Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ plot

qq_plot

AF plot

af_plot

P-Z plot

pz_plot

beta_std plot

beta_std_plot

Metadata

{
    "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=ieu-b-43,TotalVariants=494577,VariantsNotRead=4,HarmonisedVariants=399503,VariantsNotHarmonised=95070,SwitchedAlleles=113606,NormalisedVariants=0,TotalControls=2509,TotalCases=515,StudyType=CaseControl>",
    "contig": "<ID=1,length=249250621,assembly=HG19/GRCh37>",
    "contig.1": "<ID=2,length=243199373,assembly=HG19/GRCh37>",
    "contig.2": "<ID=3,length=198022430,assembly=HG19/GRCh37>",
    "contig.3": "<ID=4,length=191154276,assembly=HG19/GRCh37>",
    "contig.4": "<ID=5,length=180915260,assembly=HG19/GRCh37>",
    "contig.5": "<ID=6,length=171115067,assembly=HG19/GRCh37>",
    "contig.6": "<ID=7,length=159138663,assembly=HG19/GRCh37>",
    "contig.7": "<ID=8,length=146364022,assembly=HG19/GRCh37>",
    "contig.8": "<ID=9,length=141213431,assembly=HG19/GRCh37>",
    "contig.9": "<ID=10,length=135534747,assembly=HG19/GRCh37>",
    "contig.10": "<ID=11,length=135006516,assembly=HG19/GRCh37>",
    "contig.11": "<ID=12,length=133851895,assembly=HG19/GRCh37>",
    "contig.12": "<ID=13,length=115169878,assembly=HG19/GRCh37>",
    "contig.13": "<ID=14,length=107349540,assembly=HG19/GRCh37>",
    "contig.14": "<ID=15,length=102531392,assembly=HG19/GRCh37>",
    "contig.15": "<ID=16,length=90354753,assembly=HG19/GRCh37>",
    "contig.16": "<ID=17,length=81195210,assembly=HG19/GRCh37>",
    "contig.17": "<ID=18,length=78077248,assembly=HG19/GRCh37>",
    "contig.18": "<ID=19,length=59128983,assembly=HG19/GRCh37>",
    "contig.19": "<ID=20,length=63025520,assembly=HG19/GRCh37>",
    "contig.20": "<ID=21,length=48129895,assembly=HG19/GRCh37>",
    "contig.21": "<ID=22,length=51304566,assembly=HG19/GRCh37>",
    "contig.22": "<ID=X,length=155270560,assembly=HG19/GRCh37>",
    "contig.23": "<ID=Y,length=59373566,assembly=HG19/GRCh37>",
    "contig.24": "<ID=MT,length=16569,assembly=HG19/GRCh37>",
    "contig.25": "<ID=GL000207.1,length=4262,assembly=HG19/GRCh37>",
    "contig.26": "<ID=GL000226.1,length=15008,assembly=HG19/GRCh37>",
    "contig.27": "<ID=GL000229.1,length=19913,assembly=HG19/GRCh37>",
    "contig.28": "<ID=GL000231.1,length=27386,assembly=HG19/GRCh37>",
    "contig.29": "<ID=GL000210.1,length=27682,assembly=HG19/GRCh37>",
    "contig.30": "<ID=GL000239.1,length=33824,assembly=HG19/GRCh37>",
    "contig.31": "<ID=GL000235.1,length=34474,assembly=HG19/GRCh37>",
    "contig.32": "<ID=GL000201.1,length=36148,assembly=HG19/GRCh37>",
    "contig.33": "<ID=GL000247.1,length=36422,assembly=HG19/GRCh37>",
    "contig.34": "<ID=GL000245.1,length=36651,assembly=HG19/GRCh37>",
    "contig.35": "<ID=GL000197.1,length=37175,assembly=HG19/GRCh37>",
    "contig.36": "<ID=GL000203.1,length=37498,assembly=HG19/GRCh37>",
    "contig.37": "<ID=GL000246.1,length=38154,assembly=HG19/GRCh37>",
    "contig.38": "<ID=GL000249.1,length=38502,assembly=HG19/GRCh37>",
    "contig.39": "<ID=GL000196.1,length=38914,assembly=HG19/GRCh37>",
    "contig.40": "<ID=GL000248.1,length=39786,assembly=HG19/GRCh37>",
    "contig.41": "<ID=GL000244.1,length=39929,assembly=HG19/GRCh37>",
    "contig.42": "<ID=GL000238.1,length=39939,assembly=HG19/GRCh37>",
    "contig.43": "<ID=GL000202.1,length=40103,assembly=HG19/GRCh37>",
    "contig.44": "<ID=GL000234.1,length=40531,assembly=HG19/GRCh37>",
    "contig.45": "<ID=GL000232.1,length=40652,assembly=HG19/GRCh37>",
    "contig.46": "<ID=GL000206.1,length=41001,assembly=HG19/GRCh37>",
    "contig.47": "<ID=GL000240.1,length=41933,assembly=HG19/GRCh37>",
    "contig.48": "<ID=GL000236.1,length=41934,assembly=HG19/GRCh37>",
    "contig.49": "<ID=GL000241.1,length=42152,assembly=HG19/GRCh37>",
    "contig.50": "<ID=GL000243.1,length=43341,assembly=HG19/GRCh37>",
    "contig.51": "<ID=GL000242.1,length=43523,assembly=HG19/GRCh37>",
    "contig.52": "<ID=GL000230.1,length=43691,assembly=HG19/GRCh37>",
    "contig.53": "<ID=GL000237.1,length=45867,assembly=HG19/GRCh37>",
    "contig.54": "<ID=GL000233.1,length=45941,assembly=HG19/GRCh37>",
    "contig.55": "<ID=GL000204.1,length=81310,assembly=HG19/GRCh37>",
    "contig.56": "<ID=GL000198.1,length=90085,assembly=HG19/GRCh37>",
    "contig.57": "<ID=GL000208.1,length=92689,assembly=HG19/GRCh37>",
    "contig.58": "<ID=GL000191.1,length=106433,assembly=HG19/GRCh37>",
    "contig.59": "<ID=GL000227.1,length=128374,assembly=HG19/GRCh37>",
    "contig.60": "<ID=GL000228.1,length=129120,assembly=HG19/GRCh37>",
    "contig.61": "<ID=GL000214.1,length=137718,assembly=HG19/GRCh37>",
    "contig.62": "<ID=GL000221.1,length=155397,assembly=HG19/GRCh37>",
    "contig.63": "<ID=GL000209.1,length=159169,assembly=HG19/GRCh37>",
    "contig.64": "<ID=GL000218.1,length=161147,assembly=HG19/GRCh37>",
    "contig.65": "<ID=GL000220.1,length=161802,assembly=HG19/GRCh37>",
    "contig.66": "<ID=GL000213.1,length=164239,assembly=HG19/GRCh37>",
    "contig.67": "<ID=GL000211.1,length=166566,assembly=HG19/GRCh37>",
    "contig.68": "<ID=GL000199.1,length=169874,assembly=HG19/GRCh37>",
    "contig.69": "<ID=GL000217.1,length=172149,assembly=HG19/GRCh37>",
    "contig.70": "<ID=GL000216.1,length=172294,assembly=HG19/GRCh37>",
    "contig.71": "<ID=GL000215.1,length=172545,assembly=HG19/GRCh37>",
    "contig.72": "<ID=GL000205.1,length=174588,assembly=HG19/GRCh37>",
    "contig.73": "<ID=GL000219.1,length=179198,assembly=HG19/GRCh37>",
    "contig.74": "<ID=GL000224.1,length=179693,assembly=HG19/GRCh37>",
    "contig.75": "<ID=GL000223.1,length=180455,assembly=HG19/GRCh37>",
    "contig.76": "<ID=GL000195.1,length=182896,assembly=HG19/GRCh37>",
    "contig.77": "<ID=GL000212.1,length=186858,assembly=HG19/GRCh37>",
    "contig.78": "<ID=GL000222.1,length=186861,assembly=HG19/GRCh37>",
    "contig.79": "<ID=GL000200.1,length=187035,assembly=HG19/GRCh37>",
    "contig.80": "<ID=GL000193.1,length=189789,assembly=HG19/GRCh37>",
    "contig.81": "<ID=GL000194.1,length=191469,assembly=HG19/GRCh37>",
    "contig.82": "<ID=GL000225.1,length=211173,assembly=HG19/GRCh37>",
    "contig.83": "<ID=GL000192.1,length=547496,assembly=HG19/GRCh37>",
    "Gwas2VCF_command": "--data /data/cromwell-executions/qc/a11061ae-78f0-4fcd-99aa-578156004707/call-vcf/inputs/562856221/upload.txt.gz --id ieu-b-43 --json /data/cromwell-executions/qc/a11061ae-78f0-4fcd-99aa-578156004707/call-vcf/inputs/562856221/ieu-b-43_data.json --ref /data/cromwell-executions/qc/a11061ae-78f0-4fcd-99aa-578156004707/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/a11061ae-78f0-4fcd-99aa-578156004707/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-43/ieu-b-43.vcf.gz --rm_chr_prefix --cohort_cases 515 --cohort_controls 2509; 1.2.1",
    "file_date": "2020-08-21T17:35:19.321143",
    "bcftools_viewVersion": "1.9+htslib-1.9",
    "bcftools_viewCommand": "view -h /data/igd/ieu-b-43/ieu-b-43.vcf.gz; Date=Thu Feb 25 02:21:57 2021"
}
 

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 /data/cromwell-executions/qc/a11061ae-78f0-4fcd-99aa-578156004707/call-ldsc/inputs/562856221/ieu-b-43.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-43/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Fri Aug 21 17:39:07 2020
Reading summary statistics from /data/cromwell-executions/qc/a11061ae-78f0-4fcd-99aa-578156004707/call-ldsc/inputs/562856221/ieu-b-43.vcf.gz ...
Traceback (most recent call last):
  File "./ldsc/ldsc.py", line 647, in <module>
    sumstats.estimate_h2(args, log)
  File "/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
    args, log, args.h2)
  File "/ldsc/ldscore/sumstats.py", line 246, in _read_ld_sumstats
    sumstats = _read_sumstats(args, log, fh, alleles=alleles, dropna=dropna)
  File "/ldsc/ldscore/sumstats.py", line 167, in _read_sumstats
    sumstats = ps.sumstats(fh, alleles=alleles, dropna=dropna)
  File "/ldsc/ldscore/parse.py", line 85, in sumstats
    x = read_vcf(fh, alleles, slh)
  File "/ldsc/ldscore/parse.py", line 137, in read_vcf
    o = [[rec.id, rec.samples[sample]['ES'][0]/rec.samples[sample]['SE'][0], rec.samples[sample]['SS'][0]] for rec in vcf_in.fetch()]
ZeroDivisionError: float division by zero

Analysis finished at Fri Aug 21 17:39:07 2020
Total time elapsed: 0.05s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.913,
    "inflation_factor": 1.0581,
    "mean_EFFECT": 0.0014,
    "n": 3024,
    "n_snps": 399503,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 964,
    "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": 2283,
    "n_est": 3030.2449,
    "ratio_se_n": 1.001,
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": 2.6617,
    "sd_y_est2": 2.6645,
    "r2_sum1": 0.115,
    "r2_sum2": 0.0162,
    "r2_sum3": 0.0162,
    "r2_sum4": 0.0148,
    "ldsc_nsnp_merge_refpanel_ld": "NA",
    "ldsc_nsnp_merge_regression_ld": "NA",
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": "NA",
    "ldsc_intercept_se": "NA",
    "ldsc_lambda_gc": "NA",
    "ldsc_mean_chisq": "NA",
    "ldsc_ratio": "NA"
}
 

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq NA
n_p_sig FALSE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio NA
ldsc_intercept_beta NA
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 25 0 399503 0 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
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.935680e+00 5.844948e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▆▅▃▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.756593e+07 5.666760e+07 3.30120e+04 3.048904e+07 6.804957e+07 1.142195e+08 2.492107e+08 ▇▆▃▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.445100e-03 1.045390e-01 -1.64818e+00 -5.921190e-02 1.801600e-03 6.208820e-02 1.095270e+00 ▁▁▇▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.442260e-02 3.654460e-02 0.00000e+00 7.132100e-02 8.119480e-02 1.040560e-01 5.483830e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.912069e-01 2.908254e-01 0.00000e+00 2.378001e-01 4.878002e-01 7.422001e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 964 0.9975870 NA NA NA NA NA 4.899817e-01 2.901067e-01 0.00000e+00 2.372260e-01 4.866606e-01 7.404859e-01 9.996910e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 3.592723e-01 2.545821e-01 1.00057e-02 1.423720e-01 2.981750e-01 5.405390e-01 9.899170e-01 ▇▆▃▃▂
numeric AF_reference 2283 0.9942854 NA NA NA NA NA 3.611443e-01 2.407581e-01 1.99700e-04 1.615420e-01 3.043130e-01 5.307510e-01 9.974040e-01 ▇▇▅▃▂
numeric N 0 1.0000000 NA NA NA NA NA 3.024000e+03 0.000000e+00 3.02400e+03 3.024000e+03 3.024000e+03 3.024000e+03 3.024000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 768448 rs12562034 G A 0.0256677 0.1101710 0.8158000 0.8157765 0.105726 0.191893 3024
1 1005806 rs3934834 C T 0.0459289 0.0955402 0.6307002 0.6307095 0.148488 0.223442 3024
1 1018704 rs9442372 A G 0.1103730 0.0694047 0.1118001 0.1117714 0.565981 0.611022 3024
1 1030565 rs6687776 C T 0.1972100 0.0899950 0.0284302 0.0284269 0.157866 0.306709 3024
1 1031540 rs9651273 A G 0.0573114 0.0776181 0.4603000 0.4602855 0.726524 0.881989 3024
1 1048955 rs4970405 A G 0.1371500 0.1089730 0.2082001 0.2081862 0.102731 0.110623 3024
1 1049950 rs12726255 A G 0.1527210 0.0951169 0.1083999 0.1083588 0.139536 0.289736 3024
1 1061166 rs11807848 T C 0.0487902 0.0693473 0.4817004 0.4817049 0.413427 0.329673 3024
1 1062638 rs9442373 C A -0.0109399 0.0665660 0.8695000 0.8694582 0.546023 0.574281 3024
1 1064979 rs2298217 C T 0.0582689 0.0946618 0.5382004 0.5381928 0.150994 0.164736 3024
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51123505 rs9616816 G A 0.0554347 0.0814161 0.4958999 0.4959466 0.2263520 0.3783950 3024
22 51146139 rs5770992 A G 0.0713900 0.1050080 0.4966003 0.4965976 0.1161600 0.1136180 3024
22 51147015 rs2040487 A G 0.0401818 0.0699475 0.5656998 0.5656589 0.4133520 0.4556710 3024
22 51150473 rs5770820 G A 0.0079682 0.0833507 0.9238001 0.9238398 0.2318380 0.2462060 3024
22 51151724 rs6010061 C T 0.0459289 0.0697014 0.5099000 0.5099356 0.3985900 0.6098240 3024
22 51163138 rs715586 C T 0.0198026 0.0929076 0.8311999 0.8312155 0.1541430 0.0902556 3024
22 51165664 rs8137951 G A -0.0366640 0.0753759 0.6267004 0.6266727 0.2946060 0.4063500 3024
22 51171693 rs756638 G A -0.0314907 0.0769210 0.6822994 0.6822534 0.2760440 0.3049120 3024
22 51175626 rs3810648 A G -0.0441609 0.1502820 0.7689002 0.7688698 0.0564032 0.1084270 3024
22 51178090 rs2285395 G A -0.0350056 0.1620390 0.8289999 0.8289628 0.0479109 0.0666933 3024

bcf preview

1   768448  rs12562034  G   A   .   PASS    AF=0.105726 ES:SE:LP:AF:SS:NC:ID    0.0256677:0.110171:0.0884163:0.105726:3024:515:rs12562034
1   1005806 rs3934834   C   T   .   PASS    AF=0.148488 ES:SE:LP:AF:SS:NC:ID    0.0459289:0.0955402:0.200177:0.148488:3024:515:rs3934834
1   1018704 rs9442372   A   G   .   PASS    AF=0.565981 ES:SE:LP:AF:SS:NC:ID    0.110373:0.0694047:0.951558:0.565981:3024:515:rs9442372
1   1030565 rs6687776   C   T   .   PASS    AF=0.157866 ES:SE:LP:AF:SS:NC:ID    0.19721:0.089995:1.54622:0.157866:3024:515:rs6687776
1   1031540 rs776599533 A   G   .   PASS    AF=0.726524 ES:SE:LP:AF:SS:NC:ID    0.0573114:0.0776181:0.336959:0.726524:3024:515:rs776599533
1   1048955 rs4970405   A   G   .   PASS    AF=0.102731 ES:SE:LP:AF:SS:NC:ID    0.13715:0.108973:0.681519:0.102731:3024:515:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.139536 ES:SE:LP:AF:SS:NC:ID    0.152721:0.0951169:0.964971:0.139536:3024:515:rs12726255
1   1061166 rs11807848  T   C   .   PASS    AF=0.413427 ES:SE:LP:AF:SS:NC:ID    0.0487902:0.0693473:0.317223:0.413427:3024:515:rs11807848
1   1062638 rs9442373   C   A   .   PASS    AF=0.546023 ES:SE:LP:AF:SS:NC:ID    -0.0109399:0.066566:0.0607304:0.546023:3024:515:rs9442373
1   1064979 rs2298217   C   T   .   PASS    AF=0.150994 ES:SE:LP:AF:SS:NC:ID    0.0582689:0.0946618:0.269056:0.150994:3024:515:rs2298217
1   1066029 rs12145826  G   A   .   PASS    AF=0.0720194    ES:SE:LP:AF:SS:NC:ID    -0.130564:0.137398:0.465974:0.0720194:3024:515:rs12145826
1   1087683 rs9442380   T   C   .   PASS    AF=0.929896 ES:SE:LP:AF:SS:NC:ID    0.115186:0.138468:0.392009:0.929896:3024:515:rs9442380
1   1090557 rs7553429   A   C   .   PASS    AF=0.0272798    ES:SE:LP:AF:SS:NC:ID    0.08158:0.204526:0.161214:0.0272798:3024:515:rs7553429
1   1094738 rs4970362   A   G   .   PASS    AF=0.644355 ES:SE:LP:AF:SS:NC:ID    0.00682323:0.071378:0.034422:0.644355:3024:515:rs4970362
1   1099342 rs9660710   A   C   .   PASS    AF=0.931713 ES:SE:LP:AF:SS:NC:ID    0.081644:0.138859:0.254535:0.931713:3024:515:rs9660710
1   1106473 rs4970420   G   A   .   PASS    AF=0.188064 ES:SE:LP:AF:SS:NC:ID    -0.00521357:0.0874041:0.0211806:0.188064:3024:515:rs4970420
1   1119858 rs1320565   C   T   .   PASS    AF=0.0790578    ES:SE:LP:AF:SS:NC:ID    -0.0726782:0.12933:0.240937:0.0790578:3024:515:rs1320565
1   1121794 rs11260549  G   A   .   PASS    AF=0.120641 ES:SE:LP:AF:SS:NC:ID    0.0620354:0.103178:0.261537:0.120641:3024:515:rs11260549
1   1135242 rs9729550   A   C   .   PASS    AF=0.265005 ES:SE:LP:AF:SS:NC:ID    0.0305292:0.0779476:0.157828:0.265005:3024:515:rs9729550
1   1163804 rs7515488   C   T   .   PASS    AF=0.149761 ES:SE:LP:AF:SS:NC:ID    -0.0486652:0.097059:0.210349:0.149761:3024:515:rs7515488
1   1172907 rs715643    C   T   .   PASS    AF=0.0531373    ES:SE:LP:AF:SS:NC:ID    0.0573251:0.151486:0.151749:0.0531373:3024:515:rs715643
1   1176597 rs6675798   T   C   .   PASS    AF=0.0951217    ES:SE:LP:AF:SS:NC:ID    -0.0871932:0.119826:0.330869:0.0951217:3024:515:rs6675798
1   1192515 rs7524470   A   G   .   PASS    AF=0.0376963    ES:SE:LP:AF:SS:NC:ID    -0.0939811:0.184953:0.213746:0.0376963:3024:515:rs7524470
1   1194804 rs11804831  T   C   .   PASS    AF=0.183342 ES:SE:LP:AF:SS:NC:ID    -0.0462534:0.0893796:0.218388:0.183342:3024:515:rs11804831
1   1211292 rs6685064   C   T   .   PASS    AF=0.0661819    ES:SE:LP:AF:SS:NC:ID    -0.162166:0.144297:0.583193:0.0661819:3024:515:rs6685064
1   1425700 rs819980    T   C   .   PASS    AF=0.0782545    ES:SE:LP:AF:SS:NC:ID    -0.0933222:0.130895:0.322484:0.0782545:3024:515:rs819980
1   1462766 rs9439462   C   T   .   PASS    AF=0.0378735    ES:SE:LP:AF:SS:NC:ID    -0.242836:0.193251:0.680062:0.0378735:3024:515:rs9439462
1   1505255 rs6603793   C   T   .   PASS    AF=0.320414 ES:SE:LP:AF:SS:NC:ID    -0.13102:0.0744987:1.10436:0.320414:3024:515:rs6603793
1   1706136 rs6603811   T   C   .   PASS    AF=0.949834 ES:SE:LP:AF:SS:NC:ID    -0.0158733:0.160353:0.0356932:0.949834:3024:515:rs6603811
1   1706160 rs7531583   A   G   .   PASS    AF=0.77173  ES:SE:LP:AF:SS:NC:ID    -0.00598207:0.0816328:0.0261336:0.77173:3024:515:rs7531583
1   1745726 rs16825336  G   A   .   PASS    AF=0.0980834    ES:SE:LP:AF:SS:NC:ID    0.0256677:0.11293:0.0860802:0.0980834:3024:515:rs16825336
1   1781220 rs6681938   T   C   .   PASS    AF=0.296768 ES:SE:LP:AF:SS:NC:ID    -0.0208151:0.0752131:0.106793:0.296768:3024:515:rs6681938
1   1793111 rs10907192  A   G   .   PASS    AF=0.95454  ES:SE:LP:AF:SS:NC:ID    0.165111:0.172742:0.469544:0.95454:3024:515:rs10907192
1   1801034 rs1306328781    G   A   .   PASS    AF=0.267092 ES:SE:LP:AF:SS:NC:ID    -0.0825124:0.0783526:0.534171:0.267092:3024:515:rs1306328781
1   1810090 rs7525092   C   T   .   PASS    AF=0.267745 ES:SE:LP:AF:SS:NC:ID    -0.0774211:0.0782072:0.491874:0.267745:3024:515:rs7525092
1   1873625 rs12758705  G   A   .   PASS    AF=0.259702 ES:SE:LP:AF:SS:NC:ID    -0.0213258:0.078242:0.10502:0.259702:3024:515:rs12758705
1   1874581 rs2803329   A   G   .   PASS    AF=0.801328 ES:SE:LP:AF:SS:NC:ID    0.0193867:0.0859554:0.0853396:0.801328:3024:515:rs2803329
1   2024064 rs1455744253    C   T   .   PASS    AF=0.169139 ES:SE:LP:AF:SS:NC:ID    0.228728:0.0871005:2.06359:0.169139:3024:515:rs1455744253
1   2026749 rs884080    A   G   .   PASS    AF=0.45587  ES:SE:LP:AF:SS:NC:ID    0.0778865:0.0687889:0.589223:0.45587:3024:515:rs884080
1   2033256 rs908742    G   A   .   PASS    AF=0.329176 ES:SE:LP:AF:SS:NC:ID    0.0944007:0.0721057:0.720105:0.329176:3024:515:rs908742
1   2040936 rs4648808   T   C   .   PASS    AF=0.874966 ES:SE:LP:AF:SS:NC:ID    -0.001998:0.0931574:0.00749066:0.874966:3024:515:rs4648808
1   2043080 rs6603813   T   G   .   PASS    AF=0.260204 ES:SE:LP:AF:SS:NC:ID    0.00598207:0.077087:0.0277509:0.260204:3024:515:rs6603813
1   2051513 rs1190080979    T   G   .   PASS    AF=0.595941 ES:SE:LP:AF:SS:NC:ID    -0.0667236:0.0691149:0.475864:0.595941:3024:515:rs1190080979
1   2058023 rs3128291   A   G   .   PASS    AF=0.877285 ES:SE:LP:AF:SS:NC:ID    0.00440971:0.104579:0.0148431:0.877285:3024:515:rs3128291
1   2068906 rs3128296   G   T   .   PASS    AF=0.869567 ES:SE:LP:AF:SS:NC:ID    -0.0778865:0.0995767:0.36241:0.869567:3024:515:rs3128296
1   2069681 rs3753242   C   T   .   PASS    AF=0.0644843    ES:SE:LP:AF:SS:NC:ID    0.0497421:0.138333:0.14315:0.0644843:3024:515:rs3753242
1   2071340 rs424079    C   A   .   PASS    AF=0.605173 ES:SE:LP:AF:SS:NC:ID    -0.0695261:0.0701104:0.492954:0.605173:3024:515:rs424079
1   2096638 rs3052  C   T   .   PASS    AF=0.110286 ES:SE:LP:AF:SS:NC:ID    0.0525924:0.108652:0.201764:0.110286:3024:515:rs3052
1   2119833 rs2460002   A   G   .   PASS    AF=0.691536 ES:SE:LP:AF:SS:NC:ID    -0.0178399:0.0734894:0.0924812:0.691536:3024:515:rs2460002
1   2140261 rs6665593   G   A   .   PASS    AF=0.167569 ES:SE:LP:AF:SS:NC:ID    0.0372958:0.0920673:0.164056:0.167569:3024:515:rs6665593