Ubuntu Manpage: QTLtools fenrich - Functional enrichment of molecular QTLs

Provided by: qtltools_1.3.1+dfsg-2build2_amd64

NAME

       QTLtools fenrich - Functional enrichment of molecular QTLs

SYNOPSIS

       QTLtools  fenrich  --qtl significanty_genes.bed --tss gene_tss.bed --bed TFs.encode.bed.gz
       --out output.txt [OPTIONS]

DESCRIPTION

This mode allows assessing whether a set of QTLs fall within some functional annotations
more often than what is expected by chance. The method is detailed in
<https://www.nature.com/articles/ncomms15452>. Here, we mean by chance is what is
expected given the non-uniform distributions of molQTLs and functional annotations around
the genomic positions of the molecular phenotypes. To do so, we first enumerate all the
functional annotations located nearby a given molecular phenotype. In practice, for X
phenotypes being quantified, we have X lists of annotations. And, for the subset Y of
those having a significant molQTL, we count how often the Y molQTLs overlap the
annotations in the corresponding lists: this gives the observed overlap frequency fobs(Y)
between molQTLs and functional annotations. Then, we permute the lists of functional
annotations across the phenotypes (e.g, phenotype A may be assigned the list of
annotations coming from phenotype B) and for each permuted data set, we count how often
the Y molQTLs do overlap the newly assigned functional annotations: this gives the
expected overlap frequency fexp(Y) between molQTLs and functional annotations. By doing
this permutation scheme, we keep the distribution of functional annotations and molQTLs
around molecular phenotypes unchanged. Now that we have the observed and expected overlap
frequencies, we use a fisher test to assess how fobs(Y) and fexp(Y) differ. This gives an
odd ratio estimate and a two-sided p-value which basically tells us first if there is and
enrichment or depletion, and second how significant this is.

OPTIONS

       --qtl in.bed
              List of QTLs of interest in BED format.  REQUIRED.

       --bed functional_annotation.bed.gz
              Functional annotations in BED format.  REQUIRED.

       --tss genes.bed
              List of positions of all phenotypes you mapped QTLs for, in BED format.  REQUIRED.

       --out output.txt
              Output file.  REQUIRED.

       --permute integer
              Number of permutation to run.  DEFAULT=1000

INPUT FILES

       --qtl file
        List of QTLs of interest.  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   +

        The column definitions are:

        1   The variant chromosome
        2   The variant's start position (0-based)
        3   The variant's end position (1-based)
        4   The variant ID

        5   The phenotype ID
        6   The phenotype's strand. (not used)

       --bed file
        List of annotations in BED format.  An example:

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

        The column definitions are:

        1   Chromosome
        2   Start position (0-based)
        3   End position (1-based)

       --tss file
        List of positions of all phenotypes you mapped QTLs for.  An example:

        1    29369     29370     ENSG00000227232.4   1_15211   -
        1    135894    135895    ENSG00000268903.1   1_985446  -
        1    137964    137965    ENSG00000269981.1   1_1118728 -
        1    317719    317720    ENSG00000237094.7   1_15211   +

        The column definitions are:

        1   Phenotype's chromosome
        2   The start position of the phenotype (0-based)
        3   The end position of the phenotype (1-based)
        4   The phenotype ID
        5   Top variant (not used)
        6   The phenotype's strand

OUTPUT FILE

       --out file
        Space separated results output file detailing the enrichment with the following columns:

        1   The observed number of QTLs falling within the functional annotations
        2   The total number of QTLs
        3   The mean expected number of QTLs falling within the  functional  annotations  (across
            multiple permutations)
        4   The  standard  deviation of the expected number of QTLs falling within the functional
            annotations (across multiple permutations)
        5   The empirical p-value
        6   Lower bound of the 95% confidence interval of the odds ratio
        7   The odds ratio
        8   Upper bound of the 95% confidence interval of the odds ratio

EXAMPLE

       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 Prepare a BED file containing the positions of all phenotypes you mapped QTLs for:

         zcat  results.genes.full.txt.gz | awk '{ print $2, $3-1, $4, $1, $8, $5 }' | tr ' ' '\t'
         | sort -k1,1V -k2,2g > results.genes.quantified.bed

       3 Run the enrichment analysis:

         QTLtools fenrich --qtl results.genes.significant.bed --tss  results.genes.quantified.bed
         --bed TFs.encode.bed.gz --out enrichment.QTL.in.TF.txt

BUGS

       o Please submit bugs to <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)