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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-22617_8139/ukb-d-22617_8139.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-22617_8139/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 15:00:42 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22617_8139/ukb-d-22617_8139.vcf.gz ...
Read summary statistics for 9637881 SNPs.
Dropped 7251 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, 1274836 SNPs remain.
After merging with regression SNP LD, 1274836 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0017 (0.0051)
Lambda GC: 1.0002
Mean Chi^2: 1.005
Intercept: 1.0081 (0.0062)
Ratio: 1.6035 (1.2342)
Analysis finished at Mon Nov 25 15:02:10 2019
Total time elapsed: 1.0m:27.7s
{
"af_correlation": 0.9397,
"inflation_factor": 1.0057,
"mean_EFFECT": 3.2932e-06,
"n": 91149,
"n_snps": 9637881,
"n_clumped_hits": 0,
"n_p_sig": 0,
"n_mono": 0,
"n_ns": 1059979,
"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": 192220,
"n_est": 91154.7493,
"ratio_se_n": 1,
"mean_diff": 0,
"ratio_diff": 27.3133,
"sd_y_est1": 0.1156,
"sd_y_est2": 0.1156,
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1274836,
"ldsc_nsnp_merge_regression_ld": 1274836,
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": 1.0081,
"ldsc_intercept_se": 0.0062,
"ldsc_lambda_gc": 1.0002,
"ldsc_mean_chisq": 1.005,
"ldsc_ratio": 1.62
}
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 | 9631178 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 98 | 0 | 46924 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 29623 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.079591e+00 | 6.175378e+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 | 7.873411e+07 | 5.611670e+07 | 3.02000e+02 | 3.242810e+07 | 6.961581e+07 | 1.147434e+08 | 2.492297e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.300000e-06 | 1.210500e-03 | -1.07684e-02 | -5.885000e-04 | -5.600000e-06 | 5.752000e-04 | 1.451560e-02 | ▁▂▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.049700e-03 | 5.920000e-04 | 4.47600e-04 | 5.925000e-04 | 7.878000e-04 | 1.340900e-03 | 3.309200e-03 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.991745e-01 | 2.891568e-01 | 1.00000e-07 | 2.489218e-01 | 4.987846e-01 | 7.497975e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.991728e-01 | 2.891579e-01 | 1.00000e-07 | 2.489195e-01 | 4.987837e-01 | 7.497971e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.631342e-01 | 2.628494e-01 | 1.01626e-02 | 4.526740e-02 | 1.616490e-01 | 4.185320e-01 | 9.898370e-01 | ▇▂▂▁▁ |
numeric | AF_reference | 192220 | 0.9800558 | NA | NA | NA | NA | NA | 2.625882e-01 | 2.536538e-01 | 0.00000e+00 | 5.151760e-02 | 1.767170e-01 | 4.139380e-01 | 1.000000e+00 | ▇▃▂▁▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.114900e+04 | 0.000000e+00 | 9.11490e+04 | 9.114900e+04 | 9.114900e+04 | 9.114900e+04 | 9.114900e+04 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | -0.0008862 | 0.0009468 | 0.3492714 | 0.3492676 | 0.1114870 | 0.1894970 | 91149 |
1 | 693731 | rs12238997 | A | G | -0.0015955 | 0.0008967 | 0.0751813 | 0.0751783 | 0.1164590 | 0.1417730 | 91149 |
1 | 707522 | rs371890604 | G | C | -0.0009775 | 0.0010076 | 0.3320137 | 0.3320096 | 0.0978765 | 0.1293930 | 91149 |
1 | 717587 | rs144155419 | G | A | -0.0017159 | 0.0024020 | 0.4750015 | 0.4749998 | 0.0157837 | 0.0045926 | 91149 |
1 | 730087 | rs148120343 | T | C | -0.0003700 | 0.0012429 | 0.7659105 | 0.7659097 | 0.0569973 | 0.0127796 | 91149 |
1 | 731718 | rs142557973 | T | C | -0.0015017 | 0.0008509 | 0.0775818 | 0.0775775 | 0.1223590 | 0.1543530 | 91149 |
1 | 732032 | rs61770163 | A | C | -0.0012936 | 0.0009072 | 0.1538952 | 0.1538924 | 0.1220470 | 0.1555510 | 91149 |
1 | 734349 | rs141242758 | T | C | -0.0015542 | 0.0008515 | 0.0679798 | 0.0679758 | 0.1215880 | 0.1525560 | 91149 |
1 | 749963 | rs529266287 | T | TAA | 0.0014870 | 0.0008376 | 0.0758595 | 0.0758578 | 0.8689170 | 0.7641770 | 91149 |
1 | 751343 | rs28544273 | T | A | -0.0013986 | 0.0008304 | 0.0921467 | 0.0921442 | 0.1236990 | 0.2426120 | 91149 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | 0.0002320 | 0.0009961 | 0.8158229 | 0.8158230 | 0.0552869 | 0.0309934 | 91149 |
23 | 154923374 | rs111332691 | T | A | 0.0006643 | 0.0010840 | 0.5399866 | 0.5399855 | 0.0448387 | 0.0116556 | 91149 |
23 | 154925045 | rs509981 | C | T | -0.0002351 | 0.0005224 | 0.6527246 | 0.6527236 | 0.2444670 | 0.3634440 | 91149 |
23 | 154925895 | rs538470 | C | T | -0.0002627 | 0.0005341 | 0.6228493 | 0.6228476 | 0.2409490 | 0.3634440 | 91149 |
23 | 154927581 | rs644138 | G | A | -0.0001516 | 0.0004913 | 0.7576280 | 0.7576281 | 0.3001640 | 0.4635760 | 91149 |
23 | 154929412 | rs557132 | C | T | -0.0002272 | 0.0005226 | 0.6637125 | 0.6637104 | 0.2443160 | 0.3568210 | 91149 |
23 | 154929637 | rs35185538 | CT | C | 0.0000031 | 0.0005456 | 0.9954780 | 0.9954779 | 0.2286640 | 0.3011920 | 91149 |
23 | 154929952 | rs4012982 | CAA | C | -0.0001963 | 0.0005500 | 0.7211390 | 0.7211384 | 0.2382530 | 0.3165560 | 91149 |
23 | 154930230 | rs781880 | A | G | -0.0002298 | 0.0005224 | 0.6599424 | 0.6599417 | 0.2447660 | 0.3618540 | 91149 |
23 | 154930487 | rs781879 | T | A | -0.0029325 | 0.0017716 | 0.0978723 | 0.0978701 | 0.0196632 | 0.1263580 | 91149 |
1 692794 rs530212009 CA C . PASS AF=0.111487 ES:SE:LP:AF:SS:ID -0.000886171:0.000946753:0.456837:0.111487:91149:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.116459 ES:SE:LP:AF:SS:ID -0.0015955:0.000896663:1.12389:0.116459:91149:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0978765 ES:SE:LP:AF:SS:ID -0.000977495:0.00100765:0.478844:0.0978765:91149:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0157837 ES:SE:LP:AF:SS:ID -0.00171594:0.00240204:0.323305:0.0157837:91149:rs144155419
1 730087 rs148120343 T C . PASS AF=0.0569973 ES:SE:LP:AF:SS:ID -0.000370036:0.00124286:0.115822:0.0569973:91149:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122359 ES:SE:LP:AF:SS:ID -0.00150173:0.000850878:1.11024:0.122359:91149:rs58276399
1 732032 rs61770163 A C . PASS AF=0.122047 ES:SE:LP:AF:SS:ID -0.00129365:0.000907241:0.812775:0.122047:91149:rs61770163
1 734349 rs141242758 T C . PASS AF=0.121588 ES:SE:LP:AF:SS:ID -0.00155417:0.000851522:1.16762:0.121588:91149:rs141242758
1 749963 rs529266287 T TAA . PASS AF=0.868917 ES:SE:LP:AF:SS:ID 0.00148697:0.000837615:1.11999:0.868917:91149:rs529266287
1 751343 rs28544273 T A . PASS AF=0.123699 ES:SE:LP:AF:SS:ID -0.00139861:0.000830433:1.03552:0.123699:91149:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.143202 ES:SE:LP:AF:SS:ID -0.00188591:0.000822125:1.66163:0.143202:91149:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123834 ES:SE:LP:AF:SS:ID -0.00138004:0.000829232:1.01742:0.123834:91149:rs28527770
1 753405 rs3115860 C A . PASS AF=0.869892 ES:SE:LP:AF:SS:ID 0.00142294:0.000808005:1.10661:0.869892:91149:rs3115860
1 753425 rs3131970 T C . PASS AF=0.874553 ES:SE:LP:AF:SS:ID 0.00138674:0.00082111:1.03977:0.874553:91149:rs3131970
1 753541 rs2073813 G A . PASS AF=0.129529 ES:SE:LP:AF:SS:ID -0.00135556:0.000810542:1.02481:0.129529:91149:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0358205 ES:SE:LP:AF:SS:ID -0.00082594:0.0014808:0.238821:0.0358205:91149:rs12184325
1 754182 rs3131969 A G . PASS AF=0.869539 ES:SE:LP:AF:SS:ID 0.00140271:0.00080733:1.08456:0.869539:91149:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869616 ES:SE:LP:AF:SS:ID 0.00144715:0.000807682:1.13561:0.869616:91149:rs3131968
1 754334 rs3131967 T C . PASS AF=0.869535 ES:SE:LP:AF:SS:ID 0.00140395:0.000807297:1.08605:0.869535:91149:rs3131967
1 755890 rs3115858 A T . PASS AF=0.86952 ES:SE:LP:AF:SS:ID 0.00142266:0.000805633:1.11116:0.86952:91149:rs3115858
1 756434 rs61768170 G C . PASS AF=0.126911 ES:SE:LP:AF:SS:ID -0.00142026:0.000822411:1.07479:0.126911:91149:rs61768170
1 756604 rs3131962 A G . PASS AF=0.86905 ES:SE:LP:AF:SS:ID 0.00144372:0.000803547:1.14033:0.86905:91149:rs3131962
1 757640 rs3115853 G A . PASS AF=0.868436 ES:SE:LP:AF:SS:ID 0.00140849:0.000803038:1.09995:0.868436:91149:rs3115853
1 757734 rs4951929 C T . PASS AF=0.869199 ES:SE:LP:AF:SS:ID 0.00142715:0.000804276:1.11924:0.869199:91149:rs4951929
1 757936 rs4951862 C A . PASS AF=0.869205 ES:SE:LP:AF:SS:ID 0.0014265:0.000804328:1.11836:0.869205:91149:rs4951862
1 758144 rs3131956 A G . PASS AF=0.869207 ES:SE:LP:AF:SS:ID 0.00142647:0.000804335:1.11832:0.869207:91149:rs3131956
1 758626 rs3131954 C T . PASS AF=0.869687 ES:SE:LP:AF:SS:ID 0.00142435:0.000806488:1.11137:0.869687:91149:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0991787 ES:SE:LP:AF:SS:ID -0.0012964:0.000938561:0.776761:0.0991787:91149:rs10157329
1 759837 rs3115851 T A . PASS AF=0.873682 ES:SE:LP:AF:SS:ID 0.00149377:0.000818431:1.16762:0.873682:91149:rs3115851
1 761732 rs2286139 C T . PASS AF=0.863058 ES:SE:LP:AF:SS:ID 0.00133399:0.000802817:1.01508:0.863058:91149:rs2286139
1 761752 rs1057213 C T . PASS AF=0.868472 ES:SE:LP:AF:SS:ID 0.00146599:0.00081078:1.15125:0.868472:91149:rs1057213
1 762273 rs3115849 G A . PASS AF=0.865369 ES:SE:LP:AF:SS:ID 0.00132302:0.000810935:0.988036:0.865369:91149:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0995228 ES:SE:LP:AF:SS:ID -0.00174087:0.000970534:1.13751:0.0995228:91149:rs12095200
1 762589 rs3115848 G C . PASS AF=0.870657 ES:SE:LP:AF:SS:ID 0.00146916:0.000820171:1.13519:0.870657:91149:rs3115848
1 762592 rs3131950 C G . PASS AF=0.870657 ES:SE:LP:AF:SS:ID 0.00146916:0.00082017:1.13519:0.870657:91149:rs3131950
1 762601 rs3131949 T C . PASS AF=0.870654 ES:SE:LP:AF:SS:ID 0.00146935:0.000820173:1.1354:0.870654:91149:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871019 ES:SE:LP:AF:SS:ID 0.00149681:0.000820553:1.16664:0.871019:91149:rs3131948
1 764191 rs7515915 T G . PASS AF=0.126515 ES:SE:LP:AF:SS:ID -0.00138774:0.000821468:1.04021:0.126515:91149:rs7515915
1 766007 rs61768174 A C . PASS AF=0.106037 ES:SE:LP:AF:SS:ID -0.00139621:0.000892944:0.928431:0.106037:91149:rs61768174
1 766105 rs2519015 T A . PASS AF=0.85438 ES:SE:LP:AF:SS:ID 0.00114855:0.000802514:0.817075:0.85438:91149:rs2519015
1 768116 rs376645387 A AGTTTT . PASS AF=0.839153 ES:SE:LP:AF:SS:ID 1.64329e-05:0.000792927:0.00724065:0.839153:91149:rs376645387
1 768253 rs2977608 A C . PASS AF=0.763195 ES:SE:LP:AF:SS:ID 0.000522967:0.000637553:0.385036:0.763195:91149:rs2977608
1 768448 rs12562034 G A . PASS AF=0.105092 ES:SE:LP:AF:SS:ID 0.000710288:0.000878554:0.377973:0.105092:91149:rs12562034
1 769138 rs59306077 CAT C . PASS AF=0.129904 ES:SE:LP:AF:SS:ID -0.00129361:0.000809996:0.957598:0.129904:91149:rs762168062
1 769223 rs60320384 C G . PASS AF=0.129636 ES:SE:LP:AF:SS:ID -0.0013003:0.00080893:0.966721:0.129636:91149:rs60320384
1 769963 rs7518545 G A . PASS AF=0.104365 ES:SE:LP:AF:SS:ID 0.000661967:0.000885375:0.342311:0.104365:91149:rs7518545
1 770886 rs371458725 G A . PASS AF=0.103379 ES:SE:LP:AF:SS:ID 0.000662331:0.000893032:0.338858:0.103379:91149:rs371458725
1 771410 rs2519006 C T . PASS AF=0.829291 ES:SE:LP:AF:SS:ID 0.000772534:0.000789219:0.484587:0.829291:91149:rs2519006
1 771823 rs2977605 T C . PASS AF=0.869067 ES:SE:LP:AF:SS:ID 0.00142432:0.000805028:1.11435:0.869067:91149:rs2977605
1 771967 rs59066358 G A . PASS AF=0.129741 ES:SE:LP:AF:SS:ID -0.00136422:0.000808487:1.03842:0.129741:91149:rs59066358