Summary
Summary {data-width=650}
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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"file_date": "2019-10-26T21:45:35.311730",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005194/EBI-a-GCST005194_data.json --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/hg38/hg38.fa; 1.1.1",
"reference": "file:/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/b37/human_g1k_v37.fasta",
"bcftools_annotateVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
"bcftools_annotateCommand": "annotate -a /mnt/storage/home/gh13047/mr-eve/vcf-reference-datasets/dbsnp/dbsnp.v153.b37.vcf.gz -c ID -o /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005194/EBI-a-GCST005194.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005194/EBI-a-GCST005194_data.vcf.gz; Date=Sat Oct 26 22:00:05 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST005194/ebi-a-GCST005194.vcf.gz; Date=Sun May 10 04:47:58 2020"
}
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/ebi_gwas_import/processed/EBI-a-GCST005194/EBI-a-GCST005194.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/ebi_gwas_import/processed/EBI-a-GCST005194/ldsc.txt \
--snplist /data/ref/snplist.gz \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Sat Oct 26 22:23:30 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005194/EBI-a-GCST005194.vcf.gz ...
and extracting SNPs specified in /data/ref/snplist.gz ...
Traceback (most recent call last):
File "./ldsc/ldsc.py", line 647, in <module>
sumstats.estimate_h2(args, log)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
args, log, args.h2)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 246, in _read_ld_sumstats
sumstats = _read_sumstats(args, log, fh, alleles=alleles, dropna=dropna)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 165, in _read_sumstats
sumstats = ps.sumstats(fh, alleles=alleles, dropna=dropna, slh=args.snplist)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 85, in sumstats
x = read_vcf(fh, alleles, slh)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 161, in read_vcf
with gzip.open(slh) as f:
File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 34, in open
return GzipFile(filename, mode, compresslevel)
File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 94, in __init__
fileobj = self.myfileobj = __builtin__.open(filename, mode or 'rb')
IOError: [Errno 2] No such file or directory: '/data/ref/snplist.gz'
Analysis finished at Sat Oct 26 22:24:22 2019
Total time elapsed: 51.62sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9557,
"inflation_factor": 1.2817,
"mean_EFFECT": 0.0003,
"n": "-Inf",
"n_snps": 7904237,
"n_clumped_hits": 145,
"n_p_sig": 10054,
"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": 57371,
"n_est": "NA",
"ratio_se_n": "NA",
"mean_diff": "NaN",
"ratio_diff": "NaN",
"sd_y_est1": "NaN",
"sd_y_est2": "NA",
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": "NA",
"ldsc_nsnp_merge_regression_ld": "NA",
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": "NA",
"ldsc_intercept_se": "NA",
"ldsc_lambda_gc": "NA",
"ldsc_mean_chisq": "NA",
"ldsc_ratio": "NA"
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | TRUE |
| n | TRUE |
| is_snpid_non_unique | FALSE |
| 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 | TRUE |
| ldsc_intercept_beta | TRUE |
| n_clumped_hits | FALSE |
| r2_sum1 | FALSE |
| r2_sum2 | FALSE |
| r2_sum3 | FALSE |
| r2_sum4 | FALSE |
Definitions
General metrics
af_correlation: Correlation coefficient betweenAFandAF_reference.inflation_factor(lambda): Genomic inflation factor.mean_EFFECT: Mean ofEFFECTsize.n: Maximum value of reported sample size across all SNPs, \(n\).n_clumped_hits: Number of clumped hits.n_snps: Number of SNPsn_p_sig: Number of SNPs with pvalue below5e-8.n_mono: Number of monomorphic (MAF == 1orMAF == 0) SNPs.n_ns: Number of SNPs with nonsense values:- alleles other than
A, C, G or T. - P-values
< 0or> 1. - negative or infinite standard errors (
<= 0or= Infinity). - infinite beta estimates or allele frequencies
< 0or> 1.
- alleles other than
n_mac: Number of cases whereMAC(\(2 \times N \times MAF\)) is less than6.is_snpid_unique:trueif the combination ofIDREFALTis unique and therefore no duplication in snpid.n_miss_<*>: Number ofNAobservations 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 expectratio_se_nto 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 ofdiffand the mean ofdiff2(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<*>:r2statistics under various assumptions1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).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: NOTis_snpid_unique.mean_EFFECT_nonfinite:mean(EFFECT)isNA,NaN, orInf.mean_EFFECT_05:abs(mean(EFFECT))> 0.5.mean_EFFECT_01:abs(mean(EFFECT))> 0.1.mean_chisq:ldsc_mean_chisq> 1.3 orldsc_mean_chisq< 0.7.n_p_sig:n_p_sig> 1000.miss_<*>:n_miss_<*>/n_snps> 0.01.ldsc_ratio:ldsc_ratio> 0.5ldsc_intercept_beta:ldsc_intercept_beta> 1.5n_clumped_hits:n_clumped_hits> 1000r2_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 | logical.mean | logical.count | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 0 | 1.0000000 | 3 | 58 | 0 | 7888871 | 0 | NA | NA | 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 | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 7888885 | 0.0000000 | NA | NA | NA | NA | NA | NaN | : | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.610124e+00 | 5.736126e+00 | 1.0000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.896261e+07 | 5.625866e+07 | 828.0000 | 3.260979e+07 | 6.963393e+07 | 1.146458e+08 | 2.492223e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.503000e-04 | 1.632100e-02 | -0.4373 | -7.300000e-03 | 2.000000e-04 | 7.600000e-03 | 5.656000e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.240080e-02 | 8.831100e-03 | 0.0050 | 6.300000e-03 | 8.700000e-03 | 1.570000e-02 | 2.034000e-01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.580654e-01 | 2.991104e-01 | 0.0000 | 1.894000e-01 | 4.451004e-01 | 7.171005e-01 | 9.995000e-01 | ▇▆▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.580551e-01 | 2.991082e-01 | 0.0000 | 1.893515e-01 | 4.452005e-01 | 7.173005e-01 | 9.993145e-01 | ▇▆▆▆▆ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.452756e-01 | 2.563511e-01 | 0.0009 | 3.840000e-02 | 1.400000e-01 | 3.873000e-01 | 9.988000e-01 | ▇▂▂▁▁ |
| numeric | AF_reference | 57371 | 0.9927276 | NA | NA | NA | NA | NA | NA | NA | 2.462487e-01 | 2.526064e-01 | 0.0000 | 4.073480e-02 | 1.525560e-01 | 3.845850e-01 | 1.000000e+00 | ▇▃▂▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 752566 | rs3094315 | G | A | -0.0030 | 0.0082 | 0.7161005 | 0.7144743 | 0.8082 | 0.718251 | NA |
| 1 | 752721 | rs3131972 | A | G | -0.0023 | 0.0082 | 0.7808992 | 0.7791033 | 0.7993 | 0.653355 | NA |
| 1 | 753405 | rs3115860 | C | A | 0.0047 | 0.0088 | 0.5957005 | 0.5932786 | 0.8345 | 0.751797 | NA |
| 1 | 753541 | rs2073813 | G | A | -0.0049 | 0.0088 | 0.5793993 | 0.5776517 | 0.1582 | 0.301917 | NA |
| 1 | 754182 | rs3131969 | A | G | 0.0049 | 0.0087 | 0.5785994 | 0.5732862 | 0.8271 | 0.678514 | NA |
| 1 | 754192 | rs3131968 | A | G | 0.0047 | 0.0087 | 0.5885997 | 0.5890385 | 0.8270 | 0.678514 | NA |
| 1 | 754334 | rs3131967 | T | C | 0.0044 | 0.0088 | 0.6195994 | 0.6170751 | 0.8244 | 0.684305 | NA |
| 1 | 754503 | rs3115859 | G | A | -0.0003 | 0.0082 | 0.9735001 | 0.9708156 | 0.8006 | 0.663938 | NA |
| 1 | 754964 | rs3131966 | C | T | 0.0002 | 0.0083 | 0.9792000 | 0.9807757 | 0.7980 | 0.663339 | NA |
| 1 | 755775 | rs3131965 | A | G | 0.0010 | 0.0084 | 0.9091999 | 0.9052376 | 0.7981 | NA | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51196164 | rs8136603 | A | T | -0.0171 | 0.0130 | 0.1878002 | 0.1883807 | 0.0653 | 0.1427720 | NA |
| 22 | 51197266 | rs61290853 | A | G | 0.0105 | 0.0068 | 0.1227001 | 0.1225598 | 0.3861 | 0.4229230 | NA |
| 22 | 51197602 | rs187225588 | T | A | -0.0116 | 0.0141 | 0.4128003 | 0.4106814 | 0.0508 | 0.0175719 | NA |
| 22 | 51198569 | rs142671391 | G | C | -0.0113 | 0.0148 | 0.4475000 | 0.4451572 | 0.0529 | 0.1110220 | NA |
| 22 | 51208568 | rs148425445 | G | T | -0.0093 | 0.0133 | 0.4834995 | 0.4843970 | 0.0611 | 0.1160140 | NA |
| 22 | 51211031 | rs9616968 | A | G | 0.0032 | 0.0137 | 0.8144001 | 0.8153137 | 0.0679 | 0.0373403 | NA |
| 22 | 51216564 | rs9616970 | T | C | -0.0022 | 0.0094 | 0.8129999 | 0.8149519 | 0.1282 | 0.1563500 | NA |
| 22 | 51218377 | rs2519461 | G | C | 0.0044 | 0.0121 | 0.7190002 | 0.7161296 | 0.0748 | 0.0826677 | NA |
| 22 | 51219006 | rs28729663 | G | A | 0.0059 | 0.0090 | 0.5120000 | 0.5121101 | 0.1501 | 0.2052720 | NA |
| 22 | 51222100 | rs114553188 | G | T | -0.0073 | 0.0138 | 0.5969995 | 0.5968155 | 0.0563 | 0.0880591 | NA |
bcf preview
1 752566 rs3094315 G A . PASS AF=0.8082 ES:SE:LP:AF:ID -0.003:0.0082:0.145026:0.8082:rs3094315
1 752721 rs3131972 A G . PASS AF=0.7993 ES:SE:LP:AF:ID -0.0023:0.0082:0.107405:0.7993:rs3131972
1 753405 rs3115860 C A . PASS AF=0.8345 ES:SE:LP:AF:ID 0.0047:0.0088:0.224972:0.8345:rs3115860
1 753541 rs2073813 G A . PASS AF=0.1582 ES:SE:LP:AF:ID -0.0049:0.0088:0.237022:0.1582:rs2073813
1 754182 rs3131969 A G . PASS AF=0.8271 ES:SE:LP:AF:ID 0.0049:0.0087:0.237622:0.8271:rs3131969
1 754192 rs3131968 A G . PASS AF=0.827 ES:SE:LP:AF:ID 0.0047:0.0087:0.23018:0.827:rs3131968
1 754334 rs3131967 T C . PASS AF=0.8244 ES:SE:LP:AF:ID 0.0044:0.0088:0.207889:0.8244:rs3131967
1 754503 rs3115859 G A . PASS AF=0.8006 ES:SE:LP:AF:ID -0.0003:0.0082:0.011664:0.8006:rs3115859
1 754964 rs3131966 C T . PASS AF=0.798 ES:SE:LP:AF:ID 0.0002:0.0083:0.00912859:0.798:rs3131966
1 755775 rs3131965 A G . PASS AF=0.7981 ES:SE:LP:AF:ID 0.001:0.0084:0.0413406:0.7981:rs3131965
1 755890 rs3115858 A T . PASS AF=0.8353 ES:SE:LP:AF:ID 0.004:0.0088:0.189431:0.8353:rs3115858
1 756604 rs3131962 A G . PASS AF=0.8291 ES:SE:LP:AF:ID 0.0046:0.0087:0.225118:0.8291:rs3131962
1 757640 rs3115853 G A . PASS AF=0.8224 ES:SE:LP:AF:ID 0.0029:0.0088:0.129538:0.8224:rs3115853
1 757734 rs4951929 C T . PASS AF=0.8366 ES:SE:LP:AF:ID 0.0025:0.0088:0.110586:0.8366:rs4951929
1 757936 rs4951862 C A . PASS AF=0.8365 ES:SE:LP:AF:ID 0.0023:0.0088:0.102208:0.8365:rs4951862
1 758144 rs3131956 A G . PASS AF=0.8314 ES:SE:LP:AF:ID 0.0042:0.0087:0.202525:0.8314:rs3131956
1 758626 rs3131954 C T . PASS AF=0.8368 ES:SE:LP:AF:ID 0.003:0.0088:0.133713:0.8368:rs3131954
1 760912 rs1048488 C T . PASS AF=0.8039 ES:SE:LP:AF:ID 0.0006:0.0083:0.0268721:0.8039:rs1048488
1 761147 rs3115850 T C . PASS AF=0.8048 ES:SE:LP:AF:ID -0.0006:0.0083:0.0253962:0.8048:rs3115850
1 761732 rs2286139 C T . PASS AF=0.8123 ES:SE:LP:AF:ID 0.0057:0.0088:0.286762:0.8123:rs2286139
1 762320 rs75333668 C T . PASS AF=0.0041 ES:SE:LP:AF:ID -0.0271:0.0622:0.178486:0.0041:rs75333668
1 766007 rs61768174 A C . PASS AF=0.1085 ES:SE:LP:AF:ID -0.0086:0.0102:0.399899:0.1085:rs61768174
1 768253 rs2977608 A C . PASS AF=0.7171 ES:SE:LP:AF:ID 0.0049:0.0072:0.306713:0.7171:rs2977608
1 768448 rs12562034 G A . PASS AF=0.118 ES:SE:LP:AF:ID -0.0054:0.0094:0.247952:0.118:rs12562034
1 769223 rs60320384 C G . PASS AF=0.1398 ES:SE:LP:AF:ID -0.005:0.0091:0.237547:0.1398:rs60320384
1 771823 rs2977605 T C . PASS AF=0.8378 ES:SE:LP:AF:ID 0.0049:0.0089:0.236572:0.8378:rs2977605
1 771967 rs59066358 G A . PASS AF=0.1412 ES:SE:LP:AF:ID -0.0051:0.009:0.243973:0.1412:rs59066358
1 772755 rs2905039 A C . PASS AF=0.837 ES:SE:LP:AF:ID 0.0046:0.0089:0.219035:0.837:rs2905039
1 777122 rs2980319 A T . PASS AF=0.8385 ES:SE:LP:AF:ID 0.0076:0.0088:0.411952:0.8385:rs2980319
1 777232 rs112618790 C T . PASS AF=0.0904 ES:SE:LP:AF:ID -0.0036:0.0113:0.125808:0.0904:rs112618790
1 778745 rs1055606 A G . PASS AF=0.1401 ES:SE:LP:AF:ID -0.0078:0.009:0.413976:0.1401:rs1055606
1 779322 rs4040617 A G . PASS AF=0.1427 ES:SE:LP:AF:ID -0.0083:0.0089:0.451119:0.1427:rs4040617
1 780785 rs2977612 T A . PASS AF=0.83 ES:SE:LP:AF:ID 0.0081:0.0088:0.450874:0.83:rs2977612
1 781845 rs61768199 A G . PASS AF=0.1007 ES:SE:LP:AF:ID -0.0109:0.0105:0.521578:0.1007:rs61768199
1 785050 rs2905062 G A . PASS AF=0.8255 ES:SE:LP:AF:ID 0.0072:0.0087:0.388277:0.8255:rs2905062
1 785989 rs2980300 T C . PASS AF=0.8223 ES:SE:LP:AF:ID 0.0075:0.0087:0.411728:0.8223:rs2980300
1 787399 rs2905055 G T . PASS AF=0.8177 ES:SE:LP:AF:ID 0.0055:0.0088:0.270673:0.8177:rs2905055
1 787606 rs3863622 G T . PASS AF=0.1421 ES:SE:LP:AF:ID -0.0098:0.009:0.558148:0.1421:rs3863622
1 787685 rs2905054 G T . PASS AF=0.8143 ES:SE:LP:AF:ID 0.0055:0.0088:0.271322:0.8143:rs2905054
1 787844 rs2905053 C T . PASS AF=0.8284 ES:SE:LP:AF:ID 0.0069:0.0089:0.357239:0.8284:rs2905053
1 790465 rs61768207 G A . PASS AF=0.1067 ES:SE:LP:AF:ID -0.0074:0.0105:0.317043:0.1067:rs61768207
1 791191 rs111818025 G A . PASS AF=0.1398 ES:SE:LP:AF:ID -0.0081:0.0092:0.423659:0.1398:rs111818025
1 791853 rs6684487 G A . PASS AF=0.0908 ES:SE:LP:AF:ID -0.0043:0.0113:0.154592:0.0908:rs6684487
1 794332 rs12127425 G A . PASS AF=0.0826 ES:SE:LP:AF:ID -0.0019:0.0118:0.0584886:0.0826:rs12127425
1 795222 rs12131377 C G . PASS AF=0.0791 ES:SE:LP:AF:ID -0.0026:0.012:0.0834408:0.0791:rs12131377
1 795988 rs59380221 C T . PASS AF=0.1683 ES:SE:LP:AF:ID 0.0048:0.0094:0.21846:0.1683:rs59380221
1 796100 rs12132398 C T . PASS AF=0.0809 ES:SE:LP:AF:ID -0.0029:0.0119:0.0931265:0.0809:rs12132398
1 796375 rs12083781 T C . PASS AF=0.1333 ES:SE:LP:AF:ID 0.0028:0.0095:0.113002:0.1333:rs12083781
1 797281 rs76631953 G C . PASS AF=0.0783 ES:SE:LP:AF:ID -0.0032:0.0121:0.100836:0.0783:rs76631953
1 797325 rs111739932 T C . PASS AF=0.0789 ES:SE:LP:AF:ID -0.0037:0.012:0.121248:0.0789:rs111739932