Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std plot

beta_std_plot

beta_std_plot

Metadata

{
    "fileformat": "VCFv4.2",
    "FILTER": "<ID=PASS,Description=\"All filters passed\">",
    "INFO": "<ID=AF,Number=A,Type=Float,Description=\"Allele Frequency\">",
    "FORMAT": "<ID=ES,Number=A,Type=Float,Description=\"Effect size estimate relative to the alternative allele\">",
    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
    "FORMAT.2": "<ID=LP,Number=A,Type=Float,Description=\"-log10 p-value for effect estimate\">",
    "FORMAT.3": "<ID=AF,Number=A,Type=Float,Description=\"Alternate allele frequency in the association study\">",
    "FORMAT.4": "<ID=SS,Number=A,Type=Float,Description=\"Sample size used to estimate genetic effect\">",
    "FORMAT.5": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
    "FORMAT.6": "<ID=SI,Number=A,Type=Float,Description=\"Accuracy score of summary data imputation\">",
    "FORMAT.7": "<ID=NC,Number=A,Type=Float,Description=\"Number of cases used to estimate genetic effect\">",
    "FORMAT.8": "<ID=ID,Number=1,Type=String,Description=\"Study variant identifier\">",
    "META": "<ID=TotalVariants,Number=1,Type=Integer,Description=\"Total number of variants in input\">",
    "META.1": "<ID=VariantsNotRead,Number=1,Type=Integer,Description=\"Number of variants that could not be read\">",
    "META.2": "<ID=HarmonisedVariants,Number=1,Type=Integer,Description=\"Total number of harmonised variants\">",
    "META.3": "<ID=VariantsNotHarmonised,Number=1,Type=Integer,Description=\"Total number of variants that could not be harmonised\">",
    "META.4": "<ID=SwitchedAlleles,Number=1,Type=Integer,Description=\"Total number of variants strand switched\">",
    "META.5": "<ID=TotalControls,Number=1,Type=Integer,Description=\"Total number of controls in the association study\">",
    "META.6": "<ID=TotalCases,Number=1,Type=Integer,Description=\"Total number of cases in the association study\">",
    "META.7": "<ID=StudyType,Number=1,Type=String,Description=\"Type of GWAS study [Continuous or CaseControl]\">",
    "SAMPLE": "<ID=UKB-b:17097,TotalVariants=9851866,VariantsNotRead=0,HarmonisedVariants=9851866,VariantsNotHarmonised=0,SwitchedAlleles=9851866,TotalControls=420698,TotalCases=40700,StudyType=CaseControl>",
    "contig": "<ID=1,length=249250621,assembly=GRCh37>",
    "contig.1": "<ID=2,length=243199373,assembly=GRCh37>",
    "contig.2": "<ID=3,length=198022430,assembly=GRCh37>",
    "contig.3": "<ID=4,length=191154276,assembly=GRCh37>",
    "contig.4": "<ID=5,length=180915260,assembly=GRCh37>",
    "contig.5": "<ID=6,length=171115067,assembly=GRCh37>",
    "contig.6": "<ID=7,length=159138663,assembly=GRCh37>",
    "contig.7": "<ID=8,length=146364022,assembly=GRCh37>",
    "contig.8": "<ID=9,length=141213431,assembly=GRCh37>",
    "contig.9": "<ID=10,length=135534747,assembly=GRCh37>",
    "contig.10": "<ID=11,length=135006516,assembly=GRCh37>",
    "contig.11": "<ID=12,length=133851895,assembly=GRCh37>",
    "contig.12": "<ID=13,length=115169878,assembly=GRCh37>",
    "contig.13": "<ID=14,length=107349540,assembly=GRCh37>",
    "contig.14": "<ID=15,length=102531392,assembly=GRCh37>",
    "contig.15": "<ID=16,length=90354753,assembly=GRCh37>",
    "contig.16": "<ID=17,length=81195210,assembly=GRCh37>",
    "contig.17": "<ID=18,length=78077248,assembly=GRCh37>",
    "contig.18": "<ID=19,length=59128983,assembly=GRCh37>",
    "contig.19": "<ID=20,length=63025520,assembly=GRCh37>",
    "contig.20": "<ID=21,length=48129895,assembly=GRCh37>",
    "contig.21": "<ID=22,length=51304566,assembly=GRCh37>",
    "contig.22": "<ID=X,length=155270560,assembly=GRCh37>",
    "contig.23": "<ID=Y,length=59373566,assembly=GRCh37>",
    "contig.24": "<ID=MT,length=16569,assembly=GRCh37>",
    "contig.25": "<ID=GL000207.1,length=4262,assembly=GRCh37>",
    "contig.26": "<ID=GL000226.1,length=15008,assembly=GRCh37>",
    "contig.27": "<ID=GL000229.1,length=19913,assembly=GRCh37>",
    "contig.28": "<ID=GL000231.1,length=27386,assembly=GRCh37>",
    "contig.29": "<ID=GL000210.1,length=27682,assembly=GRCh37>",
    "contig.30": "<ID=GL000239.1,length=33824,assembly=GRCh37>",
    "contig.31": "<ID=GL000235.1,length=34474,assembly=GRCh37>",
    "contig.32": "<ID=GL000201.1,length=36148,assembly=GRCh37>",
    "contig.33": "<ID=GL000247.1,length=36422,assembly=GRCh37>",
    "contig.34": "<ID=GL000245.1,length=36651,assembly=GRCh37>",
    "contig.35": "<ID=GL000197.1,length=37175,assembly=GRCh37>",
    "contig.36": "<ID=GL000203.1,length=37498,assembly=GRCh37>",
    "contig.37": "<ID=GL000246.1,length=38154,assembly=GRCh37>",
    "contig.38": "<ID=GL000249.1,length=38502,assembly=GRCh37>",
    "contig.39": "<ID=GL000196.1,length=38914,assembly=GRCh37>",
    "contig.40": "<ID=GL000248.1,length=39786,assembly=GRCh37>",
    "contig.41": "<ID=GL000244.1,length=39929,assembly=GRCh37>",
    "contig.42": "<ID=GL000238.1,length=39939,assembly=GRCh37>",
    "contig.43": "<ID=GL000202.1,length=40103,assembly=GRCh37>",
    "contig.44": "<ID=GL000234.1,length=40531,assembly=GRCh37>",
    "contig.45": "<ID=GL000232.1,length=40652,assembly=GRCh37>",
    "contig.46": "<ID=GL000206.1,length=41001,assembly=GRCh37>",
    "contig.47": "<ID=GL000240.1,length=41933,assembly=GRCh37>",
    "contig.48": "<ID=GL000236.1,length=41934,assembly=GRCh37>",
    "contig.49": "<ID=GL000241.1,length=42152,assembly=GRCh37>",
    "contig.50": "<ID=GL000243.1,length=43341,assembly=GRCh37>",
    "contig.51": "<ID=GL000242.1,length=43523,assembly=GRCh37>",
    "contig.52": "<ID=GL000230.1,length=43691,assembly=GRCh37>",
    "contig.53": "<ID=GL000237.1,length=45867,assembly=GRCh37>",
    "contig.54": "<ID=GL000233.1,length=45941,assembly=GRCh37>",
    "contig.55": "<ID=GL000204.1,length=81310,assembly=GRCh37>",
    "contig.56": "<ID=GL000198.1,length=90085,assembly=GRCh37>",
    "contig.57": "<ID=GL000208.1,length=92689,assembly=GRCh37>",
    "contig.58": "<ID=GL000191.1,length=106433,assembly=GRCh37>",
    "contig.59": "<ID=GL000227.1,length=128374,assembly=GRCh37>",
    "contig.60": "<ID=GL000228.1,length=129120,assembly=GRCh37>",
    "contig.61": "<ID=GL000214.1,length=137718,assembly=GRCh37>",
    "contig.62": "<ID=GL000221.1,length=155397,assembly=GRCh37>",
    "contig.63": "<ID=GL000209.1,length=159169,assembly=GRCh37>",
    "contig.64": "<ID=GL000218.1,length=161147,assembly=GRCh37>",
    "contig.65": "<ID=GL000220.1,length=161802,assembly=GRCh37>",
    "contig.66": "<ID=GL000213.1,length=164239,assembly=GRCh37>",
    "contig.67": "<ID=GL000211.1,length=166566,assembly=GRCh37>",
    "contig.68": "<ID=GL000199.1,length=169874,assembly=GRCh37>",
    "contig.69": "<ID=GL000217.1,length=172149,assembly=GRCh37>",
    "contig.70": "<ID=GL000216.1,length=172294,assembly=GRCh37>",
    "contig.71": "<ID=GL000215.1,length=172545,assembly=GRCh37>",
    "contig.72": "<ID=GL000205.1,length=174588,assembly=GRCh37>",
    "contig.73": "<ID=GL000219.1,length=179198,assembly=GRCh37>",
    "contig.74": "<ID=GL000224.1,length=179693,assembly=GRCh37>",
    "contig.75": "<ID=GL000223.1,length=180455,assembly=GRCh37>",
    "contig.76": "<ID=GL000195.1,length=182896,assembly=GRCh37>",
    "contig.77": "<ID=GL000212.1,length=186858,assembly=GRCh37>",
    "contig.78": "<ID=GL000222.1,length=186861,assembly=GRCh37>",
    "contig.79": "<ID=GL000200.1,length=187035,assembly=GRCh37>",
    "contig.80": "<ID=GL000193.1,length=189789,assembly=GRCh37>",
    "contig.81": "<ID=GL000194.1,length=191469,assembly=GRCh37>",
    "contig.82": "<ID=GL000225.1,length=211173,assembly=GRCh37>",
    "contig.83": "<ID=GL000192.1,length=547496,assembly=GRCh37>",
    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_6139_3.vcf.gz --id UKB-b:17097 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_6139_3.txt.gz --cohort_cases 40700 --cohort_controls 420698 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
    "file_date": "2019-09-12T23:18:53.912472",
    "bcftools_viewVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
    "bcftools_viewCommand": "view -T ^/mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17097/mac_discard.txt -Oz /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17097/UKB-b-17097_raw.vcf.gz; Date=Thu Oct 17 12:34:28 2019",
    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-17097/ukb-b-17097.vcf.gz; Date=Sun May 10 14:31:35 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/public/UKB-b-17097/UKB-b-17097_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17097/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:33 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17097/UKB-b-17097_data.vcf.gz ...
Read summary statistics for 7946894 SNPs.
Dropped 6037 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1281837 SNPs remain.
After merging with regression SNP LD, 1281837 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0202 (0.0014)
Lambda GC: 1.2198
Mean Chi^2: 1.2336
Intercept: 1.0509 (0.0075)
Ratio: 0.2178 (0.0319)
Analysis finished at Thu Oct 17 14:46:50 2019
Total time elapsed: 1.0m:16.41s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9426,
    "inflation_factor": 1.1999,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "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": 74172,
    "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": 1281837,
    "ldsc_nsnp_merge_regression_ld": 1281837,
    "ldsc_observed_scale_h2_beta": 0.0202,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0509,
    "ldsc_intercept_se": 0.0075,
    "ldsc_lambda_gc": 1.2198,
    "ldsc_mean_chisq": 1.2336,
    "ldsc_ratio": 0.2179
}

Flags

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 FALSE
ldsc_intercept_beta FALSE
n_clumped_hits FALSE
r2_sum1 FALSE
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 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 7940884 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 7946894 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 8.660951e+00 5.763517e+00 1.000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.870049e+07 5.641787e+07 828.000000 3.225211e+07 6.916728e+07 1.145444e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.150000e-05 1.517400e-03 -0.016146 -7.419000e-04 -7.700000e-06 7.180000e-04 1.656190e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.237600e-03 7.361000e-04 0.000569 6.581000e-04 9.126000e-04 1.624900e-03 7.002700e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.732549e-01 2.956042e-01 0.000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.732552e-01 2.955787e-01 0.000000 2.107698e-01 4.630260e-01 7.293137e-01 9.999997e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.470014e-01 2.607576e-01 0.008600 3.640500e-02 1.385930e-01 3.910890e-01 9.914000e-01 ▇▂▂▁▁
numeric AF_reference 74172 0.9906665 NA NA NA NA NA NA NA 2.462322e-01 2.525964e-01 0.000000 3.873800e-02 1.539540e-01 3.863820e-01 1.000000e+00 ▇▃▂▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C 0.0004854 0.0010470 0.6400000 0.6429686 0.623779 0.7821490 NA
1 54676 rs2462492 C T -0.0003026 0.0010372 0.7700005 0.7704544 0.400411 NA NA
1 86028 rs114608975 T C -0.0007773 0.0016583 0.6400000 0.6392693 0.103549 0.0277556 NA
1 91536 rs6702460 G T 0.0004961 0.0010213 0.6300007 0.6271371 0.456858 0.4207270 NA
1 234313 rs8179466 C T -0.0005471 0.0020135 0.7899998 0.7858431 0.074509 NA NA
1 534192 rs6680723 C T 0.0012222 0.0011666 0.2900000 0.2947826 0.240965 NA NA
1 546697 rs12025928 A G -0.0001002 0.0014554 0.9500000 0.9451063 0.913480 NA NA
1 693731 rs12238997 A G -0.0010334 0.0009775 0.2900000 0.2904266 0.116331 0.1417730 NA
1 705882 rs72631875 G A -0.0003536 0.0014326 0.8100000 0.8050291 0.067283 0.0315495 NA
1 706368 rs55727773 A G 0.0000263 0.0007241 0.9699999 0.9710757 0.515650 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0003535 0.0008738 0.6899999 0.6857700 0.137946 0.2052720 NA
22 51219387 rs9616832 T C -0.0005417 0.0011343 0.6300007 0.6329396 0.073738 0.0654952 NA
22 51219704 rs147475742 G A 0.0003620 0.0015201 0.8100000 0.8117999 0.041948 0.0473243 NA
22 51221190 rs369304721 G A -0.0013401 0.0015176 0.3800004 0.3772188 0.049727 NA NA
22 51221731 rs115055839 T C -0.0006062 0.0011350 0.5900000 0.5932901 0.073229 0.0625000 NA
22 51222100 rs114553188 G T 0.0000122 0.0013360 0.9900000 0.9927118 0.054466 0.0880591 NA
22 51223637 rs375798137 G A -0.0000253 0.0013425 0.9800000 0.9849706 0.054095 0.0788738 NA
22 51229805 rs9616985 T C -0.0004646 0.0011391 0.6800001 0.6833943 0.073064 0.0730831 NA
22 51232488 rs376461333 A G 0.0005857 0.0026827 0.8300000 0.8271657 0.020053 NA NA
22 51237063 rs3896457 T C -0.0000679 0.0006967 0.9199999 0.9223896 0.297982 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623779 ES:SE:LP:AF:ID  0.000485353:0.00104703:0.19382:0.623779:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400411 ES:SE:LP:AF:ID  -0.000302629:0.00103718:0.113509:0.400411:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103549 ES:SE:LP:AF:ID  -0.000777289:0.00165832:0.19382:0.103549:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456858 ES:SE:LP:AF:ID  0.000496107:0.0010213:0.200659:0.456858:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074509 ES:SE:LP:AF:ID  -0.000547104:0.00201354:0.102373:0.074509:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240965 ES:SE:LP:AF:ID  0.00122218:0.00116655:0.537602:0.240965:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91348  ES:SE:LP:AF:ID  -0.000100212:0.00145544:0.0222764:0.91348:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116331 ES:SE:LP:AF:ID  -0.00103339:0.000977491:0.537602:0.116331:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067283 ES:SE:LP:AF:ID  -0.000353621:0.00143257:0.091515:0.067283:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  2.62567e-05:0.000724139:0.0132283:0.51565:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032979 ES:SE:LP:AF:ID  0.000238588:0.00182625:0.0457575:0.032979:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036592 ES:SE:LP:AF:ID  3.45353e-05:0.00165886:0.00877392:0.036592:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036709 ES:SE:LP:AF:ID  6.60692e-05:0.00165258:0.0132283:0.036709:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036409 ES:SE:LP:AF:ID  0.000216387:0.00166446:0.0457575:0.036409:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016399 ES:SE:LP:AF:ID  -0.00232502:0.00256263:0.443698:0.016399:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036948 ES:SE:LP:AF:ID  9.28336e-05:0.00164603:0.0177288:0.036948:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037047 ES:SE:LP:AF:ID  0.000143398:0.00164032:0.0315171:0.037047:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10123  ES:SE:LP:AF:ID  0.000611529:0.00119449:0.21467:0.10123:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959131 ES:SE:LP:AF:ID  0.000130312:0.00158223:0.0315171:0.959131:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031455 ES:SE:LP:AF:ID  0.0016204:0.00287067:0.244125:0.031455:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053268 ES:SE:LP:AF:ID  -0.00434177:0.00228311:1.24413:0.053268:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036563 ES:SE:LP:AF:ID  0.00019182:0.00165101:0.0409586:0.036563:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03688  ES:SE:LP:AF:ID  0.000120407:0.00163595:0.0268721:0.03688:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843235 ES:SE:LP:AF:ID  0.00104152:0.000847233:0.657577:0.843235:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055937 ES:SE:LP:AF:ID  -0.00104865:0.00137139:0.356547:0.055937:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122313 ES:SE:LP:AF:ID  -0.00122761:0.000927246:0.721246:0.122313:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025716 ES:SE:LP:AF:ID  -0.00210591:0.00228067:0.443698:0.025716:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121556 ES:SE:LP:AF:ID  -0.00132567:0.000927638:0.823909:0.121556:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132323 ES:SE:LP:AF:ID  -0.000557005:0.000914374:0.267606:0.132323:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011135 ES:SE:LP:AF:ID  0.000529876:0.00332405:0.0604807:0.011135:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036793 ES:SE:LP:AF:ID  0.000266509:0.00161945:0.0604807:0.036793:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838971 ES:SE:LP:AF:ID  0.00123422:0.000820482:0.886057:0.838971:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838599 ES:SE:LP:AF:ID  0.00124309:0.000819599:0.886057:0.838599:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869776 ES:SE:LP:AF:ID  0.00153152:0.000879404:1.08619:0.869776:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129874 ES:SE:LP:AF:ID  -0.00160399:0.000881187:1.16115:0.129874:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037303 ES:SE:LP:AF:ID  0.000407738:0.00159201:0.09691:0.037303:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037546 ES:SE:LP:AF:ID  0.000512207:0.00158195:0.124939:0.037546:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869119 ES:SE:LP:AF:ID  0.00152701:0.000877682:1.08619:0.869119:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869216 ES:SE:LP:AF:ID  0.00154155:0.000878029:1.10237:0.869216:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037505 ES:SE:LP:AF:ID  0.000537514:0.00158879:0.130768:0.037505:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869122 ES:SE:LP:AF:ID  0.00152176:0.000877664:1.08092:0.869122:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838051 ES:SE:LP:AF:ID  0.00112968:0.000817322:0.769551:0.838051:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037517 ES:SE:LP:AF:ID  0.000550317:0.00159103:0.136677:0.037517:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838682 ES:SE:LP:AF:ID  0.00121929:0.000819618:0.853872:0.838682:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013779 ES:SE:LP:AF:ID  0.003118:0.00286012:0.552842:0.013779:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839789 ES:SE:LP:AF:ID  0.00125993:0.000830686:0.886057:0.839789:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869402 ES:SE:LP:AF:ID  0.00154675:0.000876651:1.10791:0.869402:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868947 ES:SE:LP:AF:ID  0.00151905:0.000874443:1.08619:0.868947:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867902 ES:SE:LP:AF:ID  0.00150166:0.000872769:1.07058:0.867902:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869091 ES:SE:LP:AF:ID  0.00151832:0.00087516:1.08092:0.869091:rs4951929