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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-30720_raw/ukb-d-30720_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-30720_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 16:35:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30720_raw/ukb-d-30720_raw.vcf.gz ...
Read summary statistics for 13586046 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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1691 (0.0466)
Lambda GC: 1.5793
Mean Chi^2: 2.3698
Intercept: 1.0956 (0.0135)
Ratio: 0.0698 (0.0098)
Analysis finished at Mon Nov 25 16:37:09 2019
Total time elapsed: 2.0m:2.86s
{
"af_correlation": 0.9521,
"inflation_factor": 1.3506,
"mean_EFFECT": 9.8001e-06,
"n": 344264,
"n_snps": 13586046,
"n_clumped_hits": 196,
"n_p_sig": 40422,
"n_mono": 0,
"n_ns": 1251777,
"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": 569176,
"n_est": 345598.4081,
"ratio_se_n": 1.0019,
"mean_diff": 0.0001,
"ratio_diff": 86.2817,
"sd_y_est1": 0.1619,
"sd_y_est2": 0.1622,
"r2_sum1": 0.0012,
"r2_sum2": 0.0453,
"r2_sum3": 0.0451,
"r2_sum4": 0.045,
"ldsc_nsnp_merge_refpanel_ld": 1283504,
"ldsc_nsnp_merge_regression_ld": 1283504,
"ldsc_observed_scale_h2_beta": 0.1691,
"ldsc_observed_scale_h2_se": 0.0466,
"ldsc_intercept_beta": 1.0956,
"ldsc_intercept_se": 0.0135,
"ldsc_lambda_gc": 1.5793,
"ldsc_mean_chisq": 2.3698,
"ldsc_ratio": 0.0698
}
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 | 13573999 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 57079 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33337 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.051233e+00 | 6.184968e+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 | 7.902571e+07 | 5.591524e+07 | 3.02000e+02 | 3.293108e+07 | 7.013935e+07 | 1.148601e+08 | 2.492309e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.800000e-06 | 2.414200e-03 | -6.25410e-02 | -7.426000e-04 | -4.300000e-06 | 7.312000e-04 | 6.004500e-02 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.639400e-03 | 1.581400e-03 | 3.20800e-04 | 4.668000e-04 | 8.601000e-04 | 2.356000e-03 | 7.988100e-03 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.499440e-01 | 3.031008e-01 | 0.00000e+00 | 1.744299e-01 | 4.331198e-01 | 7.126200e-01 | 1.000000e+00 | ▇▆▅▅▅ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.499435e-01 | 3.031011e-01 | 0.00000e+00 | 1.744250e-01 | 4.331177e-01 | 7.126203e-01 | 9.999999e-01 | ▇▆▅▅▅ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.908090e-01 | 2.544041e-01 | 1.00000e-03 | 7.431400e-03 | 6.003900e-02 | 2.953200e-01 | 9.990000e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 569176 | 0.9581058 | NA | NA | NA | NA | NA | 1.963385e-01 | 2.471023e-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 | 3.442640e+05 | 0.000000e+00 | 3.44264e+05 | 3.442640e+05 | 3.442640e+05 | 3.442640e+05 | 3.442640e+05 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | -0.0000182 | 0.0006834 | 0.9788000 | 0.9788038 | 0.1105100 | 0.1894970 | 344264 |
1 | 693731 | rs12238997 | A | G | 0.0003280 | 0.0006454 | 0.6113403 | 0.6113323 | 0.1157900 | 0.1417730 | 344264 |
1 | 707522 | rs371890604 | G | C | 0.0004811 | 0.0007260 | 0.5075595 | 0.5075551 | 0.0972240 | 0.1293930 | 344264 |
1 | 717587 | rs144155419 | G | A | -0.0012179 | 0.0017330 | 0.4821998 | 0.4821992 | 0.0156620 | 0.0045926 | 344264 |
1 | 723329 | rs189787166 | A | T | -0.0042225 | 0.0051024 | 0.4079200 | 0.4079244 | 0.0017377 | 0.0003994 | 344264 |
1 | 730087 | rs148120343 | T | C | 0.0003467 | 0.0008996 | 0.6999500 | 0.6999427 | 0.0564140 | 0.0127796 | 344264 |
1 | 731718 | rs142557973 | T | C | 0.0004812 | 0.0006122 | 0.4317904 | 0.4317943 | 0.1216800 | 0.1543530 | 344264 |
1 | 732032 | rs61770163 | A | C | 0.0005778 | 0.0006532 | 0.3764497 | 0.3764435 | 0.1210800 | 0.1555510 | 344264 |
1 | 734349 | rs141242758 | T | C | 0.0004861 | 0.0006125 | 0.4274005 | 0.4273998 | 0.1209100 | 0.1525560 | 344264 |
1 | 740284 | rs61770167 | C | T | 0.0008147 | 0.0028092 | 0.7718004 | 0.7717994 | 0.0057570 | 0.0023962 | 344264 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | -0.0003845 | 0.0007074 | 0.5867201 | 0.5867274 | 0.056184 | 0.0309934 | 344264 |
23 | 154923374 | rs111332691 | T | A | 0.0002844 | 0.0007764 | 0.7141295 | 0.7141316 | 0.044880 | 0.0116556 | 344264 |
23 | 154925045 | rs509981 | C | T | 0.0017164 | 0.0003740 | 0.0000045 | 0.0000044 | 0.245660 | 0.3634440 | 344264 |
23 | 154925895 | rs538470 | C | T | 0.0016719 | 0.0003826 | 0.0000124 | 0.0000124 | 0.242000 | 0.3634440 | 344264 |
23 | 154927581 | rs644138 | G | A | 0.0014194 | 0.0003518 | 0.0000545 | 0.0000545 | 0.302230 | 0.4635760 | 344264 |
23 | 154929412 | rs557132 | C | T | 0.0017104 | 0.0003741 | 0.0000048 | 0.0000048 | 0.245520 | 0.3568210 | 344264 |
23 | 154929637 | rs35185538 | CT | C | 0.0015056 | 0.0003905 | 0.0001154 | 0.0001154 | 0.229770 | 0.3011920 | 344264 |
23 | 154929952 | rs4012982 | CAA | C | 0.0016776 | 0.0003935 | 0.0000201 | 0.0000201 | 0.239490 | 0.3165560 | 344264 |
23 | 154930230 | rs781880 | A | G | 0.0017233 | 0.0003741 | 0.0000041 | 0.0000041 | 0.245920 | 0.3618540 | 344264 |
23 | 154930487 | rs781879 | T | A | 0.0033548 | 0.0012823 | 0.0088916 | 0.0088905 | 0.019561 | 0.1263580 | 344264 |
1 692794 rs530212009 CA C . PASS AF=0.11051 ES:SE:LP:AF:SS:ID -1.8157e-05:0.0006834:0.00930604:0.11051:344264:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.11579 ES:SE:LP:AF:SS:ID 0.000328:0.00064545:0.213717:0.11579:344264:rs12238997
1 707522 rs371890604 G C . PASS AF=0.097224 ES:SE:LP:AF:SS:ID 0.00048111:0.00072604:0.294513:0.097224:344264:rs371890604
1 717587 rs144155419 G A . PASS AF=0.015662 ES:SE:LP:AF:SS:ID -0.0012179:0.001733:0.316773:0.015662:344264:rs144155419
1 723329 rs189787166 A T . PASS AF=0.0017377 ES:SE:LP:AF:SS:ID -0.0042225:0.0051024:0.389425:0.0017377:344264:rs189787166
1 730087 rs148120343 T C . PASS AF=0.056414 ES:SE:LP:AF:SS:ID 0.0003467:0.00089959:0.154933:0.056414:344264:rs148120343
1 731718 rs58276399 T C . PASS AF=0.12168 ES:SE:LP:AF:SS:ID 0.00048125:0.00061218:0.364727:0.12168:344264:rs58276399
1 732032 rs61770163 A C . PASS AF=0.12108 ES:SE:LP:AF:SS:ID 0.00057777:0.00065324:0.424293:0.12108:344264:rs61770163
1 734349 rs141242758 T C . PASS AF=0.12091 ES:SE:LP:AF:SS:ID 0.00048611:0.0006125:0.369165:0.12091:344264:rs141242758
1 740284 rs61770167 C T . PASS AF=0.005757 ES:SE:LP:AF:SS:ID 0.00081473:0.0028092:0.112495:0.005757:344264:rs61770167
1 742813 rs112573343 C T . PASS AF=0.0018608 ES:SE:LP:AF:SS:ID -0.0053166:0.0053271:0.497218:0.0018608:344264:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.86983 ES:SE:LP:AF:SS:ID -0.00067364:0.00060389:0.577345:0.86983:344264:rs529266287
1 750230 rs190826124 G C . PASS AF=0.0015195 ES:SE:LP:AF:SS:ID -0.0047571:0.0054889:0.413278:0.0015195:344264:rs190826124
1 751343 rs28544273 T A . PASS AF=0.12285 ES:SE:LP:AF:SS:ID 0.0007128:0.00059803:0.632085:0.12285:344264:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.14267 ES:SE:LP:AF:SS:ID 0.00056146:0.00059103:0.465796:0.14267:344264:rs200141114
1 751756 rs28527770 T C . PASS AF=0.12297 ES:SE:LP:AF:SS:ID 0.00071983:0.00059719:0.641951:0.12297:344264:rs28527770
1 753405 rs3115860 C A . PASS AF=0.87098 ES:SE:LP:AF:SS:ID -0.00057357:0.00058202:0.488933:0.87098:344264:rs3115860
1 753425 rs3131970 T C . PASS AF=0.87555 ES:SE:LP:AF:SS:ID -0.00069911:0.00059161:0.624666:0.87555:344264:rs3131970
1 753541 rs2073813 G A . PASS AF=0.12855 ES:SE:LP:AF:SS:ID 0.00059587:0.00058345:0.512692:0.12855:344264:rs2073813
1 754105 rs12184325 C T . PASS AF=0.036324 ES:SE:LP:AF:SS:ID -0.00022686:0.0010591:0.0807127:0.036324:344264:rs12184325
1 754182 rs3131969 A G . PASS AF=0.87057 ES:SE:LP:AF:SS:ID -0.00054846:0.00058141:0.461527:0.87057:344264:rs3131969
1 754192 rs3131968 A G . PASS AF=0.87068 ES:SE:LP:AF:SS:ID -0.00055228:0.00058168:0.465479:0.87068:344264:rs3131968
1 754334 rs3131967 T C . PASS AF=0.87057 ES:SE:LP:AF:SS:ID -0.00054566:0.00058139:0.458458:0.87057:344264:rs3131967
1 754433 rs150578204 G A . PASS AF=0.0050487 ES:SE:LP:AF:SS:ID 0.0019452:0.0029819:0.288876:0.0050487:344264:rs150578204
1 754458 rs142682604 G T . PASS AF=0.0050157 ES:SE:LP:AF:SS:ID 0.0019068:0.0029899:0.280975:0.0050157:344264:rs142682604
1 755435 rs184270342 T G . PASS AF=0.0055433 ES:SE:LP:AF:SS:ID -0.0025505:0.0029023:0.420765:0.0055433:344264:rs184270342
1 755890 rs3115858 A T . PASS AF=0.87066 ES:SE:LP:AF:SS:ID -0.00057635:0.00058039:0.493915:0.87066:344264:rs3115858
1 756434 rs61768170 G C . PASS AF=0.1259 ES:SE:LP:AF:SS:ID 0.00066871:0.00059217:0.587053:0.1259:344264:rs61768170
1 756604 rs3131962 A G . PASS AF=0.87023 ES:SE:LP:AF:SS:ID -0.00053637:0.00057901:0.45069:0.87023:344264:rs3131962
1 757640 rs3115853 G A . PASS AF=0.8695 ES:SE:LP:AF:SS:ID -0.00057232:0.00057847:0.491484:0.8695:344264:rs3115853
1 757734 rs4951929 C T . PASS AF=0.87037 ES:SE:LP:AF:SS:ID -0.00054021:0.00057949:0.454408:0.87037:344264:rs4951929
1 757936 rs4951862 C A . PASS AF=0.87038 ES:SE:LP:AF:SS:ID -0.00053973:0.00057953:0.45384:0.87038:344264:rs4951862
1 758144 rs3131956 A G . PASS AF=0.87039 ES:SE:LP:AF:SS:ID -0.00054171:0.00057955:0.456006:0.87039:344264:rs3131956
1 758626 rs3131954 C T . PASS AF=0.87083 ES:SE:LP:AF:SS:ID -0.00055598:0.00058101:0.4703:0.87083:344264:rs3131954
1 759293 rs10157329 T A . PASS AF=0.09877 ES:SE:LP:AF:SS:ID 0.00056792:0.00067529:0.39756:0.09877:344264:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.006431 ES:SE:LP:AF:SS:ID -0.0014889:0.0026216:0.244057:0.006431:344264:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.87472 ES:SE:LP:AF:SS:ID -0.0006018:0.00058964:0.512254:0.87472:344264:rs3115851
1 761732 rs2286139 C T . PASS AF=0.86413 ES:SE:LP:AF:SS:ID -0.00055146:0.00057834:0.468113:0.86413:344264:rs2286139
1 761752 rs1057213 C T . PASS AF=0.86951 ES:SE:LP:AF:SS:ID -0.00066073:0.00058385:0.588768:0.86951:344264:rs1057213
1 762273 rs3115849 G A . PASS AF=0.86645 ES:SE:LP:AF:SS:ID -0.00057256:0.00058397:0.485638:0.86645:344264:rs3115849
1 762485 rs12095200 C A . PASS AF=0.098724 ES:SE:LP:AF:SS:ID 0.00057829:0.00069906:0.389223:0.098724:344264:rs12095200
1 762589 rs3115848 G C . PASS AF=0.87164 ES:SE:LP:AF:SS:ID -0.00067246:0.00059066:0.593613:0.87164:344264:rs3115848
1 762592 rs3131950 C G . PASS AF=0.87164 ES:SE:LP:AF:SS:ID -0.00067249:0.00059066:0.59363:0.87164:344264:rs3131950
1 762601 rs3131949 T C . PASS AF=0.87164 ES:SE:LP:AF:SS:ID -0.00067106:0.00059067:0.591913:0.87164:344264:rs3131949
1 762632 rs3131948 T A . PASS AF=0.87201 ES:SE:LP:AF:SS:ID -0.00067022:0.00059099:0.590456:0.87201:344264:rs3131948
1 764191 rs7515915 T G . PASS AF=0.12549 ES:SE:LP:AF:SS:ID 0.00063775:0.00059141:0.551495:0.12549:344264:rs7515915
1 766007 rs61768174 A C . PASS AF=0.10538 ES:SE:LP:AF:SS:ID 0.00066415:0.00064398:0.519433:0.10538:344264:rs61768174
1 766105 rs2519015 T A . PASS AF=0.85548 ES:SE:LP:AF:SS:ID -0.00060601:0.0005781:0.5309:0.85548:344264:rs2519015
1 767393 rs538667473 A C . PASS AF=0.0016566 ES:SE:LP:AF:SS:ID -0.0047802:0.0051152:0.455882:0.0016566:344264:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.83826 ES:SE:LP:AF:SS:ID -0.0003224:0.00056915:0.243303:0.83826:344264:rs376645387