Provided by: qtltools_1.3.1+dfsg-2build2_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)