Provided by: qtltools_1.3.1+dfsg-4build4_amd64 
NAME
QTLtools - A complete tool set for molecular QTL discovery and analysis
SYNOPSIS
QTLtools [MODE] [OPTIONS]
DESCRIPTION
QTLtools is a complete tool set for molecular QTL discovery and analysis that is fast, user and cluster
friendly. QTLtools performs multiple key tasks such as checking the quality of the sequence data,
checking that sequence and genotype data match, quantifying and stratifying individuals using molecular
phenotypes, discovering proximal or distal molQTLs and integrating them with functional annotations or
GWAS data, and analyzing allele specific expression. It utilizes HTSlib <http://www.htslib.org/> to
quickly and efficiently handle common genomics files types like VCF, BCF, BAM, SAM, CRAM, BED, and GTF,
and the Eigen C++ library <http://eigen.tuxfamily.org/> for fast linear algebra.
MODES
bamstat QTLtools bamstat --bam [in.sam|in.bam|in.cram] --bed annotation.bed.gz --out output.txt
[OPTIONS]
Calculate basic QC metrics for BAM/SAM.
mbv QTLtools mbv --bam [in.sam|in.bam|in.cram] --vcf [in.vcf|in.vcf.gz|in.bcf] --out output.txt
[OPTIONS]
Match BAM to VCF
pca QTLtools pca --vcf [in.vcf|in.vcf.gz|in.bcf] | --bed in.bed.gz --out output.txt [OPTIONS]
Calculate principal components for a BED/VCF/BCF/CRAM file.
correct QTLtools correct --vcf [in.vcf|in.vcf.gz|in.bcf] | --bed in.bed.gz --cov covariates.txt |
--normal --out output.txt [OPTIONS]
Covariate correction of a BED or a VCF file.
cis QTLtools cis --vcf [in.vcf|in.vcf.gz|in.bcf|in.bed.gz] --bed quantifications.bed.gz
[--nominal float | --permute integer | --mapping in.txt] --out output.txt [OPTIONS]
cis QTL analysis.
trans QTLtools trans --vcf [in.vcf|in.vcf.gz|in.bcf|in.bed.gz] --bed quantifications.bed.gz
[--nominal | --permute | --sample integer | --adjust in.txt] --out output.txt [OPTIONS]
trans QTL analysis.
fenrich QTLtools fenrich --qtl significanty_genes.bed --tss gene_tss.bed --bed TFs.encode.bed.gz
--out output.txt [OPTIONS]
Functional enrichment for QTLs.
fdensity QTLtools fdensity --qtl significanty_genes.bed --bed TFs.encode.bed.gz --out output.txt
[OPTIONS]
Functional density around QTLs.
genrich QTLtools genrich --qtl significanty_genes.bed --tss gene_tss.bed --vcf 1000kg.vcf --gwas
gwas_hits.bed --out output.txt [OPTIONS]
GWAS enrichment for QTLs. This mode is deprecated and not supported, use rtc instead.
rtc QTLtools rtc --vcf [in.vcf|in.vcf.gz|in.bcf|in.bed.gz] --bed quantifications.bed.gz
--hotspots hotspots_b37_hg19.bed [--gwas-cis | --gwas-trans | --mergeQTL-cis | --mergeQTL-
trans] variants_external.txt qtls_in_this_dataset.txt --out output.txt [OPTIONS]
Regulatory Trait Concordance score analysis to test if two colocalizing variants are due to
the same functional effect.
rtc-union 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]
Find the union of QTLs from independent datasets. If there was a QTL in a given
recombination interval in one dataset, then find the best QTL (may or may not be genome-wide
significant) in the same recombination interval in all other datasets.
extract QTLtools extract [--vcf --bed --cov] relevant_file --out output_prefix [OPTIONS]
Data extraction mode. Extract all the data from the provided files into one flat file.
quan QTLtools quan --bam [in.sam|in.bam|in.cram] --gtf gene_annotation.gtf --out-prefix output
[OPTIONS]
Quantify gene and exon expression from RNAseq.
ase QTLtools ase --bam [in.sam|in.bam|in.cram] --vcf [in.vcf|in.vcf.gz|in.bcf] --ind
sample_name_in_vcf --mapq integer --out output.txt [OPTIONS]
Measure allele specific expression from RNAseq at transcribed heterozygous SNPs
rep QTLtools rep --bed quantifications.bed.gz --vcf [in.vcf|in.vcf.gz|in.bcf] --qtl
qtls_external.txt --out output.txt [OPTIONS]
Replicate QTL associations in an independent dataset
gwas QTLtools gwas --vcf [in.vcf|in.vcf.gz|in.bcf|in.bed.gz] --bed quantifications.bed.gz --out
output.txt [OPTIONS]
GWAS tests. Correlate all genotypes with all phenotypes.
GLOBAL OPTIONS
QTLtools can read gzip, bgzip, and bzip2 files, and can output gzip and bzip2 files. This is dependent
on the input and output files' extension. E.g --out output.txt.gz will write a gzipped file.
The following are common options that are used in all of the modes. Some of these will not apply to
certain modes.
--help Produces a description of options for a given mode.
--seed integer
Random seed for analyses that utilizes randomness. Useful for generating replicable results.
Default=15112011.
--log file
Dump screen output to this file.
--silent
Disable screen output.
--exclude-samples file
List of samples to exclude. One sample name per line.
--include-samples file
List of samples to include. One sample name per line.
--exclude-sites file
List of variants to exclude. One variant ID per line.
--include-sites file
List of variants to include. One variant ID per line.
--exclude-positions file
List of positions to exclude from genotypes. One chr position per line (separated by a space).
--include-positions file
List of positions to include from genotypes. One chr position per line (separated by a space).
--exclude-phenotypes file
List of phenotypes to exclude. One phenotype ID per line.
--include-phenotypes file
List of phenotypes to include. One phenotype ID per line.
--exclude-covariates file
List of covariates to exclude. One covariate name per line.
--include-covariates file
List of covariates to include. One covariate name per line.
FILE FORMATS
.bcf|.vcf|.vcf.gz
These files are used for genotype data. The official VCF specification is described at
<https://samtools.github.io/hts-specs/VCFv4.2.pdf>. The VCF/BCF files used with QTLtools must
satisfy this spec's requirements. BCF files must be indexed with bcftools index in.bcf
<http://samtools.github.io/bcftools/bcftools.html>. VCF files should be compressed by bgzip
<http://www.htslib.org/doc/bgzip.html> and indexed with tabix -p vcf in.vcf.gz
<http://www.htslib.org/doc/tabix.html>.
.bed|.bed.gz
These files are used for phenotype data, and in certain modes they can also be used with the --vcf
option, which can be used to correlate two molecular phenotypes. The format used for QTLtools is
a custom UCSC BED format <https://genome.ucsc.edu/FAQ/FAQformat.html#format1>, which has 6
annotation columns followed by sample columns. The header line must exist, and must begin with a
# and columns must be tab separated. THIS IS A DIFFERENT FILE FORMAT THAN THE ONE USED FOR
FASTQTL, THUS FASTQTL BED FILES ARE INCOMPATIBLE WITH QTLTOOLS. Phenotype BED files must be
compressed by bgzip <http://www.htslib.org/doc/bgzip.html> and indexed with tabix -p bed
in.bed.gz <http://www.htslib.org/doc/tabix.html>. Missing values must be coded as NA. Following
is an example BED file:
#chr start end pid gid strand sample1 sample2
1 9999 10000 exon1 gene1 + 15 234
1 9999 10000 exon2 gene1 + 11 134
1 19999 20000 exon1 gene2 - 154 284
1 19999 20000 exon2 gene2 - 112 301
BED file's annotation columns' descriptions:
1 Phenotype chromosome [string]
2 Start position of the phenotype [integer, 0-based]
3 End position of the phenotype [integer, 1-based]
4 Phenotype ID [string]
5 Phenotype group ID or any type of info about the phenotype [string]
6 Phenotype strand [+/-]
.bam|.sam|.cram
These files are used for sequence data. The official SAM specification is described at
<https://samtools.github.io/hts-specs/SAMv1.pdf>. The SAM/BAM/CRAM files used with QTLtools must
satisfy this spec's requirements. SAM/BAM/CRAM files must be indexed with samtools index in.bam
<http://www.htslib.org/doc/samtools.html>.
.gtf These files are used for gene annotation. The file specification is described at
<https://www.ensembl.org/info/website/upload/gff.html>. The GTF files used must comply with this
spec, and should have the gene_id, transcript_id, gene_name, gene_type, and trnascript_type
attributes. We recommend using gene annotations from GENCODE <https://www.gencodegenes.org/>.
covariate files
The covariate file contains the covariate data in simple text format. The missing values should
be encoded as NA. Both quantitative and qualitative covariates are supported. Quantitative
covariates are assumed when only numeric values are provided. Qualitative covariates are assumed
when only non-numeric values are provided. In practice, qualitative covariates with F factors are
converted in F-1 binary covariates. Following is an example a covariate file:
id sample1 sample2 sample3
PC1 -0.02 0.14 0.16
PC2 0.01 0.11 0.10
PC3 0.03 0.05 0.07
COV A B C
include/exclude files
The various --{include,exclude}-{sites,samples,phenotypes,covariates} options require a simple
text file which lists the IDs of the desired type, one ID per line. The include options will
result in running the analyses only in this subset of IDs, whereas exclude options will remove
these IDs from the analyses. The IDs for --{include,exclude}-sites refer to the 3rd column in
VCF/BCF files, --{include,exclude}-covariates refer to the 1st column in COV files,
--{include,exclude}-phenotyps refer to the 4th column in BED files and when --grp-best option is
used to the 5th column. The --include-positions and --exclude-positions options require a text
file which lists the chromosomes and positions (separated by a space) of genotypes to be excluded
or included. One position per line.
IMPORTANT NOTES
o BED files' start position is 0-based, whereas the end position is 1-based. Positions in all other
files used in QTLtools are 1-based. All positions provided as option arguments and filters, even the
ones referring to BED files, must be 1-based. 1-based means the first base of the sequence has the
position 1, whereas in 0-based the first position is 0.
o Make sure the chromosome names are the same across all files. If some files have e.g. chr1 and another
has 1 as a chromosome name then these will be considered different chromosomes.
o BED files used for FastQTL <http://fastqtl.sourceforge.net/> are not directly compatible with QTLtools.
To convert a FastQTL BED file to the format used in QTLtools you need to add 2 columns after the 4th
column.
o The quan mode in version 1.2 and above is not compatible with the quantifications generated by the
previous versions. This due to bug fixes and slight adjustments to the way we quantify. Do not mix
quantifications generated by earlier versions of QTLtools with quantifications from version 1.2 and
above, as this will create a bias in your dataset.
o Make sure you index all your genotype, phenotype, and sequence files.
o Use BCF and BAM files for the best performance.
EXAMPLE FILES
exons.50percent.chr22.bed.gz <http://jungle.unige.ch/QTLtools_examples/exons.50percent.chr22.bed.gz>
exons.50percent.chr22.bed.gz.tbi <http://jungle.unige.ch/QTLtools_examples/exons.50percent.chr22.bed.gz.tbi>
gencode.v19.annotation.chr22.gtf.gz <http://jungle.unige.ch/QTLtools_examples/gencode.v19.annotation.chr22.gtf.gz>
gencode.v19.exon.chr22.bed.gz <http://jungle.unige.ch/QTLtools_examples/gencode.v19.exon.chr22.bed.gz>
genes.50percent.chr22.bed.gz <http://jungle.unige.ch/QTLtools_examples/genes.50percent.chr22.bed.gz>
genes.50percent.chr22.bed.gz.tbi <http://jungle.unige.ch/QTLtools_examples/genes.50percent.chr22.bed.gz.tbi>
genes.covariates.pc50.txt.gz <http://jungle.unige.ch/QTLtools_examples/genes.covariates.pc50.txt.gz>
genes.simulated.chr22.bed.gz <http://jungle.unige.ch/QTLtools_examples/genes.simulated.chr22.bed.gz>
genes.simulated.chr22.bed.gz.tbi <http://jungle.unige.ch/QTLtools_examples/genes.simulated.chr22.bed.gz.tbi>
genotypes.chr22.vcf.gz <http://jungle.unige.ch/QTLtools_examples/genotypes.chr22.vcf.gz>
genotypes.chr22.vcf.gz.tbi <http://jungle.unige.ch/QTLtools_examples/genotypes.chr22.vcf.gz.tbi>
GWAS.b37.txt <http://jungle.unige.ch/QTLtools_examples/GWAS.b37.txt>
HG00381.chr22.bam <http://jungle.unige.ch/QTLtools_examples/HG00381.chr22.bam>
HG00381.chr22.bam.bai <http://jungle.unige.ch/QTLtools_examples/HG00381.chr22.bam.bai>
hotspots_b37_hg19.bed <http://jungle.unige.ch/QTLtools_examples/hotspots_b37_hg19.bed>
results.genes.full.txt.gz <http://jungle.unige.ch/QTLtools_examples/results.genes.full.txt.gz>
TFs.encode.bed.gz <http://jungle.unige.ch/QTLtools_examples/TFs.encode.bed.gz>
SEE ALSO
QTLtools-bamstat(1), QTLtools-mbv(1), QTLtools-pca(1), QTLtools-correct(1), QTLtools-cis(1), QTLtools-
trans(1), QTLtools-fenrich(1), QTLtools-fdensity(1), QTLtools-rtc(1), QTLtools-rtc-union(1), QTLtools-
extract(1), QTLtools-quan(1), QTLtools-ase(1), QTLtools-rep(1), QTLtools-gwas(1)
QTLtools website: <https://qtltools.github.io/qtltools>
BUGS
o 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. Affected modes: cis, correct, gwas, pca, rep,
trans, rtc-union
Please submit bugs to <https://github.com/qtltools/qtltools>
CITATIONS
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>
Ongen H, Brown A. A., 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>
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)
QTLtools-v1.3 06 May 2020 QTLtools(1)