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-974/ieu-a-974.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-974/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 11:01:42 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-974/ieu-a-974.vcf.gz ...
Read summary statistics for 2493453 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, 1160701 SNPs remain.
After merging with regression SNP LD, 1160701 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.16 (0.007)
Lambda GC: 1.0362
Mean Chi^2: 1.1479
Intercept: 0.7468 (0.0067)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Wed Feb  5 11:02:11 2020
Total time elapsed: 29.01s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9176,
    "inflation_factor": 1.0388,
    "mean_EFFECT": 0.0001,
    "n": 171977,
    "n_snps": 2493453,
    "n_clumped_hits": 37,
    "n_p_sig": 1129,
    "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": 12694,
    "n_miss_AF_reference": 21871,
    "n_est": 168270.6655,
    "ratio_se_n": 0.9892,
    "mean_diff": -0,
    "ratio_diff": 3.8334,
    "sd_y_est1": 1.4052,
    "sd_y_est2": 1.3899,
    "r2_sum1": 0.0195,
    "r2_sum2": 0.0099,
    "r2_sum3": 0.0101,
    "r2_sum4": 0.0141,
    "ldsc_nsnp_merge_refpanel_ld": 1160701,
    "ldsc_nsnp_merge_regression_ld": 1160701,
    "ldsc_observed_scale_h2_beta": 0.16,
    "ldsc_observed_scale_h2_se": 0.007,
    "ldsc_intercept_beta": 0.7468,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0362,
    "ldsc_mean_chisq": 1.1479,
    "ldsc_ratio": -1.712
}

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 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

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 2493453 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 8.594572e+00 5.661433e+00 1.0000 4.000000e+00 8.000000e+00 1.200000e+01 2.30000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.882663e+07 5.567007e+07 11523.0000 3.267591e+07 7.023911e+07 1.143035e+08 2.49219e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.139000e-04 9.885500e-03 -0.3113 -4.500000e-03 0.000000e+00 4.600000e-03 3.64500e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.059700e-03 6.624100e-03 0.0039 5.000000e-03 5.900000e-03 8.200000e-03 1.63700e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.920300e-01 2.929829e-01 0.0000 2.366001e-01 4.918005e-01 7.460003e-01 1.00000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.920383e-01 2.929812e-01 0.0000 2.366771e-01 4.917677e-01 7.459807e-01 1.00000e+00 ▇▇▇▇▇
numeric AF 12694 0.9949091 NA NA NA NA NA 3.556387e-01 2.762232e-01 0.0083 1.167000e-01 2.917000e-01 5.583000e-01 9.91700e-01 ▇▅▃▂▂
numeric AF_reference 21871 0.9912286 NA NA NA NA NA 3.592524e-01 2.570326e-01 0.0000 1.431710e-01 2.961260e-01 5.439300e-01 1.00000e+00 ▇▆▃▃▂
numeric N 0 1.0000000 NA NA NA NA NA 1.287008e+05 1.309962e+04 50000.8000 1.267810e+05 1.318830e+05 1.320780e+05 1.71977e+05 ▁▁▁▇▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 721290 rs12565286 G C 0.0128 0.0204 0.5305997 0.5303637 0.0678 0.0371406 51793.0
1 752566 rs3094315 G A -0.0008 0.0091 0.9298999 0.9299465 0.8448 0.7182510 63021.2
1 775659 rs2905035 A G 0.0046 0.0103 0.6552002 0.6551625 0.8750 0.7450080 69645.8
1 777122 rs2980319 A T 0.0051 0.0103 0.6205003 0.6204973 0.8750 0.7472040 69878.8
1 779322 rs4040617 A G -0.0010 0.0110 0.9275999 0.9275648 0.1250 0.2264380 63440.6
1 780785 rs2977612 T A -0.0007 0.0110 0.9493000 0.9492598 0.8661 0.6693290 63254.6
1 785050 rs2905062 G A 0.0008 0.0083 0.9232999 0.9232144 NA 0.6269970 89910.6
1 785989 rs2980300 T C -0.0002 0.0109 0.9854000 0.9853607 0.8729 0.6269970 63430.7
1 798959 rs11240777 G A -0.0111 0.0111 0.3172999 0.3173105 0.1667 0.4099440 52556.0
1 990380 rs3121561 C T -0.0028 0.0081 0.7296003 0.7295840 0.2667 0.3434500 101314.0
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51217134 rs117417021 A G 0.0130 0.0088 0.1395999 0.1396025 0.441700 0.2671730 73127.0
22 51222100 rs114553188 G T -0.0090 0.0136 0.5080998 0.5081220 0.066700 0.0880591 107282.0
22 51223637 rs375798137 G A -0.0092 0.0136 0.4986996 0.4987419 0.066700 0.0788738 107281.0
22 51229805 rs9616985 T C 0.0105 0.0166 0.5270005 0.5270405 0.091700 0.0730831 72408.6
23 35921591 rs2204667 C G 0.0030 0.0065 0.6444007 0.6444123 0.166700 NA 132047.0
23 51666786 rs14115 A G 0.0185 0.0106 0.0809394 0.0809356 0.025000 NA 125275.0
23 70163799 rs1626496 A C -0.0130 0.0091 0.1530999 0.1531275 0.075000 NA 131866.0
23 74963352 rs1053838 T G -0.0936 0.0584 0.1089999 0.1089921 0.991379 NA 62799.6
23 91415872 rs6562597 G A 0.0115 0.0177 0.5159006 0.5158747 0.008300 0.0021192 118145.0
23 118495837 rs12882977 G A 0.0020 0.0047 0.6704000 0.6704490 0.516700 0.2307280 132092.0

bcf preview

1   721290  rs12565286  G   C   .   PASS    AF=0.0678   ES:SE:LP:AF:SS:ID   0.0128:0.0204:0.275233:0.0678:51793:rs12565286
1   752566  rs3094315   G   A   .   PASS    AF=0.8448   ES:SE:LP:AF:SS:ID   -0.0008:0.0091:0.0315638:0.8448:63021.2:rs3094315
1   775659  rs2905035   A   G   .   PASS    AF=0.875    ES:SE:LP:AF:SS:ID   0.0046:0.0103:0.183626:0.875:69645.8:rs2905035
1   777122  rs2980319   A   T   .   PASS    AF=0.875    ES:SE:LP:AF:SS:ID   0.0051:0.0103:0.207258:0.875:69878.8:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.125    ES:SE:LP:AF:SS:ID   -0.001:0.011:0.0326393:0.125:63440.6:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.8661   ES:SE:LP:AF:SS:ID   -0.0007:0.011:0.0225965:0.8661:63254.6:rs2977612
1   785050  rs2905062   G   A   .   PASS    .   ES:SE:LP:SS:ID  0.0008:0.0083:0.0346572:89910.6:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.8729   ES:SE:LP:AF:SS:ID   -0.0002:0.0109:0.00638744:0.8729:63430.7:rs2980300
1   798959  rs11240777  G   A   .   PASS    AF=0.1667   ES:SE:LP:AF:SS:ID   -0.0111:0.0111:0.49853:0.1667:52556:rs11240777
1   990380  rs3121561   C   T   .   PASS    AF=0.2667   ES:SE:LP:AF:SS:ID   -0.0028:0.0081:0.136915:0.2667:101314:rs3121561
1   998501  rs3813193   G   C   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   0.0075:0.0081:0.450384:0.15:101183:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.7373   ES:SE:LP:AF:SS:ID   0.0092:0.0061:0.881074:0.7373:127575:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.1167   ES:SE:LP:AF:SS:ID   0.0103:0.0076:0.756218:0.1167:107708:rs3934834
1   1017170 rs3766193   C   G   .   PASS    AF=0.5667   ES:SE:LP:AF:SS:ID   0.0042:0.0057:0.336111:0.5667:125586:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.5763   ES:SE:LP:AF:SS:ID   0.0044:0.0054:0.381743:0.5763:126537:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.09649  ES:SE:LP:AF:SS:ID   0.0109:0.0079:0.775467:0.09649:108075:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.5917   ES:SE:LP:AF:SS:ID   0.0029:0.0053:0.233364:0.5917:129034:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.6017   ES:SE:LP:AF:SS:ID   0.003:0.0052:0.248721:0.6017:129003:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.1271   ES:SE:LP:AF:SS:ID   0.0117:0.008:0.842846:0.1271:107974:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.7167   ES:SE:LP:AF:SS:ID   0.0087:0.0055:0.94424:0.7167:130346:rs3737728
1   1021583 rs10907178  A   C   .   PASS    .   ES:SE:LP:SS:ID  0.0118:0.0081:0.838033:104966:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.725    ES:SE:LP:AF:SS:ID   0.0095:0.0058:0.993962:0.725:129806:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.5667   ES:SE:LP:AF:SS:ID   0.0032:0.0057:0.24071:0.5667:121254:rs6701114
1   1026707 rs4074137   C   A   .   PASS    AF=0.6  ES:SE:LP:AF:SS:ID   -0.007:0.0059:0.628194:0.6:108692:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.08333  ES:SE:LP:AF:SS:ID   0.0049:0.0071:0.309715:0.08333:109994:rs6687776
1   1030633 rs6678318   G   A   .   PASS    AF=0.08621  ES:SE:LP:AF:SS:ID   0.0026:0.0077:0.133358:0.08621:98875.6:rs6678318
1   1031540 rs9651273   A   G   .   PASS    AF=0.6583   ES:SE:LP:AF:SS:ID   -0.0027:0.006:0.185286:0.6583:106125:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.05 ES:SE:LP:AF:SS:ID   0.0128:0.0084:0.894149:0.05:119834:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.075    ES:SE:LP:AF:SS:ID   0.007:0.0077:0.439735:0.075:114723:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.06667  ES:SE:LP:AF:SS:ID   0.006:0.0077:0.360713:0.06667:118189:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.05172  ES:SE:LP:AF:SS:ID   0.0115:0.0084:0.767004:0.05172:119819:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.06667  ES:SE:LP:AF:SS:ID   0.0046:0.0076:0.263604:0.06667:118203:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.05 ES:SE:LP:AF:SS:ID   0.0108:0.0088:0.65817:0.05:116574:rs4970409
1   1060174 rs7548798   C   T   .   PASS    AF=0.3981   ES:SE:LP:AF:SS:ID   -0.0014:0.0073:0.0716554:0.3981:85817.5:rs7548798
1   1060235 rs7540009   G   A   .   PASS    AF=0.01667  ES:SE:LP:AF:SS:ID   -0.0178:0.0164:0.556268:0.01667:98970.3:rs7540009
1   1060608 rs17160824  G   A   .   PASS    AF=0.05833  ES:SE:LP:AF:SS:ID   0.0104:0.0087:0.634699:0.05833:119714:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.05455  ES:SE:LP:AF:SS:ID   0.0107:0.0088:0.649752:0.05455:119731:rs17160826
1   1061152 rs12748370  T   C   .   PASS    .   ES:SE:LP:SS:ID  0.0116:0.0089:0.715795:116495:rs12748370
1   1061166 rs11807848  T   C   .   PASS    AF=0.4123   ES:SE:LP:AF:SS:ID   0.0022:0.0061:0.143634:0.4123:102991:rs11807848
1   1062015 rs9659914   C   T   .   PASS    AF=0.01667  ES:SE:LP:AF:SS:ID   -0.018:0.0178:0.505985:0.01667:92550.3:rs9659914
1   1062638 rs9442373   C   A   .   PASS    AF=0.5517   ES:SE:LP:AF:SS:ID   -0.0019:0.006:0.124071:0.5517:102330:rs9442373
1   1064535 rs6682475   G   C   .   PASS    AF=0.7542   ES:SE:LP:AF:SS:ID   -0.0093:0.0086:0.553618:0.7542:89465.9:rs6682475
1   1064979 rs2298217   C   T   .   PASS    AF=0.08333  ES:SE:LP:AF:SS:ID   0.0081:0.0077:0.533429:0.08333:103588:rs2298217
1   1066403 rs10907182  T   C   .   PASS    AF=0.675    ES:SE:LP:AF:SS:ID   -0.0002:0.0065:0.0107727:0.675:98390.4:rs10907182
1   1071118 rs10907183  G   C   .   PASS    AF=0.6833   ES:SE:LP:AF:SS:ID   -0.0012:0.0071:0.0625824:0.6833:94846.1:rs10907183
1   1077064 rs4970357   C   A   .   PASS    AF=0.92373  ES:SE:LP:AF:SS:ID   -0.0082:0.0111:0.337148:0.92373:117465:rs4970357
1   1079198 rs11260603  T   C   .   PASS    AF=0.2241   ES:SE:LP:AF:SS:ID   -0.0012:0.0109:0.0398623:0.2241:55928.6:rs11260603
1   1087683 rs9442380   T   C   .   PASS    AF=0.91228  ES:SE:LP:AF:SS:ID   -0.0119:0.0099:0.639407:0.91228:123134:rs9442380
1   1089262 rs4970358   A   G   .   PASS    AF=0.9661   ES:SE:LP:AF:SS:ID   -0.0158:0.0128:0.66334:0.9661:124109:rs4970358
1   1094738 rs4970362   A   G   .   PASS    AF=0.6667   ES:SE:LP:AF:SS:ID   -0.0045:0.0072:0.274088:0.6667:65906.8:rs4970362