QTLtools-mbv(1)

✨ QTLtools-mbv(1) ✨

okay bestie, welcome to the QTLtools-mbv(1) page 🎀 it's all bioinformatics tools energy, and it's giving very useful 🧬

✨ NAME ✨

QTLtools mbv - Match genotypes in a VCF to a BAM file 💖

✨ SYNOPSIS ✨

QTLtools mbv --bam [sample.bam|sample.sam|sample.cram] --vcf
[in.vcf|in.bcf|in.vcf.gz] --out output_file [OPTIONS]

so you pass --bam, --vcf, and --out, then add whatever [OPTIONS] you want 💅

✨ DESCRIPTION ✨

okay so this mode checks if the genotypes in the VCF are actually observed in the RNAseq reads in the BAM file 🕵️‍♀️ it's a quick way to catch sample mislabeling, cross-sample contamination, and PCR amplification bias. The details of the method are described at <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6044394/> if you want the full lore ✨

ngl here's the tea: for each individual in the VCF, we measure the proportions of heterozygous and homozygous genotypes where both alleles are captured by the sequencing reads in the BAM file. A 'match' should have close to 100% concordance for both measures 🙌 while a 'mismatch' has significantly lower concordance for both metrics 🙅‍♀️

the bias stuff is so specific 😭 increased cross-sample contamination leads to decreased homozygous concordance with no change in heterozygous concordance. Meanwhile, increased amplification bias leads to decreased heterozygous concordance with no change in homozygous concordance. Two different vibes, two different signatures 🦋

we recommend using uniquely mapping reads only, so set the correct --filter-mapping-quality 🫶

✨ OPTIONS ✨

• --vcf [in.vcf|in.bcf|in.vcf.gz] — your genotypes in VCF/BCF format. It should contain all the samples in the dataset. REQUIRED 💅
• --bam [in.bam|in.sam|in.cram] — your sequence data in BAM/SAM/CRAM format. REQUIRED 📖
• --out output — the output file name. REQUIRED 📝
• --reg chr:start-end — the genomic region you want processed, e.g. chr4:12334456-16334456, or chr5 🗺️
• --filter-mapping-quality integer — minimum mapping quality for a read or read pair to be considered. Set this to only include uniquely mapped reads 👑 DEFAULT=10
• --filter-base-quality integer — minimum phred quality for a base to be considered. DEFAULT=5 🍓
• --filter-binomial-pvalue float — binomial p-value threshold below which a heterozygous genotype is considered as showing allelic imbalance. DEFAULT=0.05 ⭐
• --filter-minimal-coverage integer — minimum number of reads overlapping a genotype for it to be considered. DEFAULT=10 🌸
• --filter-imputation-qual float — minimum imputation information score for a variant to be considered. DEFAULT=0.9 🧚
• --filter-imputation-prob float — minimum posterior probability for a genotype to be considered. DEFAULT=0.99 💜
• --filter-keep-duplicates — keeps reads the aligner flagged as duplicates 🔥

✨ OUTPUT FILE COLUMNS ✨

okay so for --out filename: this file does not have a header 🙈 It contains the following columns, in this order:

1. the sample ID in the VCF that the sequence data has been matched against 🫶
2. the number of missing genotypes for this sample
3. the total number of heterozygous genotypes examined
4. the total number of homozygous genotypes examined
5. the number of heterozygous genotypes considered for the matching, i.e. the ones covered by more than --filter-minimal-coverage
6. the number of homozygous genotypes considered for the matching, i.e. the ones covered by more than --filter-minimal-coverage
7. the number of heterozygous genotypes that match between this sample and the BAM file
8. the number of homozygous genotypes that match between this sample and the BAM file
9. the percentage of heterozygous genotypes that match between this sample and the BAM file 📊
10. the percentage of homozygous genotypes that match between this sample and the BAM file 📊
11. the number of heterozygous genotypes with significant allelic imbalance 🌈

✨ EXAMPLES ✨

Running mbv on an RNAseq sample mapped with GEM 🍓

QTLtools mbv --bam HG00381.chr22.bam --out HG00381.chr22.mbv.txt --vcf
genotypes.chr22.vcf.gz --filter-mapping-quality 150

then you can plot column 9 vs. 10 to find the genotyped sample in the VCF that matches your sequence data best. main character energy 👑

✨ SEE ALSO ✨

QTLtools(1) 📚

QTLtools website: <https://qtltools.github.io/qtltools> 🌐

✨ BUGS ✨

if you find a bug, submit it here 🐛 <https://github.com/qtltools/qtltools>

✨ CITATION ✨

Fort A., Panousis N. I., Garieri M. et al. MBV: a method to solve sample mislabeling and detect technical bias in large combined genotype and sequencing assay datasets, Bioinformatics 33(12), 1895 2017. <https://doi.org/10.1093/bioinformatics/btx074> 🎓

✨ AUTHORS ✨

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

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bestie that's the whole tea ✨ this is QTLtools-v1.3 from 06 May 2020, and you're literally going to ace your sample matching now 🦋 love you, mwah 💋🌈