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-85/ieu-a-85.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-85/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Tue Feb  4 20:52:49 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-85/ieu-a-85.vcf.gz ...
Read summary statistics for 1982482 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, 975764 SNPs remain.
After merging with regression SNP LD, 975764 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.6135 (0.0404)
Lambda GC: 1.039
Mean Chi^2: 1.0618
Intercept: 0.8885 (0.0077)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Tue Feb  4 20:53:15 2020
Total time elapsed: 25.94s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8843,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0.0003,
    "n": 16068,
    "n_snps": 1982482,
    "n_clumped_hits": 7,
    "n_p_sig": 228,
    "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": 2065,
    "n_miss_AF_reference": 15984,
    "n_est": 15515.6914,
    "ratio_se_n": 0.9827,
    "mean_diff": 0.0002,
    "ratio_diff": 18.9512,
    "sd_y_est1": 2.4466,
    "sd_y_est2": 2.4042,
    "r2_sum1": 0.1401,
    "r2_sum2": 0.0234,
    "r2_sum3": 0.0242,
    "r2_sum4": 0.0234,
    "ldsc_nsnp_merge_refpanel_ld": 975764,
    "ldsc_nsnp_merge_regression_ld": 975764,
    "ldsc_observed_scale_h2_beta": 0.6135,
    "ldsc_observed_scale_h2_se": 0.0404,
    "ldsc_intercept_beta": 0.8885,
    "ldsc_intercept_se": 0.0077,
    "ldsc_lambda_gc": 1.039,
    "ldsc_mean_chisq": 1.0618,
    "ldsc_ratio": -1.8042
}

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 1982482 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 8.574015e+00 5.653941e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.200000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.884663e+07 5.574042e+07 1.2183e+04 3.254331e+07 7.019551e+07 1.145245e+08 2.491722e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -2.962000e-04 3.756700e-02 -2.7000e-01 -2.300000e-02 -3.000000e-04 2.300000e-02 3.500000e-01 ▁▃▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.544330e-02 1.130700e-02 2.5000e-02 2.700000e-02 3.100000e-02 4.100000e-02 1.200000e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.930532e-01 2.909072e-01 0.0000e+00 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.927803e-01 2.909963e-01 0.0000e+00 2.385689e-01 4.904111e-01 7.454268e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 2065 0.9989584 NA NA NA NA NA 3.971520e-01 2.425215e-01 8.0000e-03 1.860000e-01 3.500000e-01 5.830000e-01 9.920000e-01 ▇▇▆▅▂
numeric AF_reference 15984 0.9919374 NA NA NA NA NA 3.944460e-01 2.321403e-01 1.9970e-04 2.008790e-01 3.510380e-01 5.674920e-01 1.000000e+00 ▆▇▆▃▂
numeric N 0 1.0000000 NA NA NA NA NA 1.333642e+04 2.359199e+03 7.9949e+03 1.143500e+04 1.412150e+04 1.545580e+04 1.606800e+04 ▂▂▂▃▇

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 990380 rs3121561 C T 0.0067 0.046 0.8800001 0.8841960 0.267 0.343450 11563.80
1 998501 rs3813193 G C 0.0580 0.048 0.2300001 0.2269191 0.150 0.206669 9809.49
1 1003629 rs4075116 C T 0.0700 0.035 0.0479999 0.0455003 0.737 0.720647 13988.60
1 1005806 rs3934834 C T 0.0520 0.047 0.2700001 0.2685608 0.119 0.223442 9281.00
1 1017170 rs3766193 C G 0.0130 0.032 0.6800001 0.6845589 0.569 0.575479 15278.30
1 1017197 rs3766192 C T 0.0140 0.030 0.6400000 0.6407384 0.576 0.511182 15340.40
1 1017587 rs3766191 C T 0.0620 0.051 0.2200002 0.2241045 0.096 0.171126 8981.86
1 1018562 rs9442371 C T 0.0140 0.030 0.6400000 0.6407384 0.592 0.530152 15356.60
1 1018704 rs9442372 A G 0.0150 0.030 0.6200004 0.6170751 0.602 0.611022 15356.50
1 1021346 rs10907177 A G 0.0600 0.053 0.2500000 0.2576027 0.127 0.178914 8885.03
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51158017 rs6010065 G C 0.0160 0.026 0.5400003 0.5383007 0.442 0.5475240 15139.3
22 51162059 rs10451 G A 0.0086 0.035 0.8100000 0.8059034 0.284 0.3865810 10317.7
22 51163138 rs715586 C T 0.0130 0.044 0.7700005 0.7676467 0.150 0.0902556 10548.0
22 51165664 rs8137951 G A 0.0170 0.030 0.5700002 0.5709407 0.275 0.4063500 14617.0
22 51171693 rs756638 G A -0.0500 0.036 0.1600000 0.1648665 0.283 0.3049120 11470.0
22 51212875 rs2238837 A C 0.0370 0.047 0.4299995 0.4311449 0.392 0.3724040 8665.0
22 51217134 rs117417021 A G 0.0340 0.047 0.4700002 0.4694316 0.442 0.2671730 8491.0
23 35921591 rs2204667 C G 0.0340 0.041 0.4000000 0.4069526 0.167 NA 11453.0
23 70163799 rs1626496 A C -0.1100 0.065 0.0800000 0.0905873 0.075 NA 8054.7
23 118495837 rs12882977 G A 0.0099 0.025 0.6999999 0.6921050 0.509 0.2307280 15893.0

bcf preview

1   990380  rs3121561   C   T   .   PASS    AF=0.267    ES:SE:LP:AF:SS:ID   0.0067:0.046:0.0555173:0.267:11563.8:rs3121561
1   998501  rs3813193   G   C   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   0.058:0.048:0.638272:0.15:9809.49:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.737    ES:SE:LP:AF:SS:ID   0.07:0.035:1.31876:0.737:13988.6:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.119    ES:SE:LP:AF:SS:ID   0.052:0.047:0.568636:0.119:9281:rs3934834
1   1017170 rs3766193   C   G   .   PASS    AF=0.569    ES:SE:LP:AF:SS:ID   0.013:0.032:0.167491:0.569:15278.3:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.576    ES:SE:LP:AF:SS:ID   0.014:0.03:0.19382:0.576:15340.4:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.096    ES:SE:LP:AF:SS:ID   0.062:0.051:0.657577:0.096:8981.86:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.592    ES:SE:LP:AF:SS:ID   0.014:0.03:0.19382:0.592:15356.6:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.602    ES:SE:LP:AF:SS:ID   0.015:0.03:0.207608:0.602:15356.5:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.127    ES:SE:LP:AF:SS:ID   0.06:0.053:0.60206:0.127:8885.03:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.717    ES:SE:LP:AF:SS:ID   0.048:0.033:0.853872:0.717:14365:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.113    ES:SE:LP:AF:SS:ID   0.065:0.053:0.657577:0.113:8888.84:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.725    ES:SE:LP:AF:SS:ID   0.044:0.034:0.721246:0.725:14216.5:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.567    ES:SE:LP:AF:SS:ID   -0.0065:0.032:0.0757207:0.567:14053.3:rs6701114
1   1026707 rs4074137   C   A   .   PASS    AF=0.6  ES:SE:LP:AF:SS:ID   -0.058:0.035:1.01773:0.6:11221.8:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.083    ES:SE:LP:AF:SS:ID   0.04:0.048:0.387216:0.083:8526:rs6687776
1   1031540 rs9651273   A   G   .   PASS    AF=0.658    ES:SE:LP:AF:SS:ID   -0.021:0.036:0.259637:0.658:10777:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.05 ES:SE:LP:AF:SS:ID   0.14:0.064:1.61979:0.05:8083:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.075    ES:SE:LP:AF:SS:ID   0.076:0.054:0.79588:0.075:8674.7:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.067    ES:SE:LP:AF:SS:ID   0.081:0.053:0.886057:0.067:9331.9:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.052    ES:SE:LP:AF:SS:ID   0.15:0.063:1.74473:0.052:8296:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.067    ES:SE:LP:AF:SS:ID   0.073:0.052:0.769551:0.067:9329:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.05 ES:SE:LP:AF:SS:ID   0.14:0.062:1.65758:0.05:8464.9:rs4970409
1   1060174 rs7548798   C   T   .   PASS    AF=0.398    ES:SE:LP:AF:SS:ID   -0.024:0.046:0.221849:0.398:8386.79:rs7548798
1   1060608 rs17160824  G   A   .   PASS    AF=0.058    ES:SE:LP:AF:SS:ID   0.15:0.062:1.76955:0.058:8669:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.055    ES:SE:LP:AF:SS:ID   0.15:0.063:1.67778:0.055:8464.7:rs17160826
1   1061152 rs12748370  T   C   .   PASS    AF=0.05 ES:SE:LP:AF:SS:ID   0.15:0.064:1.72125:0.05:8464.8:rs12748370
1   1061166 rs11807848  T   C   .   PASS    AF=0.412    ES:SE:LP:AF:SS:ID   0.03:0.037:0.387216:0.412:10549.2:rs11807848
1   1062638 rs9442373   C   A   .   PASS    AF=0.552    ES:SE:LP:AF:SS:ID   -0.018:0.037:0.200659:0.552:10450.5:rs9442373
1   1064535 rs6682475   G   C   .   PASS    AF=0.754    ES:SE:LP:AF:SS:ID   -0.096:0.05:1.26761:0.754:10001.2:rs6682475
1   1064979 rs2298217   C   T   .   PASS    AF=0.083    ES:SE:LP:AF:SS:ID   -0.01:0.051:0.0757207:0.083:8303:rs2298217
1   1066403 rs10907182  T   C   .   PASS    AF=0.675    ES:SE:LP:AF:SS:ID   0.0033:0.041:0.0268721:0.675:9874.43:rs10907182
1   1071118 rs10907183  G   C   .   PASS    AF=0.683    ES:SE:LP:AF:SS:ID   0.0061:0.043:0.05061:0.683:9729.69:rs10907183
1   1077064 rs4970357   C   A   .   PASS    AF=0.924    ES:SE:LP:AF:SS:ID   0.026:0.078:0.130768:0.924:8095.3:rs4970357
1   1087683 rs9442380   T   C   .   PASS    AF=0.912    ES:SE:LP:AF:SS:ID   -0.032:0.075:0.173925:0.912:8496.3:rs9442380
1   1106473 rs4970420   G   A   .   PASS    AF=0.144    ES:SE:LP:AF:SS:ID   -0.17:0.05:3.10791:0.144:8149:rs4970420
1   1121794 rs11260549  G   A   .   PASS    AF=0.125    ES:SE:LP:AF:SS:ID   -0.083:0.054:0.920819:0.125:8566:rs11260549
1   1124663 rs6684820   G   A   .   PASS    AF=0.267    ES:SE:LP:AF:SS:ID   0.013:0.034:0.161151:0.267:13702.5:rs6684820
1   1125553 rs10907174  A   T   .   PASS    AF=0.225    ES:SE:LP:AF:SS:ID   0.0017:0.037:0.0177288:0.225:12721.7:rs10907174
1   1129672 rs11260554  G   T   .   PASS    AF=0.125    ES:SE:LP:AF:SS:ID   -0.091:0.054:1.02687:0.125:8566:rs11260554
1   1130727 rs10907175  A   C   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   0.085:0.06:0.79588:0.1:8658.5:rs10907175
1   1135242 rs9729550   A   C   .   PASS    AF=0.275    ES:SE:LP:AF:SS:ID   0.011:0.033:0.124939:0.275:13770:rs9729550
1   1140435 rs1815606   G   T   .   PASS    AF=0.31 ES:SE:LP:AF:SS:ID   0.05:0.037:0.769551:0.31:10398.4:rs1815606
1   1152631 rs11721 C   A   .   PASS    AF=0.083    ES:SE:LP:AF:SS:ID   -0.038:0.061:0.267606:0.083:8602:rs11721
1   1156131 rs2887286   T   C   .   PASS    AF=0.183    ES:SE:LP:AF:SS:ID   0.078:0.041:1.23657:0.183:10572:rs2887286
1   1158277 rs3813199   G   A   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   0.015:0.059:0.102373:0.1:8944:rs3813199
1   1162435 rs3766186   C   A   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   0.0086:0.058:0.0555173:0.1:9321:rs3766186
1   1163804 rs7515488   C   T   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.014:0.045:0.124939:0.15:10895:rs7515488
1   1176597 rs6675798   T   C   .   PASS    AF=0.108    ES:SE:LP:AF:SS:ID   0.052:0.06:0.420216:0.108:9283:rs6675798
1   1181751 rs6603783   T   C   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   0.045:0.062:0.327902:0.1:8910.9:rs6603783