.000760463:0.799746:0.869251:89866:rs4951862
1 758144 rs3131956 A G . PASS AF=0.869252 ES:SE:LP:AF:SS:ID -0.00107222:0.000760468:0.799809:0.869252:89866:rs3131956
1 758626 rs3131954 C T . PASS AF=0.869724 ES:SE:LP:AF:SS:ID -0.00109497:0.00076249:0.821037:0.869724:89866:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0991203 ES:SE:LP:AF:SS:ID 0.00157758:0.000887659:1.12187:0.0991203:89866:rs10157329
1 759837 rs3115851 T A . PASS AF=0.873732 ES:SE:LP:AF:SS:ID -0.00103367:0.000773818:0.740843:0.873732:89866:rs3115851
1 761732 rs2286139 C T . PASS AF=0.863116 ES:SE:LP:AF:SS:ID -0.000998233:0.000758997:0.724813:0.863116:89866:rs2286139
1 761752 rs1057213 C T . PASS AF=0.868511 ES:SE:LP:AF:SS:ID -0.00110802:0.000766578:0.828718:0.868511:89866:rs1057213
1 762273 rs3115849 G A . PASS AF=0.86539 ES:SE:LP:AF:SS:ID -0.00106164:0.000766691:0.779505:0.86539:89866:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0994301 ES:SE:LP:AF:SS:ID 0.000918393:0.00091812:0.498709:0.0994301:89866:rs12095200
1 762589 rs3115848 G C . PASS AF=0.870696 ES:SE:LP:AF:SS:ID -0.00114557:0.00077551:0.855018:0.870696:89866:rs3115848
1 762592 rs3131950 C G . PASS AF=0.870695 ES:SE:LP:AF:SS:ID -0.00114557:0.00077551:0.855024:0.870695:89866:rs3131950
1 762601 rs3131949 T C . PASS AF=0.870693 ES:SE:LP:AF:SS:ID -0.00114545:0.000775512:0.854891:0.870693:89866:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871061 ES:SE:LP:AF:SS:ID -0.00112026:0.000775879:0.82745:0.871061:89866:rs3131948
1 764191 rs7515915 T G . PASS AF=0.126484 ES:SE:LP:AF:SS:ID 0.00121607:0.000776661:0.930306:0.126484:89866:rs7515915
1 766007 rs61768174 A C . PASS AF=0.106022 ES:SE:LP:AF:SS:ID 0.00154458:0.00084429:1.17175:0.106022:89866:rs61768174
1 766105 rs2519015 T A . PASS AF=0.854451 ES:SE:LP:AF:SS:ID -0.000742197:0.00075882:0.484085:0.854451:89866:rs2519015
1 768116 rs376645387 A AGTTTT . PASS AF=0.839008 ES:SE:LP:AF:SS:ID 0.000124433:0.000749638:0.0613977:0.839008:89866:rs376645387
1 768253 rs2977608 A C . PASS AF=0.76317 ES:SE:LP:AF:SS:ID -0.000650587:0.000602701:0.552239:0.76317:89866:rs2977608
1 768448 rs12562034 G A . PASS AF=0.10519 ES:SE:LP:AF:SS:ID -9.93372e-05:0.00083062:0.043445:0.10519:89866:rs12562034
1 769138 rs59306077 CAT C . PASS AF=0.129876 ES:SE:LP:AF:SS:ID 0.00122229:0.000765781:0.956787:0.129876:89866:rs762168062
1 769223 rs60320384 C G . PASS AF=0.129602 ES:SE:LP:AF:SS:ID 0.00115601:0.000764781:0.883894:0.129602:89866:rs60320384
1 769963 rs7518545 G A . PASS AF=0.104469 ES:SE:LP:AF:SS:ID -0.000175143:0.000837025:0.0786996:0.104469:89866:rs7518545
1 770886 rs371458725 G A . PASS AF=0.103468 ES:SE:LP:AF:SS:ID -0.000208446:0.000844288:0.0942074:0.103468:89866:rs371458725
1 771410 rs2519006 C T . PASS AF=0.829371 ES:SE:LP:AF:SS:ID -0.00115407:0.000746484:0.913259:0.829371:89866:rs2519006
1 771823 rs2977605 T C . PASS AF=0.869112 ES:SE:LP:AF:SS:ID -0.00108192:0.000761092:0.809206:0.869112:89866:rs2977605
1 771967 rs59066358 G A . PASS AF=0.129712 ES:SE:LP:AF:SS:ID 0.00120137:0.000764342:0.935512:0.129712:89866:rs59066358