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"file_date": "2019-11-25T17:20:35.710247",
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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-J18/ukb-d-J18.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-J18/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 18:03:35 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-J18/ukb-d-J18.vcf.gz ...
Read summary statistics for 12165648 SNPs.
Dropped 10691 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, 1283118 SNPs remain.
After merging with regression SNP LD, 1283118 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0025 (0.0012)
Lambda GC: 1.0259
Mean Chi^2: 1.0217
Intercept: 1.0042 (0.0057)
Ratio: 0.1925 (0.2612)
Analysis finished at Mon Nov 25 18:05:40 2019
Total time elapsed: 2.0m:4.72s
{
"af_correlation": 0.9494,
"inflation_factor": 1.0192,
"mean_EFFECT": -2.1073e-06,
"n": 361194,
"n_snps": 12165648,
"n_clumped_hits": 0,
"n_p_sig": 3,
"n_mono": 0,
"n_ns": 1191823,
"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": 301205,
"n_est": 362104.079,
"ratio_se_n": 1.0013,
"mean_diff": -0,
"ratio_diff": 34.0193,
"sd_y_est1": 0.1212,
"sd_y_est2": 0.1213,
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1283118,
"ldsc_nsnp_merge_regression_ld": 1283118,
"ldsc_observed_scale_h2_beta": 0.0025,
"ldsc_observed_scale_h2_se": 0.0012,
"ldsc_intercept_beta": 1.0042,
"ldsc_intercept_se": 0.0057,
"ldsc_lambda_gc": 1.0259,
"ldsc_mean_chisq": 1.0217,
"ldsc_ratio": 0.1935
}
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 | 12155583 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 53770 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 32271 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.066568e+00 | 6.184645e+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 | 7.891332e+07 | 5.597105e+07 | 3.02000e+02 | 3.272552e+07 | 6.994762e+07 | 1.147824e+08 | 2.492309e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -2.100000e-06 | 1.167400e-03 | -1.19318e-02 | -3.949000e-04 | -4.100000e-06 | 3.819000e-04 | 1.567040e-02 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.918000e-04 | 7.513000e-04 | 2.34600e-04 | 3.292000e-04 | 5.300000e-04 | 1.235700e-03 | 4.443700e-03 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.970985e-01 | 2.895510e-01 | 0.00000e+00 | 2.455698e-01 | 4.959159e-01 | 7.482780e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.970981e-01 | 2.895513e-01 | 0.00000e+00 | 2.455688e-01 | 4.959150e-01 | 7.482780e-01 | 9.999999e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.118906e-01 | 2.589004e-01 | 2.32900e-03 | 1.424440e-02 | 8.842610e-02 | 3.361780e-01 | 9.976710e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 301205 | 0.9752414 | NA | NA | NA | NA | NA | 2.135486e-01 | 2.504783e-01 | 0.00000e+00 | 1.098240e-02 | 1.084270e-01 | 3.392570e-01 | 1.000000e+00 | ▇▂▁▁▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.611940e+05 | 0.000000e+00 | 3.61194e+05 | 3.611940e+05 | 3.611940e+05 | 3.611940e+05 | 3.611940e+05 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | -0.0005062 | 0.0004997 | 0.3111208 | 0.3111200 | 0.1106400 | 0.1894970 | 361194 |
1 | 693731 | rs12238997 | A | G | -0.0005284 | 0.0004722 | 0.2631401 | 0.2631391 | 0.1158300 | 0.1417730 | 361194 |
1 | 707522 | rs371890604 | G | C | -0.0004276 | 0.0005308 | 0.4204932 | 0.4204926 | 0.0973034 | 0.1293930 | 361194 |
1 | 717587 | rs144155419 | G | A | -0.0017122 | 0.0012667 | 0.1764672 | 0.1764676 | 0.0156880 | 0.0045926 | 361194 |
1 | 730087 | rs148120343 | T | C | -0.0003808 | 0.0006578 | 0.5626664 | 0.5626664 | 0.0564602 | 0.0127796 | 361194 |
1 | 731718 | rs142557973 | T | C | -0.0004579 | 0.0004478 | 0.3065328 | 0.3065328 | 0.1217380 | 0.1543530 | 361194 |
1 | 732032 | rs61770163 | A | C | -0.0006749 | 0.0004777 | 0.1576990 | 0.1576986 | 0.1211710 | 0.1555510 | 361194 |
1 | 734349 | rs141242758 | T | C | -0.0004792 | 0.0004481 | 0.2848138 | 0.2848130 | 0.1209650 | 0.1525560 | 361194 |
1 | 740284 | rs61770167 | C | T | -0.0012809 | 0.0020499 | 0.5320617 | 0.5320607 | 0.0057851 | 0.0023962 | 361194 |
1 | 749963 | rs529266287 | T | TAA | 0.0005506 | 0.0004417 | 0.2125651 | 0.2125642 | 0.8697420 | 0.7641770 | 361194 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | 0.0001822 | 0.0005174 | 0.7246445 | 0.7246438 | 0.0561667 | 0.0309934 | 361194 |
23 | 154923374 | rs111332691 | T | A | 0.0010511 | 0.0005686 | 0.0645119 | 0.0645114 | 0.0447862 | 0.0116556 | 361194 |
23 | 154925045 | rs509981 | C | T | -0.0002280 | 0.0002736 | 0.4047101 | 0.4047090 | 0.2456060 | 0.3634440 | 361194 |
23 | 154925895 | rs538470 | C | T | -0.0002285 | 0.0002799 | 0.4142152 | 0.4142147 | 0.2419150 | 0.3634440 | 361194 |
23 | 154927581 | rs644138 | G | A | -0.0001505 | 0.0002573 | 0.5586194 | 0.5586193 | 0.3021620 | 0.4635760 | 361194 |
23 | 154929412 | rs557132 | C | T | -0.0002279 | 0.0002737 | 0.4050662 | 0.4050648 | 0.2454590 | 0.3568210 | 361194 |
23 | 154929637 | rs35185538 | CT | C | -0.0001775 | 0.0002856 | 0.5343145 | 0.5343153 | 0.2296970 | 0.3011920 | 361194 |
23 | 154929952 | rs4012982 | CAA | C | -0.0002226 | 0.0002878 | 0.4393322 | 0.4393306 | 0.2394250 | 0.3165560 | 361194 |
23 | 154930230 | rs781880 | A | G | -0.0002254 | 0.0002736 | 0.4100058 | 0.4100055 | 0.2458690 | 0.3618540 | 361194 |
23 | 154930487 | rs781879 | T | A | -0.0011393 | 0.0009386 | 0.2248278 | 0.2248281 | 0.0195623 | 0.1263580 | 361194 |
1 692794 rs530212009 CA C . PASS AF=0.11064 ES:SE:LP:AF:SS:ID -0.000506172:0.000499738:0.507071:0.11064:361194:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.11583 ES:SE:LP:AF:SS:ID -0.000528384:0.000472192:0.579813:0.11583:361194:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0973034 ES:SE:LP:AF:SS:ID -0.000427628:0.000530841:0.376241:0.0973034:361194:rs371890604
1 717587 rs144155419 G A . PASS AF=0.015688 ES:SE:LP:AF:SS:ID -0.00171224:0.00126672:0.753336:0.015688:361194:rs144155419
1 730087 rs148120343 T C . PASS AF=0.0564602 ES:SE:LP:AF:SS:ID -0.000380806:0.000657826:0.249749:0.0564602:361194:rs148120343
1 731718 rs58276399 T C . PASS AF=0.121738 ES:SE:LP:AF:SS:ID -0.000457915:0.000447828:0.513523:0.121738:361194:rs58276399
1 732032 rs61770163 A C . PASS AF=0.121171 ES:SE:LP:AF:SS:ID -0.000674912:0.000477694:0.802171:0.121171:361194:rs61770163
1 734349 rs141242758 T C . PASS AF=0.120965 ES:SE:LP:AF:SS:ID -0.00047924:0.000448068:0.545439:0.120965:361194:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00578512 ES:SE:LP:AF:SS:ID -0.00128092:0.00204992:0.274038:0.00578512:361194:rs61770167
1 749963 rs529266287 T TAA . PASS AF=0.869742 ES:SE:LP:AF:SS:ID 0.000550629:0.000441724:0.672508:0.869742:361194:rs529266287
1 751343 rs28544273 T A . PASS AF=0.122916 ES:SE:LP:AF:SS:ID -0.000545696:0.00043747:0.673142:0.122916:361194:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.142712 ES:SE:LP:AF:SS:ID -0.00052126:0.000432415:0.642016:0.142712:361194:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123031 ES:SE:LP:AF:SS:ID -0.000557994:0.000436861:0.695716:0.123031:361194:rs28527770
1 753405 rs3115860 C A . PASS AF=0.87089 ES:SE:LP:AF:SS:ID 0.000533724:0.000425706:0.677907:0.87089:361194:rs3115860
1 753425 rs3131970 T C . PASS AF=0.875472 ES:SE:LP:AF:SS:ID 0.000605966:0.000432761:0.791978:0.875472:361194:rs3131970
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1 754105 rs12184325 C T . PASS AF=0.0363613 ES:SE:LP:AF:SS:ID 0.000635587:0.000774267:0.385408:0.0363613:361194:rs12184325
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1 754334 rs3131967 T C . PASS AF=0.870481 ES:SE:LP:AF:SS:ID 0.000564495:0.000425248:0.734331:0.870481:361194:rs3131967
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1 754458 rs142682604 G T . PASS AF=0.00501064 ES:SE:LP:AF:SS:ID -0.00123419:0.002189:0.241936:0.00501064:361194:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00558665 ES:SE:LP:AF:SS:ID -0.00177891:0.00211444:0.397755:0.00558665:361194:rs184270342
1 755890 rs3115858 A T . PASS AF=0.870563 ES:SE:LP:AF:SS:ID 0.000563447:0.0004245:0.73423:0.870563:361194:rs3115858
1 756434 rs61768170 G C . PASS AF=0.125985 ES:SE:LP:AF:SS:ID -0.000562414:0.000433145:0.711892:0.125985:361194:rs61768170
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1 757640 rs3115853 G A . PASS AF=0.869414 ES:SE:LP:AF:SS:ID 0.000531501:0.000423092:0.679785:0.869414:361194:rs3115853
1 757734 rs4951929 C T . PASS AF=0.870281 ES:SE:LP:AF:SS:ID 0.000543642:0.000423843:0.699805:0.870281:361194:rs4951929
1 757936 rs4951862 C A . PASS AF=0.870287 ES:SE:LP:AF:SS:ID 0.000544332:0.000423873:0.700979:0.870287:361194:rs4951862
1 758144 rs3131956 A G . PASS AF=0.870295 ES:SE:LP:AF:SS:ID 0.000548087:0.000423886:0.707722:0.870295:361194:rs3131956
1 758626 rs3131954 C T . PASS AF=0.870739 ES:SE:LP:AF:SS:ID 0.000554603:0.000424965:0.716982:0.870739:361194:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0988442 ES:SE:LP:AF:SS:ID -0.000394966:0.000493836:0.372806:0.0988442:361194:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00647588 ES:SE:LP:AF:SS:ID -0.00253108:0.00191018:0.73246:0.00647588:361194:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.874635 ES:SE:LP:AF:SS:ID 0.000581789:0.000431299:0.751137:0.874635:361194:rs3115851
1 761732 rs2286139 C T . PASS AF=0.864027 ES:SE:LP:AF:SS:ID 0.000590715:0.000422952:0.789093:0.864027:361194:rs2286139
1 761752 rs1057213 C T . PASS AF=0.869425 ES:SE:LP:AF:SS:ID 0.000589181:0.000427059:0.775459:0.869425:361194:rs1057213
1 762273 rs3115849 G A . PASS AF=0.866371 ES:SE:LP:AF:SS:ID 0.000575551:0.000427145:0.749968:0.866371:361194:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0987831 ES:SE:LP:AF:SS:ID -0.000664398:0.000511373:0.71251:0.0987831:361194:rs12095200
1 762589 rs3115848 G C . PASS AF=0.871556 ES:SE:LP:AF:SS:ID 0.000582891:0.000432012:0.751394:0.871556:361194:rs3115848
1 762592 rs3131950 C G . PASS AF=0.871556 ES:SE:LP:AF:SS:ID 0.000582899:0.000432012:0.751409:0.871556:361194:rs3131950
1 762601 rs3131949 T C . PASS AF=0.871555 ES:SE:LP:AF:SS:ID 0.000582679:0.00043202:0.750988:0.871555:361194:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871929 ES:SE:LP:AF:SS:ID 0.000601244:0.000432266:0.784487:0.871929:361194:rs3131948
1 764191 rs7515915 T G . PASS AF=0.125562 ES:SE:LP:AF:SS:ID -0.000556013:0.000432607:0.701798:0.125562:361194:rs7515915
1 766007 rs61768174 A C . PASS AF=0.105428 ES:SE:LP:AF:SS:ID -0.000316519:0.000470953:0.299701:0.105428:361194:rs61768174
1 766105 rs2519015 T A . PASS AF=0.855376 ES:SE:LP:AF:SS:ID 0.000707783:0.000422793:1.02632:0.855376:361194:rs2519015
1 768116 rs376645387 A AGTTTT . PASS AF=0.838358 ES:SE:LP:AF:SS:ID 0.000209629:0.000416529:0.211287:0.838358:361194:rs376645387
1 768253 rs2977608 A C . PASS AF=0.763351 ES:SE:LP:AF:SS:ID 0.000256603:0.000335227:0.35262:0.763351:361194:rs2977608
1 768448 rs12562034 G A . PASS AF=0.105921 ES:SE:LP:AF:SS:ID 0.000265724:0.000461862:0.2479:0.105921:361194:rs12562034
1 768819 rs12562811 C T . PASS AF=0.00768395 ES:SE:LP:AF:SS:ID -2.53272e-05:0.00171603:0.0051446:0.00768395:361194:rs12562811
1 769138 rs59306077 CAT C . PASS AF=0.128938 ES:SE:LP:AF:SS:ID -0.000576049:0.000426556:0.752353:0.128938:361194:rs762168062