IEU GWAS QC Report

name	value
id	ieu-a-300
pmid	24097068
year	2013
mr	1
note	NULL
trait	LDL cholesterol
category	Risk factor
subcategory	Lipid
population	Mixed
sex	Males and females
ncase	NULL
ncontrol	NULL
sample_size	173082
nsnp	2437752
sd	38.6745912
priority	1
author	Willer CJ
group_name	public
access	public
build	HG19/GRCh37

name	value
gwas_id	ieu-a-300
bcf_file	ieu-a-300.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-10 10:29 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-300/ieu-a-300.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-300/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 11:01:47 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-300/ieu-a-300.vcf.gz ...
Read summary statistics for 2414488 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, 1130360 SNPs remain.
After merging with regression SNP LD, 1130360 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.219 (0.0373)
Lambda GC: 1.103
Mean Chi^2: 1.2912
Intercept: 0.9615 (0.0082)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Wed Feb  5 11:02:16 2020
Total time elapsed: 28.84s

{
    "af_correlation": 0.9289,
    "inflation_factor": 1.015,
    "mean_EFFECT": 0,
    "n": 173082,
    "n_snps": 2414488,
    "n_clumped_hits": 81,
    "n_p_sig": 3023,
    "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": 365462,
    "n_miss_AF_reference": 19039,
    "n_est": 173180.4309,
    "ratio_se_n": 1.0003,
    "mean_diff": -0,
    "ratio_diff": 11.7627,
    "sd_y_est1": 1.5506,
    "sd_y_est2": 1.551,
    "r2_sum1": 0.0976,
    "r2_sum2": 0.0406,
    "r2_sum3": 0.0406,
    "r2_sum4": 0.0713,
    "ldsc_nsnp_merge_refpanel_ld": 1130360,
    "ldsc_nsnp_merge_regression_ld": 1130360,
    "ldsc_observed_scale_h2_beta": 0.219,
    "ldsc_observed_scale_h2_se": 0.0373,
    "ldsc_intercept_beta": 0.9615,
    "ldsc_intercept_se": 0.0082,
    "ldsc_lambda_gc": 1.103,
    "ldsc_mean_chisq": 1.2912,
    "ldsc_ratio": -0.1322
}

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	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	34	0	2414488	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	8.581079e+00	5.646344e+00	1.0000e+00	4.000000e+00	8.000000e+00	1.200000e+01	2.20000e+01	▇▅▅▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.874467e+07	5.562891e+07	1.1523e+04	3.255216e+07	7.009844e+07	1.141154e+08	2.49219e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	4.200000e-05	1.004410e-02	-5.8980e-01	-5.100000e-03	0.000000e+00	5.100000e-03	2.25100e-01	▁▁▁▇▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	8.205500e-03	4.540000e-03	3.6000e-03	5.500000e-03	6.500000e-03	8.900000e-03	8.10000e-02	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	4.964218e-01	2.911325e-01	0.0000e+00	2.435000e-01	4.968005e-01	7.489003e-01	1.00000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	4.830707e-01	2.947802e-01	0.0000e+00	2.234554e-01	4.782681e-01	7.388827e-01	1.00000e+00	▇▇▇▇▇
numeric	AF	365462	0.8486379	NA	NA	NA	NA	NA	3.570397e-01	2.695278e-01	1.3190e-03	1.240000e-01	2.916000e-01	5.528000e-01	9.98681e-01	▇▅▃▂▂
numeric	AF_reference	19039	0.9921147	NA	NA	NA	NA	NA	3.600429e-01	2.550363e-01	0.0000e+00	1.461660e-01	2.977240e-01	5.431310e-01	1.00000e+00	▇▆▃▃▂
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	9.043977e+04	1.599197e+04	5.0000e+04	8.774800e+04	8.987200e+04	8.988800e+04	1.73082e+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	721290	rs12565286	G	C	-0.0325	0.0194	0.0629506	0.0938837	0.04354	0.0371406	54632.1
1	752566	rs3094315	G	A	0.0156	0.0100	0.2678003	0.1187599	0.83640	0.7182510	52845.0
1	785050	rs2905062	G	A	0.0178	0.0075	0.0273798	0.0176283	0.86680	0.6269970	91375.0
1	998501	rs3813193	G	C	0.0228	0.0114	0.0380996	0.0455003	NA	0.2066690	52355.0
1	1003629	rs4075116	C	T	-0.0056	0.0077	0.5489996	0.4670589	0.73610	0.7206470	76604.0
1	1005806	rs3934834	C	T	0.0180	0.0102	0.0618999	0.0776132	0.15960	0.2234420	52355.0
1	1017170	rs3766193	C	G	-0.0022	0.0071	0.6568996	0.7566681	NA	0.5754790	85956.0
1	1017197	rs3766192	C	T	-0.0079	0.0067	0.2506000	0.2383566	0.54880	0.5111820	85956.0
1	1017587	rs3766191	C	T	0.0243	0.0114	0.0290703	0.0330415	0.15040	0.1711260	52355.0
1	1018562	rs9442371	C	T	-0.0046	0.0066	0.4490999	0.4858218	0.56200	0.5301520	85956.0

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	51151724	rs6010061	C	T	0.0113	0.0063	0.1097001	0.0728689	0.42080	0.6098240	88430
22	51156933	rs6010063	A	G	0.0038	0.0055	0.7198997	0.4896227	0.40770	0.4960060	86052
22	51158017	rs6010065	G	C	0.0043	0.0054	0.6787002	0.4258598	NA	0.5475240	87745
22	51163138	rs715586	C	T	-0.0100	0.0055	0.0631001	0.0690363	0.12140	0.0902556	168367
22	51165664	rs8137951	G	A	0.0085	0.0041	0.0589603	0.0381564	0.28100	0.4063500	170259
22	51171693	rs756638	G	A	0.0026	0.0069	0.3906996	0.7063136	0.25990	0.3049120	79275
22	51175626	rs3810648	A	G	-0.0109	0.0110	0.4219996	0.3217300	0.05277	0.1084270	86029
22	51178090	rs2285395	G	A	-0.0015	0.0080	0.8746001	0.8512686	0.05145	0.0666933	164950
22	51196164	rs8136603	A	T	-0.0204	0.0134	0.1546999	0.1279119	NA	0.1427720	87745
22	51212875	rs2238837	A	C	0.0134	0.0084	0.1088000	0.1106590	0.22690	0.3724040	70351

1   721290  rs12565286  G   C   .   PASS    AF=0.04354  ES:SE:LP:AF:SS:ID   -0.0325:0.0194:1.201:0.04354:54632.1:rs12565286
1   752566  rs3094315   G   A   .   PASS    AF=0.8364   ES:SE:LP:AF:SS:ID   0.0156:0.01:0.572189:0.8364:52845:rs3094315
1   785050  rs2905062   G   A   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   0.0178:0.0075:1.56257:0.8668:91375:rs2905062
1   998501  rs3813193   G   C   .   PASS    .   ES:SE:LP:SS:ID  0.0228:0.0114:1.41908:52355:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.7361   ES:SE:LP:AF:SS:ID   -0.0056:0.0077:0.260428:0.7361:76604:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.1596   ES:SE:LP:AF:SS:ID   0.018:0.0102:1.20831:0.1596:52355:rs3934834
1   1017170 rs3766193   C   G   .   PASS    .   ES:SE:LP:SS:ID  -0.0022:0.0071:0.182501:85956:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.5488   ES:SE:LP:AF:SS:ID   -0.0079:0.0067:0.601019:0.5488:85956:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.1504   ES:SE:LP:AF:SS:ID   0.0243:0.0114:1.53655:0.1504:52355:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.562    ES:SE:LP:AF:SS:ID   -0.0046:0.0066:0.347657:0.562:85956:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.562    ES:SE:LP:AF:SS:ID   -0.0063:0.0065:0.510886:0.562:85931:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.1636   ES:SE:LP:AF:SS:ID   0.0221:0.0122:1.25073:0.1636:52355:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.7203   ES:SE:LP:AF:SS:ID   -0.0026:0.0067:0.141703:0.7203:84929:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.157    ES:SE:LP:AF:SS:ID   0.019:0.0118:1.08836:0.157:52355:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.7203   ES:SE:LP:AF:SS:ID   -0.0001:0.0072:0.0462403:0.7203:85956:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.5633   ES:SE:LP:AF:SS:ID   -0.0083:0.0069:0.353694:0.5633:85101:rs6701114
1   1026707 rs4074137   C   A   .   PASS    AF=0.5976   ES:SE:LP:AF:SS:ID   0.0028:0.0074:0.0193604:0.5976:55437:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.1478   ES:SE:LP:AF:SS:ID   0.0059:0.009:0.27597:0.1478:55437:rs6687776
1   1031540 rs9651273   A   G   .   PASS    AF=0.719    ES:SE:LP:AF:SS:ID   0.0007:0.0074:0.0330608:0.719:55437:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.08971  ES:SE:LP:AF:SS:ID   -0.004:0.0109:0.0147981:0.08971:70245:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.1174   ES:SE:LP:AF:SS:ID   0.0013:0.0102:0.0552706:0.1174:62515:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.1174   ES:SE:LP:AF:SS:ID   0.004:0.0098:0.229148:0.1174:70245:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.08443  ES:SE:LP:AF:SS:ID   -0.0032:0.0106:0.0253962:0.08443:72538:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.1174   ES:SE:LP:AF:SS:ID   0.0024:0.0093:0.17888:0.1174:70245:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.08839  ES:SE:LP:AF:SS:ID   -0.0045:0.0109:0.00497939:0.08839:70245:rs4970409
1   1060608 rs17160824  G   A   .   PASS    AF=0.08707  ES:SE:LP:AF:SS:ID   -0.0049:0.0108:0.00974997:0.08707:70245:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.08575  ES:SE:LP:AF:SS:ID   -0.0036:0.011:0.0234666:0.08575:70245:rs17160826
1   1061152 rs12748370  T   C   .   PASS    AF=0.08575  ES:SE:LP:AF:SS:ID   -0.0049:0.0109:0.0299787:0.08575:70245:rs12748370
1   1061166 rs11807848  T   C   .   PASS    AF=0.3918   ES:SE:LP:AF:SS:ID   -0.0015:0.008:0.0603809:0.3918:55437:rs11807848
1   1062638 rs9442373   C   A   .   PASS    AF=0.5607   ES:SE:LP:AF:SS:ID   0.0039:0.0079:0.0679831:0.5607:55437:rs9442373
1   1064535 rs6682475   G   C   .   PASS    .   ES:SE:LP:SS:ID  -0.0022:0.0105:0.119244:55437:rs6682475
1   1064979 rs2298217   C   T   .   PASS    AF=0.1161   ES:SE:LP:AF:SS:ID   -0.0025:0.01:0.0359762:0.1161:55437:rs2298217
1   1066403 rs10907182  T   C   .   PASS    AF=0.5897   ES:SE:LP:AF:SS:ID   0.0048:0.0089:0.125808:0.5897:55437:rs10907182
1   1071118 rs10907183  G   C   .   PASS    .   ES:SE:LP:SS:ID  0.0084:0.0093:0.303818:55437:rs10907183
1   1077064 rs4970357   C   A   .   PASS    AF=0.91161  ES:SE:LP:AF:SS:ID   0.0112:0.012:0.470955:0.91161:74153:rs4970357
1   1087683 rs9442380   T   C   .   PASS    AF=0.93404  ES:SE:LP:AF:SS:ID   0.0141:0.0111:0.667158:0.93404:83611:rs9442380
1   1089262 rs4970358   A   G   .   PASS    AF=0.96702  ES:SE:LP:AF:SS:ID   0.0156:0.0155:0.475344:0.96702:80872:rs4970358
1   1094738 rs4970362   A   G   .   PASS    AF=0.6293   ES:SE:LP:AF:SS:ID   0.0021:0.01:0.0903905:0.6293:51247:rs4970362
1   1097335 rs9442385   T   G   .   PASS    AF=0.93668  ES:SE:LP:AF:SS:ID   0.0127:0.0109:0.548982:0.93668:81864:rs9442385
1   1099342 rs9660710   A   C   .   PASS    AF=0.93668  ES:SE:LP:AF:SS:ID   0.0118:0.0106:0.550059:0.93668:84263:rs9660710
1   1100217 rs1891905   C   T   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   0.0175:0.017:0.489053:0.94987:80872:rs1891905
1   1106473 rs4970420   G   A   .   PASS    AF=0.19 ES:SE:LP:AF:SS:ID   0.0022:0.0106:0.0763416:0.19:55437:rs4970420
1   1119858 rs1320565   C   T   .   PASS    AF=0.08047  ES:SE:LP:AF:SS:ID   0.0145:0.0119:0.494579:0.08047:58388:rs1320565
1   1120431 rs1320571   G   A   .   PASS    AF=0.04749  ES:SE:LP:AF:SS:ID   -0.0167:0.0193:0.239201:0.04749:69979:rs1320571
1   1121794 rs11260549  G   A   .   PASS    AF=0.1346   ES:SE:LP:AF:SS:ID   0.0053:0.0094:0.437826:0.1346:65512:rs11260549
1   1124663 rs6684820   G   A   .   PASS    AF=0.2691   ES:SE:LP:AF:SS:ID   0.0098:0.0066:1.01028:0.2691:89203:rs6684820
1   1125553 rs10907174  A   T   .   PASS    .   ES:SE:LP:SS:ID  0.0056:0.0072:0.55083:89203:rs10907174
1   1129672 rs11260554  G   T   .   PASS    AF=0.124    ES:SE:LP:AF:SS:ID   0.0049:0.0096:0.465086:0.124:65476:rs11260554
1   1130727 rs10907175  A   C   .   PASS    AF=0.08971  ES:SE:LP:AF:SS:ID   0.0081:0.0096:0.465466:0.08971:87339:rs10907175
1   1135242 rs9729550   A   C   .   PASS    AF=0.2665   ES:SE:LP:AF:SS:ID   0.0094:0.0065:0.966576:0.2665:89203:rs9729550

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