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IEU GWAS information

Trait: Age at menopause.

name	value
id	ieu-a-1004
pmid	26414677
year	2015
mr	1
note	NULL
trait	Age at menopause
category	Risk factor
subcategory	Reproductive aging
population	European
sex	Females
ncase	NULL
ncontrol	NULL
sample_size	69360
nsnp	2418696
sd	3.93
priority	1
author	Day
group_name	public
access	public
build	HG19/GRCh37

Report information

name	value
gwas_id	ieu-a-1004
bcf_file	ieu-a-1004.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 13:00 BST
build_version	run_igd-8f4f4c9-2020-05-09

Summary

Summary {data-width=650}

Manhattan plot

$manhattan_plot$

manhattan_plot

QQ plot

qq_plot

AF plot

af_plot

P-Z plot

pz_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-1004/ieu-a-1004.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-1004/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 11:33:51 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1004/ieu-a-1004.vcf.gz ...
Read summary statistics for 2415893 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, 1146515 SNPs remain.
After merging with regression SNP LD, 1146515 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1893 (0.0137)
Lambda GC: 0.977
Mean Chi^2: 1.2923
Intercept: 1.0368 (0.0096)
Ratio: 0.1259 (0.0329)
Analysis finished at Wed Feb  5 11:34:20 2020
Total time elapsed: 28.93s

QC metrics

Metrics

{
    "af_correlation": 0.9152,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0,
    "n": 69360,
    "n_snps": 2415893,
    "n_clumped_hits": 42,
    "n_p_sig": 1208,
    "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": 19654,
    "n_est": 44460.8974,
    "ratio_se_n": 0.8006,
    "mean_diff": -0,
    "ratio_diff": 44.6001,
    "sd_y_est1": 4.6286,
    "sd_y_est2": 3.7058,
    "r2_sum1": 0.637,
    "r2_sum2": 0.0297,
    "r2_sum3": 0.0464,
    "r2_sum4": 0.0469,
    "ldsc_nsnp_merge_refpanel_ld": 1146515,
    "ldsc_nsnp_merge_regression_ld": 1146515,
    "ldsc_observed_scale_h2_beta": 0.1893,
    "ldsc_observed_scale_h2_se": 0.0137,
    "ldsc_intercept_beta": 1.0368,
    "ldsc_intercept_se": 0.0096,
    "ldsc_lambda_gc": 0.977,
    "ldsc_mean_chisq": 1.2923,
    "ldsc_ratio": 0.1259
}

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	TRUE
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	2415893	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	8.584573e+00	5.655200e+00	1.0000e+00	4.000000e+00	8.000000e+00	1.200000e+01	23.00	▇▅▅▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.884366e+07	5.565313e+07	1.1543e+04	3.268972e+07	7.025702e+07	1.143281e+08	249210707.00	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	4.020000e-05	3.794100e-02	-5.2000e-01	-2.000000e-02	0.000000e+00	2.000000e-02	0.88	▁▇▁▁▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	3.174310e-02	1.682670e-02	2.0000e-02	2.000000e-02	3.000000e-02	4.000000e-02	0.21	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.856034e-01	2.933971e-01	0.0000e+00	2.300001e-01	4.799997e-01	7.400005e-01	1.00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.815687e-01	3.094341e-01	0.0000e+00	1.824224e-01	5.049851e-01	7.388827e-01	1.00	▇▆▃▇▆
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	3.616448e-01	2.720218e-01	1.0000e-02	1.200000e-01	3.000000e-01	5.600000e-01	0.99	▇▅▃▃▂
numeric	AF_reference	19654	0.9918647	NA	NA	NA	NA	NA	3.641544e-01	2.541254e-01	1.9970e-04	1.503590e-01	3.033150e-01	5.479230e-01	1.00	▇▆▅▃▂
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	6.936000e+04	0.000000e+00	6.9360e+04	6.936000e+04	6.936000e+04	6.936000e+04	69360.00	▁▁▇▁▁

Head and tail

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
1	752566	rs3094315	G	A	0.01	0.05	0.8300000	0.8414806	0.83	0.718251	69360
1	777122	rs2980319	A	T	0.02	0.06	0.6700003	0.7388827	0.87	0.747204	69360
1	779322	rs4040617	A	G	-0.03	0.06	0.6300007	0.6170751	0.13	0.226438	69360
1	780785	rs2977612	T	A	0.03	0.06	0.6600001	0.6170751	0.86	0.669329	69360
1	785050	rs2905062	G	A	0.04	0.06	0.4899999	0.5049851	0.86	0.626997	69360
1	785989	rs2980300	T	C	0.03	0.06	0.5900000	0.6170751	0.85	0.626997	69360
1	990380	rs3121561	C	T	-0.02	0.03	0.5400003	0.5049851	0.29	0.343450	69360
1	998501	rs3813193	G	C	-0.04	0.04	0.2599998	0.3173105	0.17	0.206669	69360
1	1003629	rs4075116	C	T	-0.01	0.03	0.6600001	0.7388827	0.73	0.720647	69360
1	1005806	rs3934834	C	T	-0.03	0.03	0.4199997	0.3173105	0.16	0.223442	69360

CHROM	POS	ID	REF	ALT	EFFECT	SE	PVAL	PVAL_ztest	AF	AF_reference	N
22	51175626	rs3810648	A	G	-0.04	0.05	0.3800004	0.4237108	0.07	0.1084270	69360
22	51178090	rs2285395	G	A	-0.04	0.05	0.3800004	0.4237108	0.07	0.0666933	69360
22	51196164	rs8136603	A	T	-0.06	0.06	0.2700001	0.3173105	0.07	0.1427720	69360
22	51222100	rs114553188	G	T	-0.01	0.08	0.9000000	0.9005236	0.07	0.0880591	69360
22	51223637	rs375798137	G	A	-0.02	0.08	0.8300000	0.8025873	0.07	0.0788738	69360
23	35921591	rs2204667	C	G	-0.06	0.04	0.1400000	0.1336144	0.17	NA	69360
23	51666786	rs14115	A	G	0.10	0.05	0.0500000	0.0455003	0.02	NA	69360
23	70163799	rs1626496	A	C	0.03	0.05	0.5300002	0.5485062	0.07	NA	69360
23	91415872	rs6562597	G	A	0.08	0.11	0.4500005	0.4670589	0.01	0.0021192	69360
23	118495837	rs12882977	G	A	0.05	0.02	0.0460002	0.0124193	0.52	0.2307280	69360

bcf preview

1   752566  rs3094315   G   A   .   PASS    AF=0.83 ES:SE:LP:AF:SS:ID   0.01:0.05:0.0809219:0.83:69360:rs3094315
1   777122  rs2980319   A   T   .   PASS    AF=0.87 ES:SE:LP:AF:SS:ID   0.02:0.06:0.173925:0.87:69360:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.13 ES:SE:LP:AF:SS:ID   -0.03:0.06:0.200659:0.13:69360:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.86 ES:SE:LP:AF:SS:ID   0.03:0.06:0.180456:0.86:69360:rs2977612
1   785050  rs2905062   G   A   .   PASS    AF=0.86 ES:SE:LP:AF:SS:ID   0.04:0.06:0.309804:0.86:69360:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.85 ES:SE:LP:AF:SS:ID   0.03:0.06:0.229148:0.85:69360:rs2980300
1   990380  rs3121561   C   T   .   PASS    AF=0.29 ES:SE:LP:AF:SS:ID   -0.02:0.03:0.267606:0.29:69360:rs3121561
1   998501  rs3813193   G   C   .   PASS    AF=0.17 ES:SE:LP:AF:SS:ID   -0.04:0.04:0.585027:0.17:69360:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.73 ES:SE:LP:AF:SS:ID   -0.01:0.03:0.180456:0.73:69360:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.16 ES:SE:LP:AF:SS:ID   -0.03:0.03:0.376751:0.16:69360:rs3934834
1   1017170 rs3766193   C   G   .   PASS    AF=0.55 ES:SE:LP:AF:SS:ID   0:0.02:0.05061:0.55:69360:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.55 ES:SE:LP:AF:SS:ID   0:0.02:0.05061:0.55:69360:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.04:0.04:0.522879:0.15:69360:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.56 ES:SE:LP:AF:SS:ID   0.01:0.02:0.091515:0.56:69360:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.57 ES:SE:LP:AF:SS:ID   0.01:0.02:0.113509:0.57:69360:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.03:0.04:0.431798:0.15:69360:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.72 ES:SE:LP:AF:SS:ID   0:0.03:0.0268721:0.72:69360:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.03:0.04:0.318759:0.15:69360:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.72 ES:SE:LP:AF:SS:ID   0:0.03:0.0705811:0.72:69360:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.56 ES:SE:LP:AF:SS:ID   0.01:0.02:0.251812:0.56:69360:rs6701114
1   1026707 rs4074137   C   A   .   PASS    AF=0.6  ES:SE:LP:AF:SS:ID   0.04:0.03:0.823909:0.6:69360:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.16 ES:SE:LP:AF:SS:ID   -0.02:0.03:0.21467:0.16:69360:rs6687776
1   1030633 rs6678318   G   A   .   PASS    AF=0.16 ES:SE:LP:AF:SS:ID   -0.04:0.05:0.337242:0.16:69360:rs6678318
1   1031540 rs9651273   A   G   .   PASS    AF=0.73 ES:SE:LP:AF:SS:ID   0.03:0.04:0.431798:0.73:69360:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   -0.02:0.04:0.283997:0.11:69360:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.03:0.03:0.443698:0.15:69360:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.14 ES:SE:LP:AF:SS:ID   -0.03:0.03:0.49485:0.14:69360:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   -0.04:0.04:0.552842:0.11:69360:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.03:0.03:0.468521:0.15:69360:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   -0.03:0.04:0.387216:0.11:69360:rs4970409
1   1060608 rs17160824  G   A   .   PASS    AF=0.12 ES:SE:LP:AF:SS:ID   -0.03:0.04:0.443698:0.12:69360:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   -0.04:0.04:0.468521:0.11:69360:rs17160826
1   1061152 rs12748370  T   C   .   PASS    AF=0.11 ES:SE:LP:AF:SS:ID   -0.03:0.04:0.420216:0.11:69360:rs12748370
1   1061166 rs11807848  T   C   .   PASS    AF=0.42 ES:SE:LP:AF:SS:ID   -0.07:0.04:1.3279:0.42:69360:rs11807848
1   1062638 rs9442373   C   A   .   PASS    AF=0.54 ES:SE:LP:AF:SS:ID   0.07:0.04:1.38722:0.54:69360:rs9442373
1   1064535 rs6682475   G   C   .   PASS    AF=0.72 ES:SE:LP:AF:SS:ID   0.08:0.05:1.13668:0.72:69360:rs6682475
1   1064979 rs2298217   C   T   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.02:0.03:0.229148:0.15:69360:rs2298217
1   1077064 rs4970357   C   A   .   PASS    AF=0.91 ES:SE:LP:AF:SS:ID   0.01:0.04:0.0809219:0.91:69360:rs4970357
1   1087683 rs9442380   T   C   .   PASS    AF=0.92 ES:SE:LP:AF:SS:ID   0.02:0.04:0.161151:0.92:69360:rs9442380
1   1089262 rs4970358   A   G   .   PASS    AF=0.96 ES:SE:LP:AF:SS:ID   0.01:0.07:0.0861861:0.96:69360:rs4970358
1   1097335 rs9442385   T   G   .   PASS    AF=0.93 ES:SE:LP:AF:SS:ID   0.01:0.04:0.0555173:0.93:69360:rs9442385
1   1099342 rs9660710   A   C   .   PASS    AF=0.93 ES:SE:LP:AF:SS:ID   0:0.04:0.0315171:0.93:69360:rs9660710
1   1100217 rs1891905   C   T   .   PASS    AF=0.95 ES:SE:LP:AF:SS:ID   0.03:0.05:0.30103:0.95:69360:rs1891905
1   1120431 rs1320571   G   A   .   PASS    AF=0.04 ES:SE:LP:AF:SS:ID   -0.01:0.07:0.0655015:0.04:69360:rs1320571
1   1121014 rs3813204   G   A   .   PASS    AF=0.12 ES:SE:LP:AF:SS:ID   -0.04:0.06:0.244125:0.12:69360:rs3813204
1   1121794 rs11260549  G   A   .   PASS    AF=0.12 ES:SE:LP:AF:SS:ID   0:0.03:0.0555173:0.12:69360:rs11260549
1   1124663 rs6684820   G   A   .   PASS    AF=0.26 ES:SE:LP:AF:SS:ID   -0.01:0.02:0.200659:0.26:69360:rs6684820
1   1125553 rs10907174  A   T   .   PASS    AF=0.21 ES:SE:LP:AF:SS:ID   0:0.03:0.0362122:0.21:69360:rs10907174
1   1129672 rs11260554  G   T   .   PASS    AF=0.12 ES:SE:LP:AF:SS:ID   0:0.03:0.0268721:0.12:69360:rs11260554
1   1130727 rs10907175  A   C   .   PASS    AF=0.09 ES:SE:LP:AF:SS:ID   0.02:0.04:0.167491:0.09:69360:rs10907175