Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std plot

beta_std_plot

beta_std_plot

Metadata

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LDSC

*********************************************************************
* 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/ieu-a-import/processed/ieu-a-8/ieu-a-8.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/ieu-a-import/processed/ieu-a-8/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Wed Feb  5 13:21:29 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-8/ieu-a-8.vcf.gz ...
Read summary statistics for 2417476 SNPs.
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, 1144892 SNPs remain.
After merging with regression SNP LD, 1144892 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.074 (0.0085)
Lambda GC: 1.0977
Mean Chi^2: 1.1347
Intercept: 1.0215 (0.0074)
Ratio: 0.1597 (0.0547)
Analysis finished at Wed Feb  5 13:21:59 2020
Total time elapsed: 30.56s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9213,
    "inflation_factor": 1.0963,
    "mean_EFFECT": 0.0001,
    "n": 84264,
    "n_snps": 2417476,
    "n_clumped_hits": 15,
    "n_p_sig": 160,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 20147,
    "n_est": 76035.6783,
    "ratio_se_n": 0.9499,
    "mean_diff": -0.0001,
    "ratio_diff": 2.7976,
    "sd_y_est1": 3.0978,
    "sd_y_est2": 2.9426,
    "r2_sum1": 0.0958,
    "r2_sum2": 0.01,
    "r2_sum3": 0.0111,
    "r2_sum4": 0.0081,
    "ldsc_nsnp_merge_refpanel_ld": 1144892,
    "ldsc_nsnp_merge_regression_ld": 1144892,
    "ldsc_observed_scale_h2_beta": 0.074,
    "ldsc_observed_scale_h2_se": 0.0085,
    "ldsc_intercept_beta": 1.0215,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.0977,
    "ldsc_mean_chisq": 1.1347,
    "ldsc_ratio": 0.1596
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique FALSE
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

Definitions

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 SNPs
  • n_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:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 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.
    • \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
    • \({z}_j = \frac{\beta_j}{{se}_j}\),
    • and \(\beta_j\) is the reported effect size.
  • 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.
    • \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
    • \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
  • 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.
    • \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
    • \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
    • and \({se}_j\) is the reported standard error.
  • 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.
    • \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
    • \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),

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 > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_sum<*>: r2_sum<*> > 0.5

Plots

  • Manhattan plot
    • Red line: \(-log_{10}^{5 \times 10^{-8}}\)
    • Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
  • QQ plot
  • AF plot
  • P-Z plot
  • beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)

Diagnostics

Details

Summary stats

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 42 0 2417476 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.581941e+00 5.655293e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.200000e+01 2.30000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.885726e+07 5.564780e+07 1.15230e+04 3.270636e+07 7.028019e+07 1.143469e+08 2.49219e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.030000e-05 2.776610e-02 -1.10961e+00 -1.413180e-02 -9.700000e-05 1.392080e-02 1.08603e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.298260e-02 1.418170e-02 1.36136e-02 1.509490e-02 1.804440e-02 2.471890e-02 5.50690e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.845822e-01 2.938341e-01 0.00000e+00 2.261919e-01 4.800550e-01 7.397705e-01 1.00000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.845822e-01 2.938341e-01 0.00000e+00 2.261920e-01 4.800541e-01 7.397711e-01 1.00000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 3.648228e-01 2.635379e-01 1.00000e-02 1.378278e-01 3.026530e-01 5.574365e-01 9.90000e-01 ▇▅▃▃▂
numeric AF_reference 20147 0.9916661 NA NA NA NA NA 3.636004e-01 2.545653e-01 1.99700e-04 1.495610e-01 3.025160e-01 5.475240e-01 1.00000e+00 ▇▆▅▃▂
numeric N 0 1.0000000 NA NA NA NA NA 7.665558e+04 1.098305e+04 2.00010e+04 7.755300e+04 8.131400e+04 8.232100e+04 8.42640e+04 ▁▁▁▁▇

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 721290 rs12565286 G C 0.1282010 0.0695073 0.0651208 0.0651212 0.0538073 0.0371406 27124
1 723819 rs11804171 T A 0.1297870 0.0698828 0.0632820 0.0632814 0.0540315 0.1345850 26259
1 752566 rs3094315 G A -0.0016609 0.0291187 0.9545153 0.9545142 0.8249000 0.7182510 36534
1 754192 rs3131968 A G -0.0289617 0.0314537 0.3571692 0.3571692 0.7698700 0.6785140 22817
1 775659 rs2905035 A G -0.0040285 0.0272131 0.8823145 0.8823149 0.8198740 0.7450080 47130
1 777122 rs2980319 A T -0.0009125 0.0270433 0.9730835 0.9730827 0.8205390 0.7472040 48068
1 779322 rs4040617 A G -0.0017451 0.0268361 0.9481510 0.9481516 0.1365300 0.2264380 47791
1 780785 rs2977612 T A -0.0000365 0.0271406 0.9989267 0.9989270 0.8634140 0.6693290 46950
1 785050 rs2905062 G A 0.0002458 0.0270487 0.9927509 0.9927495 0.8619550 0.6269970 46703
1 785989 rs2980300 T C 0.0054738 0.0259561 0.8329753 0.8329756 0.8537800 0.6269970 48946
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51175626 rs3810648 A G 0.0072231 0.0345634 0.8344619 0.8344629 0.0531682 0.1084270 68546
22 51178090 rs2285395 G A -0.0070760 0.0377561 0.8513374 0.8513365 0.0834911 0.0666933 66648
22 51196164 rs8136603 A T -0.0258867 0.0548093 0.6367090 0.6367092 0.0434938 0.1427720 60458
22 51222100 rs114553188 G T -0.0301543 0.0550702 0.5839935 0.5839933 0.0472308 0.0880591 56158
22 51223637 rs375798137 G A -0.0297975 0.0551675 0.5891081 0.5891089 0.0469412 0.0788738 56121
23 35921591 rs2204667 C G 0.0282459 0.0191645 0.1405177 0.1405177 0.1561530 NA 81489
23 51666786 rs14115 A G 0.0068168 0.0331609 0.8371288 0.8371288 0.0486877 NA 77417
23 70163799 rs1626496 A C 0.0109496 0.0257557 0.6707397 0.6707397 0.1124710 NA 81111
23 91415872 rs6562597 G A 0.0540302 0.0516399 0.2954282 0.2954282 0.0192669 0.0021192 81695
23 118495837 rs12882977 G A -0.0037640 0.0140319 0.7885078 0.7885100 0.5037110 0.2307280 81008

bcf preview

1   721290  rs12565286  G   C   .   PASS    AF=0.0538073    ES:SE:LP:AF:SS:ID   0.128201:0.0695073:1.18628:0.0538073:27124:rs12565286
1   723819  rs11804171  T   A   .   PASS    AF=0.0540315    ES:SE:LP:AF:SS:ID   0.129787:0.0698828:1.19872:0.0540315:26259:rs11804171
1   752566  rs3094315   G   A   .   PASS    AF=0.8249   ES:SE:LP:AF:SS:ID   -0.0016609:0.0291187:0.0202171:0.8249:36534:rs3094315
1   754192  rs3131968   A   G   .   PASS    AF=0.76987  ES:SE:LP:AF:SS:ID   -0.0289617:0.0314537:0.447126:0.76987:22817:rs3131968
1   775659  rs2905035   A   G   .   PASS    AF=0.819874 ES:SE:LP:AF:SS:ID   -0.0040285:0.0272131:0.0543766:0.819874:47130:rs2905035
1   777122  rs2980319   A   T   .   PASS    AF=0.820539 ES:SE:LP:AF:SS:ID   -0.0009125:0.0270433:0.0118499:0.820539:48068:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.13653  ES:SE:LP:AF:SS:ID   -0.0017451:0.0268361:0.0231225:0.13653:47791:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.863414 ES:SE:LP:AF:SS:ID   -3.65e-05:0.0271406:0.000466379:0.863414:46950:rs2977612
1   785050  rs2905062   G   A   .   PASS    AF=0.861955 ES:SE:LP:AF:SS:ID   0.0002458:0.0270487:0.00315971:0.861955:46703:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.85378  ES:SE:LP:AF:SS:ID   0.0054738:0.0259561:0.0793679:0.85378:48946:rs2980300
1   798959  rs11240777  G   A   .   PASS    AF=0.206126 ES:SE:LP:AF:SS:ID   0.008975:0.0302654:0.115309:0.206126:30919:rs11240777
1   990380  rs3121561   C   T   .   PASS    AF=0.295    ES:SE:LP:AF:SS:ID   0.028:0.0329999:0.402123:0.295:34215:rs3121561
1   998501  rs3813193   G   C   .   PASS    AF=0.182651 ES:SE:LP:AF:SS:ID   0.0034016:0.0303734:0.0405632:0.182651:34712:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.742152 ES:SE:LP:AF:SS:ID   -0.0187703:0.0217113:0.41196:0.742152:48411:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.159137 ES:SE:LP:AF:SS:ID   -0.0070263:0.0292219:0.0915229:0.159137:34528:rs3934834
1   1017170 rs3766193   C   G   .   PASS    AF=0.550892 ES:SE:LP:AF:SS:ID   -0.0157586:0.0210754:0.342345:0.550892:59854:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.561968 ES:SE:LP:AF:SS:ID   -0.0051995:0.0283805:0.0682184:0.561968:29252:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.144423 ES:SE:LP:AF:SS:ID   0.0099465:0.0314343:0.123965:0.144423:34729:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.573923 ES:SE:LP:AF:SS:ID   -0.011991:0.0182782:0.290895:0.573923:63006:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.57237  ES:SE:LP:AF:SS:ID   -0.0130313:0.0181211:0.325997:0.57237:64375:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.143209 ES:SE:LP:AF:SS:ID   0.0180932:0.0324983:0.238296:0.143209:34688:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.722623 ES:SE:LP:AF:SS:ID   -0.0074473:0.0223225:0.131552:0.722623:53228:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.142127 ES:SE:LP:AF:SS:ID   0.0197099:0.0325366:0.263871:0.142127:34680:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.729993 ES:SE:LP:AF:SS:ID   -0.0036201:0.0235499:0.0565891:0.729993:56317:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.5547   ES:SE:LP:AF:SS:ID   -0.0185:0.0519:0.141764:0.5547:21581:rs6701114
1   1026707 rs4074137   C   A   .   PASS    AF=0.626    ES:SE:LP:AF:SS:ID   -0.046:0.0252999:1.16093:0.626:34197:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.144064 ES:SE:LP:AF:SS:ID   0.0497435:0.0281564:1.11193:0.144064:39373:rs6687776
1   1030633 rs6678318   G   A   .   PASS    AF=0.142872 ES:SE:LP:AF:SS:ID   0.0509073:0.0282022:1.14836:0.142872:39337:rs6678318
1   1031540 rs9651273   A   G   .   PASS    AF=0.747557 ES:SE:LP:AF:SS:ID   -0.014647:0.0248585:0.255145:0.747557:34617:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.0898438    ES:SE:LP:AF:SS:ID   0.0532598:0.0296054:1.14254:0.0898438:65250:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.129024 ES:SE:LP:AF:SS:ID   0.0409805:0.0289901:0.802777:0.129024:41611:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.119357 ES:SE:LP:AF:SS:ID   0.0437258:0.0260782:1.02874:0.119357:65555:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.0942422    ES:SE:LP:AF:SS:ID   0.0707107:0.0283715:1.89649:0.0942422:48211:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.12066  ES:SE:LP:AF:SS:ID   0.0488419:0.0275424:1.1182:0.12066:43999:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.0907357    ES:SE:LP:AF:SS:ID   0.0510508:0.0291704:1.09635:0.0907357:65831:rs4970409
1   1060174 rs7548798   C   T   .   PASS    AF=0.322014 ES:SE:LP:AF:SS:ID   0.0331473:0.0290897:0.594312:0.322014:34671:rs7548798
1   1060235 rs7540009   G   A   .   PASS    AF=0.035    ES:SE:LP:AF:SS:ID   -0.011:0.0626997:0.0651308:0.035:34249:rs7540009
1   1060608 rs17160824  G   A   .   PASS    AF=0.0974642    ES:SE:LP:AF:SS:ID   0.0511532:0.0293633:1.08887:0.0974642:65588:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.089626 ES:SE:LP:AF:SS:ID   0.0505149:0.029373:1.06817:0.089626:65774:rs17160826
1   1061152 rs12748370  T   C   .   PASS    AF=0.0919812    ES:SE:LP:AF:SS:ID   0.0441971:0.0300373:0.850224:0.0919812:63545:rs12748370
1   1061166 rs11807848  T   C   .   PASS    AF=0.401254 ES:SE:LP:AF:SS:ID   0.0674:0.0257956:2.04676:0.401254:34777:rs11807848
1   1062015 rs9659914   C   T   .   PASS    AF=0.034    ES:SE:LP:AF:SS:ID   -0.012:0.0648997:0.0688947:0.034:34248:rs9659914
1   1062638 rs9442373   C   A   .   PASS    AF=0.557813 ES:SE:LP:AF:SS:ID   -0.0657354:0.0247604:2.1005:0.557813:34779:rs9442373
1   1064535 rs6682475   G   C   .   PASS    AF=0.73 ES:SE:LP:AF:SS:ID   -0.027:0.0340999:0.368068:0.73:34179:rs6682475
1   1064979 rs2298217   C   T   .   PASS    AF=0.126426 ES:SE:LP:AF:SS:ID   0.0435369:0.0292475:0.864547:0.126426:38716:rs2298217
1   1077064 rs4970357   C   A   .   PASS    AF=0.918735 ES:SE:LP:AF:SS:ID   0.0117037:0.0462911:0.0966923:0.918735:51912:rs4970357
1   1079198 rs11260603  T   C   .   PASS    AF=0.227    ES:SE:LP:AF:SS:ID   0.031:0.0329999:0.459012:0.227:34201:rs11260603
1   1087683 rs9442380   T   C   .   PASS    AF=0.914628 ES:SE:LP:AF:SS:ID   0.007653:0.0364682:0.0789475:0.914628:65784:rs9442380
1   1089262 rs4970358   A   G   .   PASS    AF=0.954487 ES:SE:LP:AF:SS:ID   0.0374554:0.0554406:0.301641:0.954487:55826:rs4970358
1   1094738 rs4970362   A   G   .   PASS    AF=0.615243 ES:SE:LP:AF:SS:ID   -0.0058565:0.0217067:0.103853:0.615243:34626:rs4970362