IEU GWAS QC Report

name	value
id	ieu-a-1097
pmid	26631737
year	2015
mr	1
note	NULL
trait	Microalbuminuria
category	Risk factor
subcategory	Kidney
population	European
sex	Males and females
ncase	NULL
ncontrol	NULL
sample_size	54116
nsnp	2191461
sd	NULL
priority	1
author	Teumer
group_name	public
access	public
build	HG19/GRCh37

name	value
gwas_id	ieu-a-1097
bcf_file	ieu-a-1097.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 03:37 BST
build_version	run_igd-8f4f4c9-2020-05-09

manhattan_plot

qq_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/ieu-a-import/processed/ieu-a-1097/ieu-a-1097.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-1097/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 18:45:40 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1097/ieu-a-1097.vcf.gz ...
Read summary statistics for 2189106 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, 1068054 SNPs remain.
After merging with regression SNP LD, 1068054 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0151 (0.0079)
Lambda GC: 1.0219
Mean Chi^2: 1.0227
Intercept: 1.0062 (0.0066)
Ratio: 0.2747 (0.2924)
Analysis finished at Tue Feb  4 18:46:10 2020
Total time elapsed: 30.34s

{
    "af_correlation": 0.901,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 0.0011,
    "n": 54117,
    "n_snps": 2189106,
    "n_clumped_hits": 1,
    "n_p_sig": 4,
    "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": 667,
    "n_miss_AF_reference": 18494,
    "n_est": 51432.8921,
    "ratio_se_n": 0.9749,
    "mean_diff": -0.0008,
    "ratio_diff": 39.3609,
    "sd_y_est1": 3.5226,
    "sd_y_est2": 3.4341,
    "r2_sum1": 0.0088,
    "r2_sum2": 0.0007,
    "r2_sum3": 0.0007,
    "r2_sum4": 0.0008,
    "ldsc_nsnp_merge_refpanel_ld": 1068054,
    "ldsc_nsnp_merge_regression_ld": 1068054,
    "ldsc_observed_scale_h2_beta": 0.0151,
    "ldsc_observed_scale_h2_se": 0.0079,
    "ldsc_intercept_beta": 1.0062,
    "ldsc_intercept_se": 0.0066,
    "ldsc_lambda_gc": 1.0219,
    "ldsc_mean_chisq": 1.0227,
    "ldsc_ratio": 0.2731
}

name	value
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

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	42	0	2189106	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	8.601266e+00	5.664296e+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	7.872410e+07	5.573647e+07	1.1523e+04	3.243768e+07	7.008198e+07	1.143619e+08	2.491808e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	1.130600e-03	2.997200e-02	-6.0000e-01	-1.700000e-02	8.000000e-04	1.900000e-02	6.600000e-01	▁▁▇▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	2.818870e-02	9.332200e-03	2.0000e-02	2.200000e-02	2.500000e-02	3.200000e-02	5.500000e-01	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.965725e-01	2.894816e-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	4.965821e-01	2.895136e-01	0.0000e+00	2.451696e-01	4.953539e-01	7.469018e-01	1.000000e+00	▇▇▇▇▇
numeric	AF	667	0.9996953	NA	NA	NA	NA	NA	3.809774e-01	2.563922e-01	4.0000e-03	1.590000e-01	3.250000e-01	5.740000e-01	9.960000e-01	▇▆▅▃▂
numeric	AF_reference	18494	0.9915518	NA	NA	NA	NA	NA	3.807007e-01	2.426620e-01	1.9970e-04	1.773160e-01	3.294730e-01	5.593050e-01	1.000000e+00	▇▇▅▃▂
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	5.296598e+04	3.244800e+03	1.3023e+04	5.317500e+04	5.411400e+04	5.411600e+04	5.411700e+04	▁▁▁▁▇

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	723819	rs11804171	T	A	-0.0170	0.075	0.8200001	0.8206829	0.034	0.1345850	33681
1	723891	rs2977670	G	C	-0.0009	0.061	0.9900000	0.9882284	0.934	0.7799520	30474
1	752566	rs3094315	G	A	0.0480	0.032	0.1400000	0.1336144	0.835	0.7182510	43757
1	754192	rs3131968	A	G	0.0880	0.038	0.0210000	0.0205698	0.885	0.6785140	42894
1	765948	rs2519016	C	T	0.0047	0.370	0.9900000	0.9898650	0.950	NA	23918
1	768448	rs12562034	G	A	0.1900	0.083	0.0230001	0.0220703	0.102	0.1918930	34752
1	775659	rs2905035	A	G	0.0780	0.035	0.0259998	0.0258424	0.885	0.7450080	50973
1	776546	rs12124819	A	G	0.0710	0.053	0.1800002	0.1803681	0.288	0.0756789	50514
1	777122	rs2980319	A	T	0.0820	0.032	0.0109999	0.0103922	0.866	0.7472040	54116
1	779322	rs4040617	A	G	-0.0830	0.038	0.0309999	0.0289468	0.133	0.2264380	41683

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
22	51212875	rs2238837	A	C	0.0110	0.029	0.6999999	0.7044574	0.385	0.3724040	40059
22	51216564	rs9616970	T	C	0.1100	0.044	0.0097000	0.0124193	0.146	0.1563500	38261
22	51217134	rs117417021	A	G	0.0390	0.034	0.2500000	0.2513573	0.415	0.2671730	34660
22	51222100	rs114553188	G	T	0.1100	0.064	0.0929994	0.0856599	0.062	0.0880591	35073
22	51223637	rs375798137	G	A	0.1100	0.063	0.0769999	0.0808054	0.062	0.0788738	36058
22	51229805	rs9616985	T	C	0.0270	0.065	0.6800001	0.6778604	0.092	0.0730831	38081
23	35921591	rs2204667	C	G	0.0470	0.028	0.0980009	0.0932356	0.162	NA	54107
23	51666786	rs14115	A	G	0.0083	0.048	0.8600001	0.8627169	0.027	NA	42331
23	70163799	rs1626496	A	C	0.0360	0.040	0.3599996	0.3681203	0.069	NA	54116
23	118495837	rs12882977	G	A	0.0092	0.022	0.6700003	0.6758142	0.508	0.2307280	51913

1   723819  rs11804171  T   A   .   PASS    AF=0.034    ES:SE:LP:AF:SS:ID   -0.017:0.075:0.0861861:0.034:33681:rs11804171
1   723891  rs2977670   G   C   .   PASS    AF=0.934    ES:SE:LP:AF:SS:ID   -0.0009:0.061:0.00436481:0.934:30474:rs2977670
1   752566  rs3094315   G   A   .   PASS    AF=0.835    ES:SE:LP:AF:SS:ID   0.048:0.032:0.853872:0.835:43757:rs3094315
1   754192  rs3131968   A   G   .   PASS    AF=0.885    ES:SE:LP:AF:SS:ID   0.088:0.038:1.67778:0.885:42894:rs3131968
1   765948  rs2519016   C   T   .   PASS    AF=0.95 ES:SE:LP:AF:SS:ID   0.0047:0.37:0.00436481:0.95:23918:rs2519016
1   768448  rs12562034  G   A   .   PASS    AF=0.102    ES:SE:LP:AF:SS:ID   0.19:0.083:1.63827:0.102:34752:rs12562034
1   775659  rs2905035   A   G   .   PASS    AF=0.885    ES:SE:LP:AF:SS:ID   0.078:0.035:1.58503:0.885:50973:rs2905035
1   776546  rs12124819  A   G   .   PASS    AF=0.288    ES:SE:LP:AF:SS:ID   0.071:0.053:0.744727:0.288:50514:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.866    ES:SE:LP:AF:SS:ID   0.082:0.032:1.95861:0.866:54116:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.133    ES:SE:LP:AF:SS:ID   -0.083:0.038:1.50864:0.133:41683:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.877    ES:SE:LP:AF:SS:ID   0.087:0.038:1.63827:0.877:42888:rs2977612
1   785050  rs2905062   G   A   .   PASS    AF=0.868    ES:SE:LP:AF:SS:ID   0.086:0.038:1.63827:0.868:43828:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.868    ES:SE:LP:AF:SS:ID   0.071:0.034:1.48149:0.868:45926:rs2980300
1   798026  rs4951864   C   T   .   PASS    AF=0.9  ES:SE:LP:AF:SS:ID   -0.15:0.077:1.33724:0.9:34753:rs4951864
1   798801  rs12132517  G   A   .   PASS    AF=0.108    ES:SE:LP:AF:SS:ID   0.15:0.077:1.3098:0.108:33813:rs12132517
1   798959  rs11240777  G   A   .   PASS    AF=0.219    ES:SE:LP:AF:SS:ID   -0.033:0.034:0.49485:0.219:52717:rs11240777
1   846864  rs950122    G   C   .   PASS    AF=0.138    ES:SE:LP:AF:SS:ID   -0.028:0.073:0.154902:0.138:41094:rs950122
1   882033  rs2272756   G   A   .   PASS    AF=0.23 ES:SE:LP:AF:SS:ID   -0.0022:0.046:0.0177288:0.23:48337:rs2272756
1   962210  rs3128126   A   G   .   PASS    AF=0.415    ES:SE:LP:AF:SS:ID   -0.058:0.043:0.769551:0.415:50514:rs3128126
1   990380  rs3121561   C   T   .   PASS    AF=0.254    ES:SE:LP:AF:SS:ID   -0.023:0.039:0.259637:0.254:49554:rs3121561
1   998501  rs3813193   G   C   .   PASS    AF=0.146    ES:SE:LP:AF:SS:ID   -0.0069:0.052:0.0457575:0.146:48337:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.734    ES:SE:LP:AF:SS:ID   0.043:0.025:1.04576:0.734:51930:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.124    ES:SE:LP:AF:SS:ID   -0.016:0.042:0.154902:0.124:50540:rs3934834
1   1017170 rs3766193   C   G   .   PASS    AF=0.587    ES:SE:LP:AF:SS:ID   0.024:0.024:0.49485:0.587:54116:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.571    ES:SE:LP:AF:SS:ID   0.026:0.024:0.585027:0.571:54115:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.124    ES:SE:LP:AF:SS:ID   -0.018:0.042:0.173925:0.124:50539:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.608    ES:SE:LP:AF:SS:ID   0.026:0.023:0.585027:0.608:54116:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.588    ES:SE:LP:AF:SS:ID   0.025:0.023:0.568636:0.588:54113:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.137    ES:SE:LP:AF:SS:ID   -0.018:0.042:0.173925:0.137:50540:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.735    ES:SE:LP:AF:SS:ID   0.038:0.027:0.823909:0.735:54116:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.112    ES:SE:LP:AF:SS:ID   -0.011:0.044:0.091515:0.112:48337:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.726    ES:SE:LP:AF:SS:ID   0.033:0.027:0.657577:0.726:51937:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.585    ES:SE:LP:AF:SS:ID   0.03:0.026:0.619789:0.585:52718:rs6701114
1   1025301 rs9442400   T   C   .   PASS    AF=0.952    ES:SE:LP:AF:SS:ID   0.014:0.12:0.0457575:0.952:29375:rs9442400
1   1026707 rs4074137   C   A   .   PASS    AF=0.623    ES:SE:LP:AF:SS:ID   0.049:0.035:0.79588:0.623:50515:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.133    ES:SE:LP:AF:SS:ID   -0.037:0.038:0.481486:0.133:50540:rs6687776
1   1030633 rs6678318   G   A   .   PASS    AF=0.134    ES:SE:LP:AF:SS:ID   -0.049:0.042:0.619789:0.134:42714:rs6678318
1   1031540 rs9651273   A   G   .   PASS    AF=0.717    ES:SE:LP:AF:SS:ID   0.018:0.033:0.229148:0.717:51733:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.046    ES:SE:LP:AF:SS:ID   -0.049:0.042:0.619789:0.046:50540:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.115    ES:SE:LP:AF:SS:ID   -0.044:0.039:0.585027:0.115:50540:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.062    ES:SE:LP:AF:SS:ID   -0.06:0.045:0.744727:0.062:50539:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.088    ES:SE:LP:AF:SS:ID   -0.035:0.042:0.387216:0.088:50540:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.115    ES:SE:LP:AF:SS:ID   -0.06:0.044:0.769551:0.115:50540:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.093    ES:SE:LP:AF:SS:ID   -0.066:0.049:0.744727:0.093:49600:rs4970409
1   1060174 rs7548798   C   T   .   PASS    AF=0.314    ES:SE:LP:AF:SS:ID   -0.016:0.044:0.142668:0.314:40424:rs7548798
1   1060608 rs17160824  G   A   .   PASS    AF=0.097    ES:SE:LP:AF:SS:ID   -0.06:0.048:0.677781:0.097:50540:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.051    ES:SE:LP:AF:SS:ID   -0.066:0.049:0.744727:0.051:50540:rs17160826
1   1061152 rs12748370  T   C   .   PASS    AF=0.055    ES:SE:LP:AF:SS:ID   -0.075:0.051:0.853872:0.055:49600:rs12748370
1   1061166 rs11807848  T   C   .   PASS    AF=0.389    ES:SE:LP:AF:SS:ID   -0.043:0.034:0.677781:0.389:52718:rs11807848
1   1062638 rs9442373   C   A   .   PASS    AF=0.575    ES:SE:LP:AF:SS:ID   0.026:0.034:0.366532:0.575:52718:rs9442373

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