IEU GWAS QC Report

name	value
id	ukb-d-30290_irnt
trait	High light scatter reticulocyte percentage
category	Continuous
sample_size	344729
sex	Males and females
population	European
group_name	public
access	public
build	HG19/GRCh37
author	Neale lab
year	2018
mr	1
nsnp	13586218

name	value
gwas_id	ukb-d-30290_irnt
bcf_file	ukb-d-30290_irnt.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 07:21 BST
build_version	run_igd-8f4f4c9-2020-05-09

manhattan_plot

qq_plot

$af_plot$

af_plot

pz_plot

beta_std_plot

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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-30290_irnt/ukb-d-30290_irnt.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-30290_irnt/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 14:52:43 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30290_irnt/ukb-d-30290_irnt.vcf.gz ...
Read summary statistics for 13586217 SNPs.
Dropped 12711 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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1915 (0.0149)
Lambda GC: 1.6684
Mean Chi^2: 2.5101
Intercept: 1.1545 (0.0207)
Ratio: 0.1023 (0.0137)
Analysis finished at Mon Nov 25 14:55:01 2019
Total time elapsed: 2.0m:17.23s

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.4231,
    "mean_EFFECT": -0,
    "n": 344729,
    "n_snps": 13586217,
    "n_clumped_hits": 317,
    "n_p_sig": 79485,
    "n_mono": 0,
    "n_ns": 1251786,
    "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": 569217,
    "n_est": 346033.6692,
    "ratio_se_n": 1.0019,
    "mean_diff": 7.4554e-07,
    "ratio_diff": 1.0714,
    "sd_y_est1": 1.0017,
    "sd_y_est2": 1.0036,
    "r2_sum1": 0.1037,
    "r2_sum2": 0.1033,
    "r2_sum3": 0.1029,
    "r2_sum4": 0.103,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1915,
    "ldsc_observed_scale_h2_se": 0.0149,
    "ldsc_intercept_beta": 1.1545,
    "ldsc_intercept_se": 0.0207,
    "ldsc_lambda_gc": 1.6684,
    "ldsc_mean_chisq": 2.5101,
    "ldsc_ratio": 0.1023
}

name	value
name	value
af_correlation	FALSE
inflation_factor	TRUE
n	FALSE
is_snpid_non_unique	TRUE
mean_EFFECT_nonfinite	FALSE
mean_EFFECT_05	FALSE
mean_EFFECT_01	FALSE
mean_chisq	TRUE
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

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 $\beta_j$

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
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	13574170	0	NA	NA	NA	NA	NA	NA	NA	NA
character	REF	0	1.0000000	1	100	0	57082	0	NA	NA	NA	NA	NA	NA	NA	NA
character	ALT	0	1.0000000	1	342	0	33337	0	NA	NA	NA	NA	NA	NA	NA	NA
numeric	CHROM	0	1.0000000	NA	NA	NA	NA	NA	9.051358e+00	6.184962e+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	7.902498e+07	5.591474e+07	3.02000e+02	3.293100e+07	7.013848e+07	1.148588e+08	2.492309e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	-1.370000e-05	1.521400e-02	-2.54575e-01	-4.690900e-03	1.790000e-05	4.707800e-03	3.451240e-01	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	1.013780e-02	9.779400e-03	1.98280e-03	2.886200e-03	5.318700e-03	1.456810e-02	4.973670e-02	▇▂▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.413602e-01	3.050315e-01	0.00000e+00	1.620470e-01	4.210358e-01	7.053652e-01	1.000000e+00	▇▅▅▅▅
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.413597e-01	3.050318e-01	0.00000e+00	1.620464e-01	4.210353e-01	7.053646e-01	1.000000e+00	▇▅▅▅▅
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	1.908069e-01	2.544041e-01	1.00000e-03	7.430400e-03	6.003420e-02	2.953250e-01	9.989990e-01	▇▂▁▁▁
numeric	AF_reference	569217	0.9581033	NA	NA	NA	NA	NA	1.963367e-01	2.471015e-01	0.00000e+00	5.591000e-03	8.426520e-02	3.081070e-01	1.000000e+00	▇▂▁▁▁
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	3.447290e+05	0.000000e+00	3.44729e+05	3.447290e+05	3.447290e+05	3.447290e+05	3.447290e+05	▁▁▇▁▁

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
1	692794	rs530212009	CA	C	-0.0035773	0.0042249	0.3971568	0.3971559	0.1106300	0.1894970	344729
1	693731	rs12238997	A	G	-0.0013270	0.0039921	0.7395934	0.7395937	0.1158130	0.1417730	344729
1	707522	rs371890604	G	C	-0.0007096	0.0044901	0.8744251	0.8744245	0.0972243	0.1293930	344729
1	717587	rs144155419	G	A	-0.0099970	0.0106916	0.3497744	0.3497732	0.0157292	0.0045926	344729
1	723329	rs189787166	A	T	-0.0002754	0.0317653	0.9930830	0.9930834	0.0017197	0.0003994	344729
1	730087	rs148120343	T	C	-0.0049495	0.0055572	0.3731187	0.3731185	0.0564849	0.0127796	344729
1	731718	rs142557973	T	C	-0.0011673	0.0037860	0.7578478	0.7578460	0.1217300	0.1543530	344729
1	732032	rs61770163	A	C	-0.0013422	0.0040392	0.7396598	0.7396589	0.1211220	0.1555510	344729
1	734349	rs141242758	T	C	-0.0010175	0.0037880	0.7882283	0.7882278	0.1209620	0.1525560	344729
1	740284	rs61770167	C	T	0.0163122	0.0173439	0.3469549	0.3469534	0.0057743	0.0023962	344729

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
23	154923311	rs141127553	C	T	0.0080618	0.0043713	0.0651508	0.0651492	0.0561570	0.0309934	344729
23	154923374	rs111332691	T	A	0.0027883	0.0048041	0.5616529	0.5616529	0.0447961	0.0116556	344729
23	154925045	rs509981	C	T	-0.0074229	0.0023119	0.0013239	0.0013238	0.2456220	0.3634440	344729
23	154925895	rs538470	C	T	-0.0074949	0.0023648	0.0015275	0.0015274	0.2419530	0.3634440	344729
23	154927581	rs644138	G	A	-0.0046721	0.0021742	0.0316446	0.0316441	0.3021780	0.4635760	344729
23	154929412	rs557132	C	T	-0.0073429	0.0023126	0.0014973	0.0014972	0.2454760	0.3568210	344729
23	154929637	rs35185538	CT	C	-0.0067498	0.0024135	0.0051643	0.0051641	0.2297040	0.3011920	344729
23	154929952	rs4012982	CAA	C	-0.0075059	0.0024324	0.0020300	0.0020299	0.2394410	0.3165560	344729
23	154930230	rs781880	A	G	-0.0075588	0.0023121	0.0010786	0.0010785	0.2458870	0.3618540	344729
23	154930487	rs781879	T	A	0.0026977	0.0079371	0.7339424	0.7339423	0.0195262	0.1263580	344729

1   692794  rs530212009 CA  C   .   PASS    AF=0.11063  ES:SE:LP:AF:SS:ID   -0.00357728:0.00422491:0.401038:0.11063:344729:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115813 ES:SE:LP:AF:SS:ID   -0.00132695:0.00399213:0.131007:0.115813:344729:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972243    ES:SE:LP:AF:SS:ID   -0.000709626:0.00449014:0.0582774:0.0972243:344729:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157292    ES:SE:LP:AF:SS:ID   -0.00999696:0.0106916:0.456212:0.0157292:344729:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00171967   ES:SE:LP:AF:SS:ID   -0.000275366:0.0317653:0.00301445:0.00171967:344729:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564849    ES:SE:LP:AF:SS:ID   -0.00494954:0.00555724:0.428153:0.0564849:344729:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12173  ES:SE:LP:AF:SS:ID   -0.00116727:0.00378602:0.120418:0.12173:344729:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121122 ES:SE:LP:AF:SS:ID   -0.00134224:0.00403918:0.130968:0.121122:344729:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120962 ES:SE:LP:AF:SS:ID   -0.00101751:0.00378802:0.103348:0.120962:344729:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00577432   ES:SE:LP:AF:SS:ID   0.0163122:0.0173439:0.459727:0.00577432:344729:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018795    ES:SE:LP:AF:SS:ID   0.00604733:0.0327562:0.0687812:0.0018795:344729:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869782 ES:SE:LP:AF:SS:ID   0.00239511:0.00373487:0.282879:0.869782:344729:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153601   ES:SE:LP:AF:SS:ID   -0.0134034:0.033739:0.160414:0.00153601:344729:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122886 ES:SE:LP:AF:SS:ID   -0.00199068:0.00369834:0.228857:0.122886:344729:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142712 ES:SE:LP:AF:SS:ID   0.00049379:0.00365562:0.049367:0.142712:344729:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123004 ES:SE:LP:AF:SS:ID   -0.00203604:0.00369317:0.235503:0.123004:344729:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870907 ES:SE:LP:AF:SS:ID   0.000952343:0.00359906:0.101653:0.870907:344729:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875493 ES:SE:LP:AF:SS:ID   0.00117728:0.00365853:0.126324:0.875493:344729:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128617 ES:SE:LP:AF:SS:ID   -0.00186919:0.003608:0.218668:0.128617:344729:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363561    ES:SE:LP:AF:SS:ID   -0.0088756:0.00654687:0.756478:0.0363561:344729:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8705   ES:SE:LP:AF:SS:ID   0.00125533:0.00359526:0.138485:0.8705:344729:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870603 ES:SE:LP:AF:SS:ID   0.00129646:0.00359687:0.143562:0.870603:344729:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870495 ES:SE:LP:AF:SS:ID   0.00122567:0.00359511:0.134801:0.870495:344729:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00505869   ES:SE:LP:AF:SS:ID   -0.0101737:0.0184261:0.235931:0.00505869:344729:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00502542   ES:SE:LP:AF:SS:ID   -0.0102564:0.0184755:0.23747:0.00502542:344729:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558651   ES:SE:LP:AF:SS:ID   0.00834189:0.0178699:0.193389:0.00558651:344729:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870579 ES:SE:LP:AF:SS:ID   0.000871455:0.00358881:0.0925134:0.870579:344729:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125958 ES:SE:LP:AF:SS:ID   -0.00142752:0.00366211:0.156967:0.125958:344729:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870143 ES:SE:LP:AF:SS:ID   0.000809235:0.00358014:0.0855643:0.870143:344729:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869424 ES:SE:LP:AF:SS:ID   0.000836049:0.00357681:0.0887433:0.869424:344729:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870297 ES:SE:LP:AF:SS:ID   0.000786322:0.00358325:0.0828596:0.870297:344729:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870303 ES:SE:LP:AF:SS:ID   0.000782767:0.00358351:0.0824472:0.870303:344729:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870312 ES:SE:LP:AF:SS:ID   0.000797694:0.00358363:0.0841508:0.870312:344729:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870753 ES:SE:LP:AF:SS:ID   0.000969173:0.00359274:0.103834:0.870753:344729:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0987463    ES:SE:LP:AF:SS:ID   -0.000163993:0.00417693:0.0138188:0.0987463:344729:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00648112   ES:SE:LP:AF:SS:ID   0.0089057:0.0161401:0.235747:0.00648112:344729:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874658 ES:SE:LP:AF:SS:ID   0.00139314:0.00364629:0.153411:0.874658:344729:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864055 ES:SE:LP:AF:SS:ID   0.00106847:0.00357578:0.116289:0.864055:344729:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869438 ES:SE:LP:AF:SS:ID   0.000683462:0.00361046:0.0706536:0.869438:344729:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866397 ES:SE:LP:AF:SS:ID   0.000881124:0.00361142:0.0929952:0.866397:344729:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987143    ES:SE:LP:AF:SS:ID   0.000879878:0.00432468:0.0763525:0.0987143:344729:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871574 ES:SE:LP:AF:SS:ID   0.00160885:0.00365239:0.180732:0.871574:344729:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871574 ES:SE:LP:AF:SS:ID   0.00160926:0.00365239:0.180786:0.871574:344729:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871574 ES:SE:LP:AF:SS:ID   0.00162616:0.00365246:0.18299:0.871574:344729:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871945 ES:SE:LP:AF:SS:ID   0.00167576:0.00365454:0.189388:0.871945:344729:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125545 ES:SE:LP:AF:SS:ID   -0.0019301:0.00365731:0.223531:0.125545:344729:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105343 ES:SE:LP:AF:SS:ID   0.000671396:0.00398272:0.0624174:0.105343:344729:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855408 ES:SE:LP:AF:SS:ID   0.000579991:0.00357495:0.0599225:0.855408:344729:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00164172   ES:SE:LP:AF:SS:ID   -0.00623224:0.0318216:0.0732831:0.00164172:344729:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838258 ES:SE:LP:AF:SS:ID   -0.00394871:0.00351924:0.581949:0.838258:344729:rs376645387

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