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/public/UKB-b-16639/UKB-b-16639_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16639/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:13 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16639/UKB-b-16639_data.vcf.gz ...
Read summary statistics for 1458442 SNPs.
Dropped 126 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 377397 SNPs remain.
After merging with regression SNP LD, 377397 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0044 (0.0098)
Lambda GC: 1.0176
Mean Chi^2: 1.0181
Intercept: 1.0111 (0.0115)
Ratio: 0.6145 (0.6324)
Analysis finished at Thu Oct 17 14:45:39 2019
Total time elapsed: 26.14s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.5812,
    "inflation_factor": 1,
    "mean_EFFECT": 1.5451e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 11639,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 377397,
    "ldsc_nsnp_merge_regression_ld": 377397,
    "ldsc_observed_scale_h2_beta": 0.0044,
    "ldsc_observed_scale_h2_se": 0.0098,
    "ldsc_intercept_beta": 1.0111,
    "ldsc_intercept_se": 0.0115,
    "ldsc_lambda_gc": 1.0176,
    "ldsc_mean_chisq": 1.0181,
    "ldsc_ratio": 0.6133
}
 

Flags

name value
af_correlation TRUE
inflation_factor FALSE
n TRUE
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 TRUE
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 logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 4 58 0 1458318 0 NA NA 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 NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 1458442 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.677081e+00 5.767979e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.854419e+07 5.656875e+07 1.23330e+04 3.164011e+07 6.903374e+07 1.145266e+08 2.491722e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.500000e-06 7.199000e-04 -3.36710e-03 -4.844000e-04 1.300000e-06 4.869000e-04 3.424600e-03 ▁▂▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.132000e-04 1.890000e-05 6.72600e-04 7.012000e-04 7.092000e-04 7.220000e-04 1.334000e-03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.972319e-01 2.897081e-01 4.70000e-06 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.972316e-01 2.896819e-01 4.70000e-06 2.452939e-01 4.955758e-01 7.478041e-01 9.999987e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.828393e-01 9.381870e-02 3.36539e-01 4.003230e-01 4.743180e-01 5.607070e-01 6.634610e-01 ▇▇▆▆▅
numeric AF_reference 11639 0.9920196 NA NA NA NA NA NA NA 4.610105e-01 1.440780e-01 1.99700e-04 3.534350e-01 4.552720e-01 5.638980e-01 1.000000e+00 ▁▆▇▃▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C -0.0009616 0.0012396 0.4400003 0.4379054 0.623812 0.782149 NA
1 54676 rs2462492 C T 0.0027436 0.0012360 0.0259998 0.0264374 0.399144 NA NA
1 91536 rs6702460 G T 0.0006634 0.0012157 0.5900000 0.5852504 0.455916 0.420727 NA
1 706368 rs55727773 A G 0.0007472 0.0008570 0.3800004 0.3832905 0.513304 0.275160 NA
1 814495 rs74461805 C A -0.0002222 0.0011735 0.8499999 0.8497970 0.340108 NA NA
1 840753 rs4970382 T C -0.0008962 0.0007117 0.2099999 0.2079309 0.400406 0.468850 NA
1 843405 rs11516185 A G 0.0006897 0.0008854 0.4400003 0.4359895 0.362367 0.375399 NA
1 850218 rs6664536 T A -0.0000096 0.0007078 0.9900000 0.9891499 0.589315 0.345248 NA
1 850371 rs6679046 G T 0.0001842 0.0007112 0.8000000 0.7956770 0.603035 0.508786 NA
1 850780 rs6657440 C T 0.0001854 0.0007112 0.7899998 0.7943096 0.603381 0.560304 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51158017 rs6010065 G C 0.0003217 0.0006978 0.6400000 0.6447349 0.459676 0.547524 NA
22 51158499 rs8136930 T G 0.0003323 0.0006983 0.6300007 0.6341281 0.459892 0.544728 NA
22 51161019 rs5770994 C T -0.0001873 0.0006958 0.7899998 0.7877974 0.483487 0.425719 NA
22 51163039 rs715584 G T 0.0004587 0.0007063 0.5199996 0.5160707 0.425020 0.473642 NA
22 51164109 rs5770995 G C 0.0002713 0.0007028 0.6999999 0.6995017 0.450784 0.510982 NA
22 51164115 rs5770996 C T 0.0004222 0.0007024 0.5500004 0.5477657 0.454945 0.514776 NA
22 51174048 rs9628245 G C 0.0001232 0.0007962 0.8800001 0.8770337 0.377819 0.433107 NA
22 51186143 rs2879914 T C -0.0012986 0.0007504 0.0840001 0.0835175 0.380077 0.273363 NA
22 51186228 rs3865766 C T -0.0007913 0.0007309 0.2800000 0.2789444 0.449547 0.453275 NA
22 51197266 rs61290853 A G -0.0008212 0.0007532 0.2800000 0.2755533 0.386693 0.422923 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623812 ES:SE:LP:AF:ID  -0.000961609:0.00123961:0.356547:0.623812:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399144 ES:SE:LP:AF:ID  0.00274358:0.001236:1.58503:0.399144:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.455916 ES:SE:LP:AF:ID  0.000663446:0.0012157:0.229148:0.455916:rs6702460
1   706368  rs12029736  A   G   .   PASS    AF=0.513304 ES:SE:LP:AF:ID  0.000747154:0.000856976:0.420216:0.513304:rs12029736
1   814495  rs74461805  C   A   .   PASS    AF=0.340108 ES:SE:LP:AF:ID  -0.000222242:0.00117354:0.0705811:0.340108:rs74461805
1   840753  rs4970382   T   C   .   PASS    AF=0.400406 ES:SE:LP:AF:ID  -0.000896181:0.000711664:0.677781:0.400406:rs4970382
1   843405  rs11516185  A   G   .   PASS    AF=0.362367 ES:SE:LP:AF:ID  0.000689736:0.000885431:0.356547:0.362367:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.589315 ES:SE:LP:AF:ID  -9.62543e-06:0.000707806:0.00436481:0.589315:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603035 ES:SE:LP:AF:ID  0.00018416:0.000711191:0.09691:0.603035:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603381 ES:SE:LP:AF:ID  0.000185424:0.000711204:0.102373:0.603381:rs6657440
1   852037  rs4970463   G   A   .   PASS    AF=0.588673 ES:SE:LP:AF:ID  4.64599e-05:0.000708815:0.0222764:0.588673:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.588649 ES:SE:LP:AF:ID  9.71002e-07:0.000708496:-0:0.588649:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.606715 ES:SE:LP:AF:ID  0.000328373:0.000712374:0.19382:0.606715:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.60688  ES:SE:LP:AF:ID  0.000351054:0.000712448:0.207608:0.60688:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.609504 ES:SE:LP:AF:ID  0.000246514:0.000713161:0.136677:0.609504:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.602505 ES:SE:LP:AF:ID  0.000225688:0.000711315:0.124939:0.602505:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.609473 ES:SE:LP:AF:ID  0.000256477:0.000713066:0.142668:0.609473:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.390835 ES:SE:LP:AF:ID  -0.000252145:0.000713356:0.142668:0.390835:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.390777 ES:SE:LP:AF:ID  -0.000265597:0.000713429:0.148742:0.390777:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.352504 ES:SE:LP:AF:ID  -0.000649581:0.000732315:0.420216:0.352504:rs4040605
1   866893  rs2880024   T   C   .   PASS    AF=0.608083 ES:SE:LP:AF:ID  0.000510783:0.000719665:0.318759:0.608083:rs2880024
1   875770  rs4970379   A   G   .   PASS    AF=0.598464 ES:SE:LP:AF:ID  0.000219129:0.000725047:0.119186:0.598464:rs4970379
1   881627  rs2272757   G   A   .   PASS    AF=0.65048  ES:SE:LP:AF:ID  0.000478395:0.00073243:0.29243:0.65048:rs2272757
1   891059  rs13303065  C   T   .   PASS    AF=0.650626 ES:SE:LP:AF:ID  0.000470034:0.000732358:0.283997:0.650626:rs13303065
1   891945  rs13303106  A   G   .   PASS    AF=0.650689 ES:SE:LP:AF:ID  0.000500967:0.000733196:0.309804:0.650689:rs13303106
1   903245  rs28690976  A   G   .   PASS    AF=0.565133 ES:SE:LP:AF:ID  0.000278822:0.000728055:0.154902:0.565133:rs28690976
1   909073  rs3892467   C   T   .   PASS    AF=0.386217 ES:SE:LP:AF:ID  0.000988548:0.000726534:0.769551:0.386217:rs3892467
1   909238  rs3829740   G   C   .   PASS    AF=0.572164 ES:SE:LP:AF:ID  0.00112603:0.000702882:0.958607:0.572164:rs3829740
1   912049  rs7367995   T   C   .   PASS    AF=0.585242 ES:SE:LP:AF:ID  0.00011384:0.000709697:0.0604807:0.585242:rs7367995
1   913889  rs2340596   G   A   .   PASS    AF=0.600025 ES:SE:LP:AF:ID  -7.68789e-06:0.000711108:0.00436481:0.600025:rs2340596
1   914333  rs13302979  C   G   .   PASS    AF=0.60338  ES:SE:LP:AF:ID  0.000176067:0.00071352:0.091515:0.60338:rs13302979
1   914852  rs13303368  G   C   .   PASS    AF=0.60101  ES:SE:LP:AF:ID  -1.08239e-05:0.000712207:0.00436481:0.60101:rs13303368
1   914940  rs13303033  T   C   .   PASS    AF=0.585327 ES:SE:LP:AF:ID  -0.00021184:0.000708663:0.119186:0.585327:rs13303033
1   916834  rs6694632   G   A   .   PASS    AF=0.590116 ES:SE:LP:AF:ID  -9.82875e-05:0.000709637:0.05061:0.590116:rs6694632
1   918384  rs13303118  G   T   .   PASS    AF=0.585329 ES:SE:LP:AF:ID  -0.000221342:0.000708398:0.124939:0.585329:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.590348 ES:SE:LP:AF:ID  -0.000103208:0.000709139:0.0555173:0.590348:rs2341354
1   919501  rs4970414   G   T   .   PASS    AF=0.583818 ES:SE:LP:AF:ID  -0.000637405:0.000735333:0.408935:0.583818:rs4970414
1   921716  rs13303278  C   A   .   PASS    AF=0.569359 ES:SE:LP:AF:ID  -0.00062222:0.000709787:0.420216:0.569359:rs13303278
1   924528  rs34712273  C   A   .   PASS    AF=0.579293 ES:SE:LP:AF:ID  -0.000364633:0.000712534:0.21467:0.579293:rs34712273
1   930533  rs3128110   C   G   .   PASS    AF=0.384463 ES:SE:LP:AF:ID  0.000574096:0.000722114:0.366532:0.384463:rs3128110
1   930567  rs3121574   A   G   .   PASS    AF=0.384502 ES:SE:LP:AF:ID  0.000571696:0.000722141:0.366532:0.384502:rs3121574
1   930751  rs3128111   C   G   .   PASS    AF=0.383433 ES:SE:LP:AF:ID  0.000601307:0.000722788:0.387216:0.383433:rs3128111
1   931166  rs2710880   A   G   .   PASS    AF=0.385119 ES:SE:LP:AF:ID  0.000618307:0.000722322:0.408935:0.385119:rs2710880
1   931362  rs2799060   G   A   .   PASS    AF=0.383925 ES:SE:LP:AF:ID  0.000632191:0.000722832:0.420216:0.383925:rs2799060
1   933790  rs9442392   G   A   .   PASS    AF=0.579341 ES:SE:LP:AF:ID  -0.000485936:0.000711879:0.309804:0.579341:rs9442392
1   936111  rs1936360   C   T   .   PASS    AF=0.574447 ES:SE:LP:AF:ID  -0.000573731:0.000711926:0.376751:0.574447:rs1936360
1   940005  rs2799056   A   G   .   PASS    AF=0.396767 ES:SE:LP:AF:ID  0.000377232:0.000720124:0.221849:0.396767:rs2799056
1   940096  rs4503294   C   T   .   PASS    AF=0.56692  ES:SE:LP:AF:ID  -0.000314952:0.000709776:0.180456:0.56692:rs4503294
1   941284  rs3128116   C   T   .   PASS    AF=0.39488  ES:SE:LP:AF:ID  0.000441093:0.000720085:0.267606:0.39488:rs3128116
1   941334  rs57683598  G   A   .   PASS    AF=0.394898 ES:SE:LP:AF:ID  0.000439177:0.000720082:0.267606:0.394898:rs57683598