Provided by: qtltools_1.3.1+dfsg-4_amd64 
NAME
QTLtools rtc-union - Find the union of QTLs from independent datasets
SYNOPSIS
QTLtools rtc-union --vcf [in.vcf|in.vcf.gz|in.bcf|in.bed.gz] ... --bed
quantifications.bed.gz ... --hotspots hotspots_b37_hg19.bed --results
qtl_results_files.txt ... [OPTIONS]
DESCRIPTION
This mode finds the best molQTL (may or may not be genome-wide significant) in each region
flanked by recombination hotspots (coldspot), if there was a molQTL in the same coldspot
in one dataset. First we map all the significant molQTLs in all of the datasets to
coldspots. Subsequently if certain datasets do not have a significant molQTL in a given
coldspot for a given phenotype, we then take the most significant variant associated with
that phenotype in that coldspot, for all the missing datasets.
OPTIONS
--vcf [in.vcf|in.bcf|in.vcf.gz|in.bed.gz] ...
Genotypes in VCF/BCF format, or another molecular phenotype in BED format. If
there is a DS field in the genotype FORMAT of a variant (dosage of the genotype
calculated from genotype probabilities, e.g. after imputation), then this is used
as the genotype. If there is only the GT field in the genotype FORMAT then this is
used and it is converted to a dosage. If a single file is provided then all
datasets are assumed to have the same genotypes, and all datasets' samples are all
included in this file. If multiple files are provided for each dataset, then all
--vcf, --bed, --cov, and --results files MUST be in the same order. E.g if the
first vcf file is from dataset1, then the first bed, cov, and results files must
also be from dataset1. REQUIRED.
--bed quantifications.bed.gz ...
Molecular phenotype quantifications in BED format for each of the datasets. All
--vcf, --bed, --cov, and --results files MUST be in the same order. E.g if the
first vcf file is from dataset1, then the first bed, cov, and results files must
also be from dataset1. REQUIRED.
--results significant_qtls.txt ...
Results file with the QTLs in each of the datasets. All --vcf, --bed, --cov, and
--results files MUST be in the same order. E.g if the first vcf file is from
dataset1, then the first bed, cov, and results files must also be from dataset1.
REQUIRED.
--hotspots recombination_hotspots.bed
Recombination hotspots in BED format. REQUIRED.
--out-suffix suffix
If provided output files will be suffixed with this.
--cov covariates.txt
Covariates to correct the phenotype data with for each of the datasets. All --vcf,
--bed, --cov, and --results files MUST be in the same order. E.g if the first vcf
file is from dataset1, then the first bed, cov, and results files must also be from
dataset1.
--force
If the output file exists, overwrite it.
--normal
Rank normal transform the phenotype data so that each phenotype is normally
distributed. RECOMMENDED.
--conditional
molQTLs contain independent signals so execute the conditional analysis.
--window integer
Size of the cis window flanking each phenotype's start position. DEFAULT=1000000.
RECOMMENDED=1000000.
--pheno-col integer
1-based phenotype id column number. DEFAULT=1
--geno-col integer
1-based genotype id column number. DEFAULT=8
--rank-col integer
1-based conditional analysis rank column number. Only relevant if --conditional is
in effect. DEFAULT=12
--best-col integer
1-based phenotype column number Only relevant if --conditional is in effect.
DEFAULT=21
--chunk integer1 integer2
For parallelization. Divide the data into integer2 number of chunks and process
chunk number integer1. Chunk 0 will print a header. Mutually exclusive with
--region. Minimum number of chunks has to be at least the same number of
chromosomes in the --bed file.
--region chr:start-end
Genomic region to be processed. E.g. chr4:12334456-16334456, or chr5. Mutually
exclusive with --chunk.
OUTPUT FILE
output file
Space separated output file with the following columns.
1 Column showing that this is a rtc-union result. Always __UNION__
2 The phenotype ID
3 The genotype ID. This can say __UNION_FILLER_MAX_INDEP__,
__UNION_FILLER_MISS_GENO__, or __UNION_FILLER_MISS_PHENO__ which are fillers for
missing cases in one of the datasets.
4 The rank of the best variant in this coldspot. If this was discovered in the rtc-
union run then this would be -1, and if there was already a significant variant in
this coldspot then a different value.
5 Dummy field indicating that this is the best hit per rank
6 The p-value of the association. Will be 0 if this was already significant in the
dataset
7 The coldspot ID
8 The coldspot region
EXAMPLE
o Find the union of 3 datasets, correcting for technical covariates, and rank normal
transforming the phenotypes with 20 jobs on a compute cluster (qsub needs to be changed
to the job submission system used [bsub, psub, etc...]):
for j in $(seq 1 20); do
echo "QTLtools rtc-union --bed dataset1.bed.gz dataset2.bed.gz dataset3.bed.gz
--vcf dataset1.bcf dataset2.bcf dataset3.bcf --cov dataset1.covariates.txt
dataset2.covariates.txt dataset3.covariates.txt --results dataset1.txt dataset2.txt
dataset3.txt --hotspots hotspots_b37_hg19.bed --normal --conditional --chunk $j 20
--out-suffix .chunk.$j.20.txt" | qsub
done
SEE ALSO
QTLtools(1)
QTLtools website: <https://qtltools.github.io/qtltools>
BUGS
Versions up to and including 1.2, suffer from a bug in reading missing genotypes in
VCF/BCF files. This bug affects variants with a DS field in their genotype's FORMAT and
have a missing genotype (DS field is .) in one of the samples, in which case genotypes for
all the samples are set to missing, effectively removing this variant from the analyses.
Please submit bugs to <https://github.com/qtltools/qtltools>
CITATION
Ongen H, Brown AA, Delaneau O, et al. Estimating the causal tissues for complex traits and
diseases. Nat Genet. 2017;49(12):1676-1683. doi:10.1038/ng.3981
<https://doi.org/10.1038/ng.3981>
AUTHORS
Halit Ongen (halitongen@gmail.com), Olivier Delaneau (olivier.delaneau@gmail.com)