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:8810,TotalVariants=9851866,VariantsNotRead=0,HarmonisedVariants=9851866,VariantsNotHarmonised=0,SwitchedAlleles=9851866,TotalControls=444148,TotalCases=17094,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_6142_6.vcf.gz --id UKB-b:8810 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_6142_6.txt.gz --cohort_cases 17094 --cohort_controls 444148 --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": "2019-09-13T01:51:36.732272",
    "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-8810/mac_discard.txt -Oz /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8810/UKB-b-8810_raw.vcf.gz; Date=Thu Oct 17 12:21:32 2019",
    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-8810/ukb-b-8810.vcf.gz; Date=Sun May 10 06:12:43 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-8810/UKB-b-8810_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8810/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8810/UKB-b-8810_data.vcf.gz ...
Read summary statistics for 6708614 SNPs.
Dropped 3863 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, 1252985 SNPs remain.
After merging with regression SNP LD, 1252985 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0096 (0.0012)
Lambda GC: 1.1133
Mean Chi^2: 1.1189
Intercept: 1.0319 (0.007)
Ratio: 0.2685 (0.0586)
Analysis finished at Thu Oct 17 14:43:58 2019
Total time elapsed: 1.0m:51.93s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.933,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -7.8783e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 17,
    "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": 61601,
    "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": 1252985,
    "ldsc_nsnp_merge_regression_ld": 1252985,
    "ldsc_observed_scale_h2_beta": 0.0096,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0319,
    "ldsc_intercept_se": 0.007,
    "ldsc_lambda_gc": 1.1133,
    "ldsc_mean_chisq": 1.1189,
    "ldsc_ratio": 0.2683
}

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 6704773 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 6708614 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 8.663076e+00 5.764526e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.861879e+07 5.648255e+07 828.0000000 3.208253e+07 6.906697e+07 1.145202e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -8.000000e-07 7.336000e-04 -0.0060366 -4.125000e-04 -1.700000e-06 4.083000e-04 7.872900e-03 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.491000e-04 2.770000e-04 0.0003790 4.252000e-04 5.351000e-04 8.046000e-04 3.316700e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.837895e-01 2.928625e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.837899e-01 2.928348e-01 0.0000000 2.263316e-01 4.782516e-01 7.375232e-01 9.999995e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.857067e-01 2.585234e-01 0.0204760 6.911800e-02 1.934200e-01 4.456100e-01 9.795240e-01 ▇▃▂▂▁
numeric AF_reference 61601 0.9908176 NA NA NA NA NA NA NA 2.835730e-01 2.507321e-01 0.0000000 7.807510e-02 2.040730e-01 4.377000e-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 0.0008160 0.0006976 0.2399999 0.2421114 0.623778 0.7821490 NA
1 54676 rs2462492 C T -0.0012668 0.0006910 0.0669993 0.0667433 0.400378 NA NA
1 86028 rs114608975 T C 0.0000365 0.0011048 0.9699999 0.9736684 0.103557 0.0277556 NA
1 91536 rs6702460 G T 0.0005095 0.0006805 0.4500005 0.4539799 0.456860 0.4207270 NA
1 234313 rs8179466 C T -0.0019462 0.0013412 0.1499999 0.1467541 0.074523 NA NA
1 534192 rs6680723 C T 0.0000845 0.0007772 0.9100000 0.9134718 0.240951 NA NA
1 546697 rs12025928 A G -0.0031762 0.0009695 0.0011000 0.0010527 0.913472 NA NA
1 693731 rs12238997 A G 0.0010396 0.0006513 0.1100001 0.1104266 0.116347 0.1417730 NA
1 705882 rs72631875 G A 0.0011995 0.0009545 0.2099999 0.2088819 0.067274 0.0315495 NA
1 706368 rs55727773 A G -0.0009533 0.0004825 0.0479999 0.0481713 0.515631 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0005110 0.0007541 0.5000000 0.4979839 0.073606 0.0826677 NA
22 51219006 rs28729663 G A 0.0001320 0.0005821 0.8200001 0.8206277 0.137948 0.2052720 NA
22 51219387 rs9616832 T C 0.0005109 0.0007556 0.5000000 0.4989384 0.073728 0.0654952 NA
22 51219704 rs147475742 G A 0.0000147 0.0010126 0.9900000 0.9884486 0.041940 0.0473243 NA
22 51221190 rs369304721 G A 0.0004585 0.0010109 0.6499995 0.6501537 0.049716 NA NA
22 51221731 rs115055839 T C 0.0004987 0.0007561 0.5099998 0.5095101 0.073220 0.0625000 NA
22 51222100 rs114553188 G T -0.0003937 0.0008900 0.6600001 0.6582432 0.054470 0.0880591 NA
22 51223637 rs375798137 G A -0.0003140 0.0008943 0.7300002 0.7254618 0.054101 0.0788738 NA
22 51229805 rs9616985 T C 0.0005256 0.0007589 0.4899999 0.4885313 0.073055 0.0730831 NA
22 51237063 rs3896457 T C -0.0002567 0.0004641 0.5800000 0.5801348 0.297948 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623778 ES:SE:LP:AF:ID  0.000815983:0.000697585:0.619789:0.623778:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400378 ES:SE:LP:AF:ID  -0.00126684:0.000690979:1.17393:0.400378:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103557 ES:SE:LP:AF:ID  3.64677e-05:0.00110482:0.0132283:0.103557:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45686  ES:SE:LP:AF:ID  0.000509529:0.000680464:0.346787:0.45686:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074523 ES:SE:LP:AF:ID  -0.00194622:0.00134121:0.823909:0.074523:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240951 ES:SE:LP:AF:ID  8.44529e-05:0.000777218:0.0409586:0.240951:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913472 ES:SE:LP:AF:ID  -0.00317624:0.000969535:2.95861:0.913472:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116347 ES:SE:LP:AF:ID  0.00103965:0.000651296:0.958607:0.116347:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067274 ES:SE:LP:AF:ID  0.0011995:0.000954525:0.677781:0.067274:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515631 ES:SE:LP:AF:ID  -0.00095333:0.00048249:1.31876:0.515631:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032996 ES:SE:LP:AF:ID  -0.000208342:0.00121652:0.0655015:0.032996:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036612 ES:SE:LP:AF:ID  9.16756e-06:0.00110501:0.00436481:0.036612:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036728 ES:SE:LP:AF:ID  -9.95184e-05:0.00110083:0.0315171:0.036728:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036428 ES:SE:LP:AF:ID  -0.000171096:0.00110874:0.0555173:0.036428:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036967 ES:SE:LP:AF:ID  -3.49928e-05:0.00109646:0.0132283:0.036967:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037064 ES:SE:LP:AF:ID  -9.91256e-05:0.00109272:0.0315171:0.037064:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101197 ES:SE:LP:AF:ID  0.0016522:0.000796057:1.42022:0.101197:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959109 ES:SE:LP:AF:ID  -8.41097e-06:0.00105394:0.00436481:0.959109:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031452 ES:SE:LP:AF:ID  0.00294633:0.00191265:0.920819:0.031452:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053261 ES:SE:LP:AF:ID  -0.000779647:0.00152138:0.21467:0.053261:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03658  ES:SE:LP:AF:ID  -8.84636e-05:0.00109982:0.0268721:0.03658:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036898 ES:SE:LP:AF:ID  8.89186e-06:0.00108977:0.00436481:0.036898:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843206 ES:SE:LP:AF:ID  -0.000929523:0.000564472:1:0.843206:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055925 ES:SE:LP:AF:ID  0.00148318:0.000913949:1:0.055925:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12233  ES:SE:LP:AF:ID  0.000947704:0.000617816:0.886057:0.12233:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025712 ES:SE:LP:AF:ID  -0.0016283:0.00152012:0.552842:0.025712:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121571 ES:SE:LP:AF:ID  0.000950038:0.000618085:0.920819:0.121571:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132336 ES:SE:LP:AF:ID  0.000786257:0.000609213:0.69897:0.132336:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.03681  ES:SE:LP:AF:ID  -4.95639e-05:0.0010788:0.0177288:0.03681:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838943 ES:SE:LP:AF:ID  -0.000870401:0.000546646:0.958607:0.838943:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838571 ES:SE:LP:AF:ID  -0.000856627:0.000546058:0.920819:0.838571:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86976  ES:SE:LP:AF:ID  -0.000910308:0.000585935:0.920819:0.86976:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129892 ES:SE:LP:AF:ID  0.000924222:0.00058712:0.920819:0.129892:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03732  ES:SE:LP:AF:ID  -0.000115763:0.00106052:0.0409586:0.03732:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037563 ES:SE:LP:AF:ID  -0.000121628:0.00105382:0.0409586:0.037563:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869102 ES:SE:LP:AF:ID  -0.000904368:0.000584786:0.920819:0.869102:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869201 ES:SE:LP:AF:ID  -0.000906976:0.000585019:0.920819:0.869201:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037522 ES:SE:LP:AF:ID  -0.000181983:0.00105837:0.0655015:0.037522:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869105 ES:SE:LP:AF:ID  -0.000901777:0.000584774:0.920819:0.869105:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838023 ES:SE:LP:AF:ID  -0.000840317:0.000544537:0.920819:0.838023:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037534 ES:SE:LP:AF:ID  -0.000148987:0.00105987:0.05061:0.037534:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838653 ES:SE:LP:AF:ID  -0.000842489:0.000546067:0.920819:0.838653:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839766 ES:SE:LP:AF:ID  -0.000831711:0.000553451:0.886057:0.839766:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869384 ES:SE:LP:AF:ID  -0.000902098:0.000584098:0.920819:0.869384:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868929 ES:SE:LP:AF:ID  -0.00086003:0.000582626:0.853872:0.868929:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867885 ES:SE:LP:AF:ID  -0.000868229:0.000581512:0.853872:0.867885:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869073 ES:SE:LP:AF:ID  -0.000880708:0.000583104:0.886057:0.869073:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869082 ES:SE:LP:AF:ID  -0.000881661:0.000583149:0.886057:0.869082:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869089 ES:SE:LP:AF:ID  -0.000884388:0.000583163:0.886057:0.869089:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869568 ES:SE:LP:AF:ID  -0.000918101:0.000584765:0.920819:0.869568:rs3131954