IEU GWAS QC Report

name	value
id	ieu-a-1065
pmid	21130836
year	2011
mr	1
note	Metric of information processing speed
trait	Inspection time
category	Risk factor
subcategory	Psychiatric / neurological
population	European
sex	Males and females
ncase	NULL
ncontrol	NULL
sample_size	2645
nsnp	2402666
sd	48.34
priority	1
author	Luciano
group_name	public
access	public
build	HG19/GRCh37

name	value
gwas_id	ieu-a-1065
bcf_file	ieu-a-1065.vcf.gz
qc_metrics_file	qc_metrics.json
metadata	metadata.json
refdata	1kg_v3_nomult.bcf
compile_time	2020-05-09 19:19 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-1065/ieu-a-1065.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-1065/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 10:47:10 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1065/ieu-a-1065.vcf.gz ...
Read summary statistics for 2399807 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, 1141285 SNPs remain.
After merging with regression SNP LD, 1141285 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.1138 (0.1723)
Lambda GC: 0.9817
Mean Chi^2: 0.9858
Intercept: 0.9918 (0.0065)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Tue Feb  4 10:47:42 2020
Total time elapsed: 31.36s

{
    "af_correlation": 0.9207,
    "inflation_factor": 0.9824,
    "mean_EFFECT": -0.0001,
    "n": 2645,
    "n_snps": 2399807,
    "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": 20188,
    "n_est": 2561.2608,
    "ratio_se_n": 0.984,
    "mean_diff": 0,
    "ratio_diff": 1.0045,
    "sd_y_est1": 1.0179,
    "sd_y_est2": 1.0016,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1141285,
    "ldsc_nsnp_merge_regression_ld": 1141285,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 0.9918,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 0.9817,
    "ldsc_mean_chisq": 0.9858,
    "ldsc_ratio": 0.5775
}

name	value
name	value
af_correlation	FALSE
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

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	2399807	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	8.595156e+00	5.661989e+00	1.0000e+00	4.000000e+00	8.000000e+00	1.200000e+01	2.30000e+01	▇▅▅▂▂
numeric	POS	0	1.0000000	NA	NA	NA	NA	NA	7.877922e+07	5.567137e+07	1.1523e+04	3.263012e+07	7.015307e+07	1.142824e+08	2.49219e+08	▇▆▅▂▁
numeric	EFFECT	0	1.0000000	NA	NA	NA	NA	NA	-1.375000e-04	4.802350e-02	-3.3870e+00	-2.490000e-02	-1.000000e-04	2.450000e-02	2.16500e+00	▁▁▁▇▁
numeric	SE	0	1.0000000	NA	NA	NA	NA	NA	4.194210e-02	2.408480e-02	2.6300e-02	2.890000e-02	3.380000e-02	4.530000e-02	9.88100e-01	▇▁▁▁▁
numeric	PVAL	0	1.0000000	NA	NA	NA	NA	NA	5.029465e-01	2.885811e-01	7.0000e-07	2.534002e-01	5.037998e-01	7.536002e-01	1.00000e+00	▇▇▇▇▇
numeric	PVAL_ztest	0	1.0000000	NA	NA	NA	NA	NA	5.029467e-01	2.885821e-01	7.0000e-07	2.533333e-01	5.036794e-01	7.536208e-01	1.00000e+00	▇▇▇▇▇
numeric	AF	0	1.0000000	NA	NA	NA	NA	NA	3.633291e-01	2.711903e-01	1.0060e-02	1.285000e-01	2.999000e-01	5.624500e-01	9.89940e-01	▇▅▃▃▂
numeric	AF_reference	20188	0.9915877	NA	NA	NA	NA	NA	3.650602e-01	2.532621e-01	1.9970e-04	1.523560e-01	3.051120e-01	5.485220e-01	1.00000e+00	▇▆▅▃▂
numeric	N	0	1.0000000	NA	NA	NA	NA	NA	2.645000e+03	0.000000e+00	2.6450e+03	2.645000e+03	2.645000e+03	2.645000e+03	2.64500e+03	▁▁▇▁▁

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	-0.2304	0.1170	0.0490004	0.0489266	0.03048	0.0371406	2645
1	723819	rs11804171	T	A	-0.2363	0.1162	0.0419199	0.0419957	0.03048	0.1345850	2645
1	723891	rs2977670	G	C	0.2304	0.1146	0.0443905	0.0443813	0.96924	0.7799520	2645
1	750235	rs12138618	G	A	-0.1229	0.0819	0.1333000	0.1334563	0.08166	NA	2645
1	752566	rs3094315	G	A	-0.0897	0.0547	0.1012999	0.1010356	0.79180	0.7182510	2645
1	754192	rs3131968	A	G	-0.1293	0.0575	0.0243899	0.0245319	0.81280	0.6785140	2645
1	768448	rs12562034	G	A	-0.0243	0.0629	0.6989997	0.6992541	0.11050	0.1918930	2645
1	775659	rs2905035	A	G	-0.1388	0.0578	0.0164502	0.0163332	0.81280	0.7450080	2645
1	777122	rs2980319	A	T	-0.1315	0.0579	0.0232001	0.0231375	0.81280	0.7472040	2645
1	779322	rs4040617	A	G	0.1315	0.0579	0.0232001	0.0231375	0.18720	0.2264380	2645

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	0.0086	0.0420	0.8372000	0.8377582	0.40970	0.3724040	2645
22	51216564	rs9616970	T	C	0.0187	0.0462	0.6856998	0.6856525	0.13400	0.1563500	2645
22	51217134	rs117417021	A	G	0.0086	0.0418	0.8363000	0.8369927	0.48450	0.2671730	2645
22	51222100	rs114553188	G	T	0.0187	0.0644	0.7718999	0.7715311	0.07936	0.0880591	2645
22	51223637	rs375798137	G	A	0.0187	0.0644	0.7718999	0.7715311	0.07936	0.0788738	2645
22	51229805	rs9616985	T	C	0.0051	0.0607	0.9331000	0.9330407	0.05405	0.0730831	2645
23	35921591	rs2204667	C	G	0.0206	0.0362	0.5699005	0.5693149	0.15410	NA	2645
23	51666786	rs14115	A	G	0.0044	0.0687	0.9488001	0.9489331	0.06200	NA	2645
23	70163799	rs1626496	A	C	-0.0671	0.0530	0.2057998	0.2054996	0.03939	NA	2645
23	118495837	rs12882977	G	A	-0.0021	0.0278	0.9392000	0.9397854	0.42180	0.2307280	2645

1   721290  rs12565286  G   C   .   PASS    AF=0.03048  ES:SE:LP:AF:SS:ID   -0.2304:0.117:1.3098:0.03048:2645:rs12565286
1   723819  rs11804171  T   A   .   PASS    AF=0.03048  ES:SE:LP:AF:SS:ID   -0.2363:0.1162:1.37758:0.03048:2645:rs11804171
1   723891  rs2977670   G   C   .   PASS    AF=0.96924  ES:SE:LP:AF:SS:ID   0.2304:0.1146:1.35271:0.96924:2645:rs2977670
1   750235  rs12138618  G   A   .   PASS    AF=0.08166  ES:SE:LP:AF:SS:ID   -0.1229:0.0819:0.87517:0.08166:2645:rs12138618
1   752566  rs3094315   G   A   .   PASS    AF=0.7918   ES:SE:LP:AF:SS:ID   -0.0897:0.0547:0.994391:0.7918:2645:rs3094315
1   754192  rs3131968   A   G   .   PASS    AF=0.8128   ES:SE:LP:AF:SS:ID   -0.1293:0.0575:1.61279:0.8128:2645:rs3131968
1   768448  rs12562034  G   A   .   PASS    AF=0.1105   ES:SE:LP:AF:SS:ID   -0.0243:0.0629:0.155523:0.1105:2645:rs12562034
1   775659  rs2905035   A   G   .   PASS    AF=0.8128   ES:SE:LP:AF:SS:ID   -0.1388:0.0578:1.78383:0.8128:2645:rs2905035
1   777122  rs2980319   A   T   .   PASS    AF=0.8128   ES:SE:LP:AF:SS:ID   -0.1315:0.0579:1.63451:0.8128:2645:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.1872   ES:SE:LP:AF:SS:ID   0.1315:0.0579:1.63451:0.1872:2645:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.8128   ES:SE:LP:AF:SS:ID   -0.1315:0.0579:1.63451:0.8128:2645:rs2977612
1   785050  rs2905062   G   A   .   PASS    AF=0.8131   ES:SE:LP:AF:SS:ID   -0.1315:0.0579:1.63451:0.8131:2645:rs2905062
1   798026  rs4951864   C   T   .   PASS    AF=0.8899   ES:SE:LP:AF:SS:ID   0.0195:0.0659:0.115091:0.8899:2645:rs4951864
1   798801  rs12132517  G   A   .   PASS    AF=0.1104   ES:SE:LP:AF:SS:ID   -0.0279:0.0656:0.173472:0.1104:2645:rs12132517
1   798959  rs11240777  G   A   .   PASS    AF=0.2142   ES:SE:LP:AF:SS:ID   0.0626:0.0544:0.602755:0.2142:2645:rs11240777
1   962210  rs3128126   A   G   .   PASS    AF=0.4612   ES:SE:LP:AF:SS:ID   0.0055:0.0434:0.0465786:0.4612:2645:rs3128126
1   990380  rs3121561   C   T   .   PASS    AF=0.2895   ES:SE:LP:AF:SS:ID   0.0744:0.0482:0.911155:0.2895:2645:rs3121561
1   998501  rs3813193   G   C   .   PASS    AF=0.2294   ES:SE:LP:AF:SS:ID   0.0075:0.0396:0.0708877:0.2294:2645:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.7401   ES:SE:LP:AF:SS:ID   -0.0044:0.0313:0.0516849:0.7401:2645:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.2293   ES:SE:LP:AF:SS:ID   0.0083:0.0397:0.0785737:0.2293:2645:rs3934834
1   1017170 rs3766193   C   G   .   PASS    AF=0.5155   ES:SE:LP:AF:SS:ID   -0.0368:0.0388:0.46382:0.5155:2645:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.5106   ES:SE:LP:AF:SS:ID   -0.0382:0.0384:0.494714:0.5106:2645:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.2174   ES:SE:LP:AF:SS:ID   0.0175:0.0418:0.170503:0.2174:2645:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.5106   ES:SE:LP:AF:SS:ID   -0.0162:0.0283:0.246723:0.5106:2645:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.5104   ES:SE:LP:AF:SS:ID   -0.0162:0.0283:0.246723:0.5104:2645:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.2168   ES:SE:LP:AF:SS:ID   0.0153:0.0414:0.147764:0.2168:2645:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.7174   ES:SE:LP:AF:SS:ID   -0.0006:0.031:0.00621119:0.7174:2645:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.2168   ES:SE:LP:AF:SS:ID   0.0153:0.0414:0.147764:0.2168:2645:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.7424   ES:SE:LP:AF:SS:ID   0.0022:0.0311:0.025166:0.7424:2645:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.4994   ES:SE:LP:AF:SS:ID   -0.0139:0.028:0.208309:0.4994:2645:rs6701114
1   1025301 rs9442400   T   C   .   PASS    AF=0.98189  ES:SE:LP:AF:SS:ID   -0.1194:0.1503:0.369572:0.98189:2645:rs9442400
1   1026707 rs4074137   C   A   .   PASS    AF=0.6052   ES:SE:LP:AF:SS:ID   -0.0054:0.0283:0.0716554:0.6052:2645:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.1886   ES:SE:LP:AF:SS:ID   -0.0171:0.0379:0.185686:0.1886:2645:rs6687776
1   1030633 rs6678318   G   A   .   PASS    AF=0.1857   ES:SE:LP:AF:SS:ID   -0.0171:0.0379:0.185686:0.1857:2645:rs6678318
1   1031540 rs9651273   A   G   .   PASS    AF=0.7296   ES:SE:LP:AF:SS:ID   -0.0227:0.0315:0.326426:0.7296:2645:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.0529   ES:SE:LP:AF:SS:ID   -0.0363:0.0455:0.370692:0.0529:2645:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.09919  ES:SE:LP:AF:SS:ID   -0.0266:0.0406:0.290052:0.09919:2645:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.09919  ES:SE:LP:AF:SS:ID   -0.0274:0.0402:0.304869:0.09919:2645:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.05322  ES:SE:LP:AF:SS:ID   -0.028:0.0452:0.270673:0.05322:2645:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.1112   ES:SE:LP:AF:SS:ID   -0.0325:0.0401:0.378824:0.1112:2645:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.06613  ES:SE:LP:AF:SS:ID   -0.0312:0.0449:0.312739:0.06613:2645:rs4970409
1   1060174 rs7548798   C   T   .   PASS    AF=0.3258   ES:SE:LP:AF:SS:ID   0.0247:0.0298:0.39126:0.3258:2645:rs7548798
1   1060235 rs7540009   G   A   .   PASS    AF=0.04543  ES:SE:LP:AF:SS:ID   -0.0311:0.0839:0.148008:0.04543:2645:rs7540009
1   1060608 rs17160824  G   A   .   PASS    AF=0.06642  ES:SE:LP:AF:SS:ID   -0.0336:0.0448:0.343614:0.06642:2645:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.06642  ES:SE:LP:AF:SS:ID   -0.0369:0.0451:0.38384:0.06642:2645:rs17160826
1   1061152 rs12748370  T   C   .   PASS    AF=0.06642  ES:SE:LP:AF:SS:ID   -0.038:0.0452:0.398483:0.06642:2645:rs12748370
1   1061166 rs11807848  T   C   .   PASS    AF=0.3921   ES:SE:LP:AF:SS:ID   0.0092:0.0284:0.127145:0.3921:2645:rs11807848
1   1062015 rs9659914   C   T   .   PASS    AF=0.04457  ES:SE:LP:AF:SS:ID   -0.023:0.0856:0.103198:0.04457:2645:rs9659914
1   1062638 rs9442373   C   A   .   PASS    AF=0.5233   ES:SE:LP:AF:SS:ID   0.0082:0.0279:0.113735:0.5233:2645:rs9442373
1   1064535 rs6682475   G   C   .   PASS    AF=0.7884   ES:SE:LP:AF:SS:ID   0.0426:0.0349:0.653061:0.7884:2645:rs6682475

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