QTLtools-fdensity(1)

🦋 QTLtools-fdensity(1) 🦋

okay bestie, this is the QTLtools-fdensity(1) page from the Bioinformatics tools manual, and it is all about measuring functional density around molecular QTLs 💖 no cap, it's giving science ✨

✨ NAME ✨

QTLtools fdensity — Functional density around molecular QTLs 🌸

💖 SYNOPSIS 💖

QTLtools fdensity --qtl significant_genes.bed --bed TFs.encode.bed.gz --out output.txt [OPTIONS]

🎀 DESCRIPTION 🎀

okay so this mode measures how dense functional annotations are around the genomic positions of molecular QTLs 🧚 the method is detailed in https://www.nature.com/articles/ncomms15452 ✨

basically, we first list every annotation inside a window around the molecular QTLs (by default 1 Mb) 👀 then we chop that window into tiny bins (default 1 kb) and count how many functional annotations overlap each bin. that gives you an annotation count per bin you can plot, so you can see if there's any peak or depletion around the molQTLs 📈 it's the way that 💅

🌈 OPTIONS 🌈

• --qtl in.bed — your list of QTLs of interest, in BED format. REQUIRED. 🦋
• --bed functional_annotation.bed.gz — your functional annotations, in BED format. REQUIRED. 🍓
• --out output.txt — the output file. REQUIRED. 💜
• --window integer — the window size around the molecular QTL position. DEFAULT=1000000 🌸
• --bin integer — the bin size in base pairs. DEFAULT=1000 ⭐

📥 INPUT FILES 📥

--qtl file

your list of QTLs of interest 💅 here's an example:

1    15210     15211     1_15211   ENSG00000227232.4   -
1    735984    735985    1_735985  ENSG00000177757.1   +
1    735984    735985    1_735985  ENSG00000240453.1   -
1    739527    739528    1_739528  ENSG00000237491.4   +

and here's what each column means 🫶

• Column 1 — the variant chromosome
• Column 2 — the variant's start position (0-based)
• Column 3 — the variant's end position (1-based)
• Column 4 — the variant ID
• Column 5 — the phenotype ID (not used) 🙈
• Column 6 — the phenotype's strand

--bed file

the list of annotations in BED format, looking like this 🧚

1    254874    265487
1    730984    735985
1    734984    736585
1    739527    748528

the columns, bestie:

• Column 1 — chromosome
• Column 2 — start position (0-based)
• Column 3 — end position (1-based)

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📤 OUTPUT FILE 📤

--out file

the results come out as a space separated output file that details the enrichment 🔥 with these columns:

• Column 1 — the start position of the bin
• Column 2 — the end position of the bin
• Column 3 — the number of associations in this bin

🧪 EXAMPLE 🧪

okay so there are two steps, and they're both lowkey easy 🥹

1. You need to prepare a BED file containing the positions of the QTLs of interest. To do so, extract all significant hits at a given FDR threshold (e.g. 5%), and then transform the significant QTL list into a BED file:

Rscript ./script/qtltools_runFDR_cis.R results.genes.full.txt.gz 0.05 results.genes
cat results.genes.significant.txt | awk '{ print $9, $10-1, $11, $8, $1, $5 }' | tr ' ' '\t' | sort -k1,1V -k2,2g > results.genes.significant.bed

2. Measure the density using the following command:

QTLtools fdensity --qtl results.genes.significant.bed --bed TFs.encode.bed.gz --out density.TF.around.QTL.txt

🔗 SEE ALSO 🔗

QTLtools(1)

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

🐛 BUGS 🐛

found a bug? slide into the DMs of the project: https://github.com/qtltools/qtltools 🙈

📚 CITATION 📚

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

👑 AUTHORS 👑

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

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okay bestie, that's the whole page 🫶 this is QTLtools-v1.3, last updated 06 May 2020, so go forth and be iconic 💅🦋✨