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:15297,TotalVariants=9851866,VariantsNotRead=0,HarmonisedVariants=9851866,VariantsNotHarmonised=0,SwitchedAlleles=9851866,TotalControls=458921,TotalCases=1615,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_6147_7.vcf.gz --id UKB-b:15297 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_6147_7.txt.gz --cohort_cases 1615 --cohort_controls 458921 --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": "2019-09-13T01:53:41.100703",
    "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-15297/mac_discard.txt -Oz /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15297/UKB-b-15297_raw.vcf.gz; Date=Thu Oct 17 12:31:45 2019",
    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-15297/ukb-b-15297.vcf.gz; Date=Sun May 10 04:35:25 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-15297/UKB-b-15297_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15297/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15297/UKB-b-15297_data.vcf.gz ...
Read summary statistics for 2686335 SNPs.
Dropped 325 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, 675596 SNPs remain.
After merging with regression SNP LD, 675596 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0016 (0.0013)
Lambda GC: 1.0498
Mean Chi^2: 1.0399
Intercept: 1.0231 (0.0101)
Ratio: 0.5784 (0.2539)
Analysis finished at Thu Oct 17 14:44:43 2019
Total time elapsed: 37.28s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.789,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -8.3875e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "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": 21300,
    "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": 675596,
    "ldsc_nsnp_merge_regression_ld": 675596,
    "ldsc_observed_scale_h2_beta": 0.0016,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0231,
    "ldsc_intercept_se": 0.0101,
    "ldsc_lambda_gc": 1.0498,
    "ldsc_mean_chisq": 1.0399,
    "ldsc_ratio": 0.5789
}
 

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 TRUE
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 1.000000 4 58 0 2686013 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 2686335 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.660652e+00 5.767800e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.855848e+07 5.663222e+07 5687.0000000 3.173439e+07 6.895570e+07 1.147371e+08 2.492013e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA -8.000000e-07 1.349000e-04 -0.0007230 -9.200000e-05 -1.000000e-06 8.990000e-05 7.059000e-04 ▁▂▇▂▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 1.322000e-04 8.200000e-06 0.0001189 1.252000e-04 1.298000e-04 1.379000e-04 2.672000e-04 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.928869e-01 2.896919e-01 0.0000010 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.928873e-01 2.896630e-01 0.0000010 2.412613e-01 4.900202e-01 7.435063e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA NA NA 4.465097e-01 1.606652e-01 0.2167190 3.052640e-01 4.210230e-01 5.743215e-01 7.832810e-01 ▇▆▅▃▃
numeric AF_reference 21300 0.992071 NA NA NA NA NA NA NA 4.288913e-01 1.822431e-01 0.0001997 2.839460e-01 4.105430e-01 5.625000e-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 -0.0002904 0.0002188 0.1800002 0.1844031 0.623741 0.7821490 NA
1 54676 rs2462492 C T 0.0001961 0.0002167 0.3700002 0.3654752 0.400426 NA NA
1 91536 rs6702460 G T -0.0000524 0.0002134 0.8100000 0.8060371 0.456883 0.4207270 NA
1 534192 rs6680723 C T -0.0004587 0.0002438 0.0599998 0.0598753 0.240976 NA NA
1 706368 rs55727773 A G 0.0000793 0.0001513 0.5999997 0.6000981 0.515659 0.2751600 NA
1 763394 rs369924889 G A 0.0001419 0.0001774 0.4199997 0.4238911 0.706791 0.6176120 NA
1 768253 rs2977608 A C 0.0001145 0.0001448 0.4299995 0.4290870 0.761325 0.4894170 NA
1 776546 rs12124819 A G 0.0000249 0.0001617 0.8800001 0.8774104 0.265403 0.0756789 NA
1 808631 rs11240779 G A 0.0001894 0.0001470 0.2000000 0.1976726 0.772651 0.4534740 NA
1 808928 rs11240780 C T 0.0001826 0.0001472 0.2099999 0.2149409 0.772876 0.4522760 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51180501 rs5770999 T C -0.0000452 0.0001424 0.7499995 0.7510887 0.713670 0.6369810 NA
22 51181919 rs9616825 G C -0.0000413 0.0001417 0.7700005 0.7709629 0.695475 0.6194090 NA
22 51182485 rs6009961 A G -0.0000308 0.0001429 0.8300000 0.8294194 0.715511 0.6383790 NA
22 51186143 rs2879914 T C -0.0000859 0.0001325 0.5199996 0.5165471 0.381789 0.2733630 NA
22 51186228 rs3865766 C T -0.0001614 0.0001291 0.2099999 0.2113965 0.451031 0.4532750 NA
22 51197266 rs61290853 A G -0.0000349 0.0001333 0.7899998 0.7936720 0.386331 0.4229230 NA
22 51198027 rs34939255 A G 0.0001065 0.0001509 0.4799997 0.4802647 0.254597 0.0984425 NA
22 51211106 rs9628250 T C 0.0000247 0.0001496 0.8700001 0.8688506 0.271583 0.1671330 NA
22 51212875 rs2238837 A C -0.0000148 0.0001422 0.9199999 0.9168673 0.331417 0.3724040 NA
22 51237063 rs3896457 T C -0.0000008 0.0001455 1.0000000 0.9955543 0.297968 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623741 ES:SE:LP:AF:ID  -0.000290375:0.000218768:0.744727:0.623741:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400426 ES:SE:LP:AF:ID  0.000196133:0.000216726:0.431798:0.400426:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456883 ES:SE:LP:AF:ID  -5.23976e-05:0.000213396:0.091515:0.456883:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240976 ES:SE:LP:AF:ID  -0.000458716:0.000243776:1.22185:0.240976:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515659 ES:SE:LP:AF:ID  7.93257e-05:0.00015131:0.221849:0.515659:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706791 ES:SE:LP:AF:ID  0.000141892:0.000177434:0.376751:0.706791:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761325 ES:SE:LP:AF:ID  0.000114495:0.000144792:0.366532:0.761325:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265403 ES:SE:LP:AF:ID  2.4949e-05:0.000161741:0.0555173:0.265403:rs12124819
1   808631  rs11240779  G   A   .   PASS    AF=0.772651 ES:SE:LP:AF:ID  0.000189367:0.000147:0.69897:0.772651:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772876 ES:SE:LP:AF:ID  0.0001826:0.000147247:0.677781:0.772876:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340418 ES:SE:LP:AF:ID  -7.85517e-05:0.000207518:0.148742:0.340418:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.69728  ES:SE:LP:AF:ID  -1.22609e-05:0.000138809:0.0315171:0.69728:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705437 ES:SE:LP:AF:ID  -3.72242e-05:0.000136301:0.107905:0.705437:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705482 ES:SE:LP:AF:ID  -3.70208e-05:0.000136296:0.102373:0.705482:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705668 ES:SE:LP:AF:ID  -3.85285e-05:0.000136303:0.107905:0.705668:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705697 ES:SE:LP:AF:ID  -3.88721e-05:0.000136317:0.107905:0.705697:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730165 ES:SE:LP:AF:ID  -5.20884e-05:0.000140032:0.148742:0.730165:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294336 ES:SE:LP:AF:ID  3.92954e-05:0.000136311:0.113509:0.294336:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236672 ES:SE:LP:AF:ID  0.000111801:0.000145125:0.356547:0.236672:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.23666  ES:SE:LP:AF:ID  0.000111908:0.000145127:0.356547:0.23666:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.239718 ES:SE:LP:AF:ID  9.3542e-05:0.00014466:0.283997:0.239718:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236662 ES:SE:LP:AF:ID  0.000111869:0.000145126:0.356547:0.236662:rs28484835
1   834832  rs4411087   G   C   .   PASS    AF=0.237146 ES:SE:LP:AF:ID  0.000116448:0.000145014:0.376751:0.237146:rs4411087
1   835499  rs4422948   A   G   .   PASS    AF=0.241121 ES:SE:LP:AF:ID  0.000113804:0.000144009:0.366532:0.241121:rs4422948
1   836896  rs28705752  T   C   .   PASS    AF=0.269473 ES:SE:LP:AF:ID  0.000119364:0.000138953:0.408935:0.269473:rs28705752
1   838555  rs4970383   C   A   .   PASS    AF=0.246169 ES:SE:LP:AF:ID  0.000132927:0.000143017:0.455932:0.246169:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.269984 ES:SE:LP:AF:ID  0.000117768:0.000139052:0.39794:0.269984:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400109 ES:SE:LP:AF:ID  5.78983e-05:0.000125722:0.187087:0.400109:rs4970382
1   841085  rs1574243   C   G   .   PASS    AF=0.23708  ES:SE:LP:AF:ID  0.000126241:0.000146037:0.408935:0.23708:rs1574243
1   842362  rs28540380  C   T   .   PASS    AF=0.235298 ES:SE:LP:AF:ID  0.000147664:0.000148219:0.49485:0.235298:rs28540380
1   843405  rs11516185  A   G   .   PASS    AF=0.362604 ES:SE:LP:AF:ID  0.000113636:0.000156081:0.327902:0.362604:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.590429 ES:SE:LP:AF:ID  -4.19808e-05:0.000125381:0.130768:0.590429:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603808 ES:SE:LP:AF:ID  -2.58732e-05:0.000126081:0.0757207:0.603808:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.604024 ES:SE:LP:AF:ID  -9.2193e-06:0.000126064:0.0268721:0.604024:rs6657440
1   851204  rs28552953  G   C   .   PASS    AF=0.224605 ES:SE:LP:AF:ID  0.000217449:0.000149129:0.853872:0.224605:rs28552953
1   852037  rs4970463   G   A   .   PASS    AF=0.589783 ES:SE:LP:AF:ID  -3.93402e-05:0.000125586:0.124939:0.589783:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.589765 ES:SE:LP:AF:ID  -4.8311e-05:0.00012553:0.154902:0.589765:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.607761 ES:SE:LP:AF:ID  -2.81081e-05:0.000126345:0.0861861:0.607761:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.607918 ES:SE:LP:AF:ID  -2.08094e-05:0.000126363:0.0604807:0.607918:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.6104   ES:SE:LP:AF:ID  -2.57074e-05:0.000126486:0.0757207:0.6104:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.603368 ES:SE:LP:AF:ID  -2.64357e-05:0.000126112:0.0809219:0.603368:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.610422 ES:SE:LP:AF:ID  -2.65388e-05:0.000126489:0.0809219:0.610422:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.389849 ES:SE:LP:AF:ID  2.10638e-05:0.000126513:0.0604807:0.389849:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.389833 ES:SE:LP:AF:ID  2.08852e-05:0.000126519:0.0604807:0.389833:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.350268 ES:SE:LP:AF:ID  5.17888e-05:0.000129967:0.161151:0.350268:rs4040605
1   858040  rs4970460   C   A   .   PASS    AF=0.217957 ES:SE:LP:AF:ID  0.000259447:0.000149544:1.08092:0.217957:rs4970460
1   858051  rs4970459   C   T   .   PASS    AF=0.219008 ES:SE:LP:AF:ID  0.000234178:0.000149022:0.920819:0.219008:rs4970459
1   858801  rs7418179   A   G   .   PASS    AF=0.765871 ES:SE:LP:AF:ID  -0.0002663:0.000145887:1.16749:0.765871:rs7418179
1   860416  rs61464428  G   A   .   PASS    AF=0.766661 ES:SE:LP:AF:ID  -0.000310739:0.000145957:1.48149:0.766661:rs61464428
1   860688  rs60837925  G   A   .   PASS    AF=0.766125 ES:SE:LP:AF:ID  -0.000307744:0.000145855:1.45593:0.766125:rs60837925