QTLtools-rep(1)

✨ QTLtools-rep(1) β€” NAME ✨

Bestie, okay so this is the manual page for QTLtools rep πŸ¦‹ (the Bioinformatics tools crew) and its whole vibe is replicating QTL associations in an independent dataset πŸ’…

πŸ’– NAME

QTLtools rep β€” Replicate QTL associations in an independent dataset 🌸

πŸŽ€ SYNOPSIS

QTLtools rep --bed quantifications.bed.gz --vcf
[in.vcf|in.vcf.gz|in.bcf] --qtl qtls_external.txt --out output.txt
[OPTIONS]

🌈 DESCRIPTION

Okay so this mode takes phenotype-genotype pairs that were found in another dataset and checks whether the same genotype and phenotype are associated in this dataset 🧚 It's giving replication energy, no cap πŸ’œ

πŸ‘‘ OPTIONS

  • --vcf [in.vcf|in.bcf|in.vcf.gz|in.bed.gz] ... β€” Genotypes in VCF/BCF format, or another molecular phenotype in BED format. If there's a DS field in the genotype FORMAT of a variant (the dosage calculated from genotype probabilities, e.g. after imputation), that gets used as the genotype. If there's only the GT field in the genotype FORMAT, then that's used and it gets converted to a dosage. REQUIRED πŸ”₯
  • --bed quantifications.bed.gz ... β€” Molecular phenotype quantifications in BED format. REQUIRED πŸ’…
  • --qtl external_qtls.txt ... β€” The file listing the QTLs found in the external dataset. One phenotype-genotype pair per line, separated by a space, with the phenotype first. REQUIRED ✨
  • --out filename.txt β€” The output file name. REQUIRED πŸŽ€
  • --cov covariates.txt β€” Covariates to correct the phenotype data with 🌸
  • --normal β€” Rank normal transform the phenotype data so each phenotype is normally distributed. RECOMMENDED 🫢

πŸ¦‹ OUTPUT FILE

Okay so the output file is space separated and has these columns, bestie 🧚

  • Output file β€” the output file itself, with the columns listed below πŸ’–
    1. The phenotype ID
    2. The phenotype's chromosome
    3. The phenotype's start position
    4. The phenotype's end position
    5. The phenotype's strand
    6. The genotype ID
    7. The genotype's chromosome
    8. The genotype's start position
    9. The genotype's end position
    10. The p-value of the association
    11. The slope of the association

πŸ“ EXAMPLE

Replicate the results of dataset1 in dataset2, correcting dataset2's phenotypes with technical covariates and normal transforming them πŸ’…

QTLtools rep --bed dataset2.bed.gz --vcf dataset2.bcf --cov
dataset2.covariates.txt --qtl significant_qtls_dataset1.txt --normal
--out rep_results.txt

🌸 SEE ALSO

QTLtools(1) πŸ¦‹

QTLtools website: <https://qtltools.github.io/qtltools> πŸ’œ

😭 BUGS

Versions up to and including 1.2 have a bug when reading missing genotypes in VCF/BCF files. It affects variants with a DS field in their genotype FORMAT that have a missing genotype (DS field is .) in one of the samples. In that case, genotypes for all the samples are set to missing, which effectively removes this variant from the analyses πŸ’€

Please submit bugs to <https://github.com/qtltools/qtltools> πŸ™ˆ

🌈 CITATION

Delaneau O., Ongen H., Brown A. A., et al. A complete tool set for molecular QTL discovery and analysis. Nat Commun 8, 15452 (2017). <https://doi.org/10.1038/ncomms15452> πŸ‘‘

πŸ’œ AUTHORS

Olivier Delaneau (olivier.delaneau@gmail.com), Halit Ongen (halitongen@gmail.com) 🫢


Bestie, that's the whole thing! πŸŽ€ This is QTLtools v1.3, last updated 06 May 2020, and it's still giving main character energy πŸ’…βœ¨