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:8301,TotalVariants=9851866,VariantsNotRead=0,HarmonisedVariants=9851866,VariantsNotHarmonised=0,SwitchedAlleles=9851866,TotalControls=452114,TotalCases=10819,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_20003_1140923346.vcf.gz --id UKB-b:8301 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20003_1140923346.txt.gz --cohort_cases 10819 --cohort_controls 452114 --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": "2019-09-13T02:11:31.463614",
    "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-8301/mac_discard.txt -Oz /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8301/UKB-b-8301_raw.vcf.gz; Date=Thu Oct 17 12:20:23 2019",
    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-8301/ukb-b-8301.vcf.gz; Date=Sun May 10 12:38:47 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-8301/UKB-b-8301_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8301/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:26 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8301/UKB-b-8301_data.vcf.gz ...
Read summary statistics for 6065278 SNPs.
Dropped 2830 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, 1219161 SNPs remain.
After merging with regression SNP LD, 1219161 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0118 (0.0013)
Lambda GC: 1.1197
Mean Chi^2: 1.1341
Intercept: 1.0219 (0.0072)
Ratio: 0.1635 (0.0539)
Analysis finished at Thu Oct 17 14:42:36 2019
Total time elapsed: 1.0m:9.81s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9255,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 5.4339e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 11,
    "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": 55039,
    "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": 1219161,
    "ldsc_nsnp_merge_regression_ld": 1219161,
    "ldsc_observed_scale_h2_beta": 0.0118,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0219,
    "ldsc_intercept_se": 0.0072,
    "ldsc_lambda_gc": 1.1197,
    "ldsc_mean_chisq": 1.1341,
    "ldsc_ratio": 0.1633
}

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 6062467 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 6065278 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 8.669841e+00 5.761984e+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 7.858263e+07 5.652312e+07 828.0000000 3.199182e+07 6.902802e+07 1.145085e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 5.400000e-06 5.185000e-04 -0.0048534 -3.049000e-04 2.300000e-06 3.103000e-04 4.765900e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.670000e-04 1.605000e-04 0.0003029 3.352000e-04 4.042000e-04 5.604000e-04 1.685500e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.828563e-01 2.938263e-01 0.0000000 2.200002e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▆▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.828570e-01 2.938035e-01 0.0000000 2.234267e-01 4.768042e-01 7.379393e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.091983e-01 2.539630e-01 0.0323510 9.402700e-02 2.261510e-01 4.741640e-01 9.676490e-01 ▇▃▂▂▁
numeric AF_reference 55039 0.9909256 NA NA NA NA NA NA NA 3.058668e-01 2.469962e-01 0.0000000 1.030350e-01 2.340260e-01 4.648560e-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 0.0000970 0.0005574 0.8600001 0.8618075 0.623763 0.7821490 NA
1 54676 rs2462492 C T -0.0001136 0.0005522 0.8400000 0.8370346 0.400401 NA NA
1 86028 rs114608975 T C 0.0000466 0.0008828 0.9599999 0.9579177 0.103556 0.0277556 NA
1 91536 rs6702460 G T -0.0000622 0.0005437 0.9100000 0.9088744 0.456851 0.4207270 NA
1 234313 rs8179466 C T 0.0004097 0.0010720 0.6999999 0.7023290 0.074508 NA NA
1 534192 rs6680723 C T -0.0006577 0.0006210 0.2900000 0.2895751 0.240960 NA NA
1 546697 rs12025928 A G 0.0010780 0.0007748 0.1600000 0.1641160 0.913473 NA NA
1 693731 rs12238997 A G -0.0001596 0.0005205 0.7600007 0.7590922 0.116325 0.1417730 NA
1 705882 rs72631875 G A 0.0009414 0.0007627 0.2200002 0.2170738 0.067285 0.0315495 NA
1 706368 rs55727773 A G 0.0001401 0.0003855 0.7199992 0.7162810 0.515650 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0009885 0.0006025 0.1000000 0.1008599 0.073625 0.0826677 NA
22 51219006 rs28729663 G A 0.0007071 0.0004651 0.1299999 0.1284129 0.137953 0.2052720 NA
22 51219387 rs9616832 T C 0.0010132 0.0006037 0.0929994 0.0932718 0.073747 0.0654952 NA
22 51219704 rs147475742 G A 0.0018415 0.0008090 0.0230001 0.0228295 0.041955 0.0473243 NA
22 51221190 rs369304721 G A 0.0015580 0.0008077 0.0539995 0.0537336 0.049731 NA NA
22 51221731 rs115055839 T C 0.0010179 0.0006041 0.0920005 0.0919928 0.073238 0.0625000 NA
22 51222100 rs114553188 G T 0.0001026 0.0007112 0.8900000 0.8852443 0.054459 0.0880591 NA
22 51223637 rs375798137 G A 0.0001103 0.0007147 0.8800001 0.8773134 0.054088 0.0788738 NA
22 51229805 rs9616985 T C 0.0009840 0.0006063 0.1000000 0.1045805 0.073073 0.0730831 NA
22 51237063 rs3896457 T C 0.0002997 0.0003708 0.4199997 0.4188814 0.297971 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  9.70242e-05:0.000557374:0.0655015:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -0.000113577:0.000552181:0.0757207:0.400401:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103556 ES:SE:LP:AF:ID  4.65841e-05:0.00088283:0.0177288:0.103556:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  -6.22309e-05:0.000543699:0.0409586:0.456851:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074508 ES:SE:LP:AF:ID  0.000409703:0.00107202:0.154902:0.074508:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24096  ES:SE:LP:AF:ID  -0.000657714:0.000621039:0.537602:0.24096:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913473 ES:SE:LP:AF:ID  0.001078:0.000774781:0.79588:0.913473:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116325 ES:SE:LP:AF:ID  -0.000159612:0.000520463:0.119186:0.116325:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067285 ES:SE:LP:AF:ID  0.000941409:0.000762678:0.657577:0.067285:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  0.000140116:0.000385534:0.142668:0.51565:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033004 ES:SE:LP:AF:ID  0.000840468:0.000971959:0.408935:0.033004:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036621 ES:SE:LP:AF:ID  0.000753751:0.000882849:0.408935:0.036621:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036737 ES:SE:LP:AF:ID  0.000715583:0.000879509:0.376751:0.036737:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036437 ES:SE:LP:AF:ID  0.000837445:0.000885847:0.468521:0.036437:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036976 ES:SE:LP:AF:ID  0.000716674:0.000876035:0.387216:0.036976:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037072 ES:SE:LP:AF:ID  0.000728865:0.000873034:0.39794:0.037072:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101199 ES:SE:LP:AF:ID  0.000151993:0.000636106:0.091515:0.101199:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959096 ES:SE:LP:AF:ID  -0.000400751:0.000842024:0.200659:0.959096:rs2977670
1   725060  rs865924913 A   T   .   PASS    AF=0.053254 ES:SE:LP:AF:ID  -0.0019741:0.001216:1:0.053254:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03659  ES:SE:LP:AF:ID  0.000726853:0.000878685:0.387216:0.03659:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036907 ES:SE:LP:AF:ID  0.000609925:0.000870686:0.318759:0.036907:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843212 ES:SE:LP:AF:ID  0.000133764:0.000451047:0.113509:0.843212:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055911 ES:SE:LP:AF:ID  -0.000262637:0.000730316:0.142668:0.055911:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122307 ES:SE:LP:AF:ID  -0.000307048:0.00049371:0.275724:0.122307:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121549 ES:SE:LP:AF:ID  -0.000303923:0.000493918:0.267606:0.121549:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13233  ES:SE:LP:AF:ID  0.000181826:0.000486805:0.148742:0.13233:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036821 ES:SE:LP:AF:ID  0.000511935:0.000861881:0.259637:0.036821:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838951 ES:SE:LP:AF:ID  0.000265493:0.000436807:0.267606:0.838951:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83858  ES:SE:LP:AF:ID  0.000320648:0.000436337:0.337242:0.83858:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869781 ES:SE:LP:AF:ID  0.0004273:0.000468207:0.443698:0.869781:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129871 ES:SE:LP:AF:ID  -0.000515994:0.000469166:0.568636:0.129871:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037332 ES:SE:LP:AF:ID  0.000493776:0.000847266:0.251812:0.037332:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037576 ES:SE:LP:AF:ID  0.00058125:0.000841912:0.309804:0.037576:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869123 ES:SE:LP:AF:ID  0.000501402:0.00046729:0.552842:0.869123:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:ID  0.000494625:0.000467476:0.537602:0.869221:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037534 ES:SE:LP:AF:ID  0.000484791:0.000845555:0.244125:0.037534:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869126 ES:SE:LP:AF:ID  0.000481645:0.000467281:0.522879:0.869126:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838033 ES:SE:LP:AF:ID  0.000333211:0.000435126:0.356547:0.838033:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037547 ES:SE:LP:AF:ID  0.000461683:0.000846749:0.229148:0.037547:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838664 ES:SE:LP:AF:ID  0.000330442:0.000436349:0.346787:0.838664:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839777 ES:SE:LP:AF:ID  0.000333553:0.00044225:0.346787:0.839777:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869405 ES:SE:LP:AF:ID  0.000458562:0.00046674:0.481486:0.869405:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868952 ES:SE:LP:AF:ID  0.000448727:0.000465566:0.468521:0.868952:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867905 ES:SE:LP:AF:ID  0.000472483:0.000464674:0.508638:0.867905:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869095 ES:SE:LP:AF:ID  0.000462966:0.000465947:0.49485:0.869095:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  0.000463729:0.000465983:0.49485:0.869104:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869112 ES:SE:LP:AF:ID  0.000462673:0.000465994:0.49485:0.869112:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869589 ES:SE:LP:AF:ID  0.000448073:0.000467273:0.468521:0.869589:rs3131954
1   759036  rs114525117 G   A   .   PASS    AF=0.037596 ES:SE:LP:AF:ID  0.000280327:0.000841791:0.130768:0.037596:rs114525117
1   760912  rs1048488   C   T   .   PASS    AF=0.838313 ES:SE:LP:AF:ID  0.000299438:0.0004343:0.309804:0.838313:rs1048488