---
title: "PureCN best practices"
author:
name: Markus Riester
affiliation: Novartis Institutes for BioMedical Research
output:
BiocStyle::html_document:
toc_float: true
BiocStyle::pdf_document: default
package: PureCN
abstract: |
This tutorial provides a quick overview of the command line tools shipping
with _PureCN_. These tools implement highly recommended best practices. For
the R package and more detailed information, see the main vignette.
vignette: |
%\VignetteIndexEntry{Best practices, quick start and command line usage}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r load-purecn, echo=FALSE, message=FALSE}
library(PureCN)
library(BiocStyle)
```
# Prerequisites
## Update from previous stable versions
`r Biocpkg("PureCN")` is backward compatible with input generated by
versions 1.16 and later. For versions 1.8 to 1.14, please re-run `NormalDB.R`
(see also below):
```
$ Rscript $PURECN/NormalDB.R --outdir $OUT_REF \
--coveragefiles example_normal_coverages.list \
--genome hg19 --normal_panel $NORMAL_PANEL --assay agilent_v6
```
For upgrades from version 1.6, we highly recommend starting from scratch
following this tutorial.
## Installation
For the command line scripts described in this tutorial, we will need to
install `r Biocpkg("PureCN")` with suggested dependencies:
```
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("PureCN", dependencies = TRUE)
```
Alternatively, manually install the packages required by the command line
scripts:
```
BiocManager::install(c("PureCN", "optparse",
"TxDb.Hsapiens.UCSC.hg19.knownGene", "org.Hs.eg.db"))
```
(Replace `hg19` with your genome version).
To use the alternative and in many cases recommended `r CRANpkg("PSCBS")`
segmentation:
```
# default PSCBS without support of interval weights
BiocManager::install("PSCBS")
# patched PSCBS with support of interval weights
BiocManager::install("lima1/PSCBS", ref="add_dnacopy_weighting")
```
To call mutational signatures, install the GitHub version of the
`r CRANpkg("deconstructSigs")` package:
```
BiocManager::install("raerose01/deconstructSigs")
```
For the experimental support of importing variant calls from
_GATK4 GenomicsDB_, follow the installations instructions from
[GenomicsDB-R](https://github.com/nalinigans/GenomicsDB-R).
The _GATK4_ segmentation requires the `gatk` binary in path. Versions 4.1.7.0
and newer are supported.
# Prepare environment and assay-specific reference files
- Start R and enter the following to get the path to the command line
scripts:
```{r path}
system.file("extdata", package="PureCN")
```
- Exit R and store this path in an environment variable, for example in
BASH:
```
$ export PURECN="/path/to/PureCN/extdata"
$ Rscript $PURECN/PureCN.R --help
Usage: /path/to/PureCN/inst/extdata/PureCN.R [options] ...
```
- Generate an interval file from a BED file containing baits coordinates (not
necessarily required with third-party segmentations, see in the corresponding
Section \@ref(run-purecn-with-third-party-segmentation)):
```
# specify path where PureCN should store reference files
$ export OUT_REF="reference_files"
$ Rscript $PURECN/IntervalFile.R --infile baits_hg19.bed \
--fasta hg19.fa --outfile $OUT_REF/baits_hg19_intervals.txt \
--offtarget --genome hg19 \
--export $OUT_REF/baits_optimized_hg19.bed \
--mappability wgEncodeCrgMapabilityAlign100mer.bigWig \
--reptiming wgEncodeUwRepliSeqK562WaveSignalRep1.bigWig
```
Internally, this script uses `r Biocpkg("rtracklayer")` to parse the
`infile`. Make sure that the file format matches the file extension.
See the `r Biocpkg("rtracklayer")` documentation for problems loading the file.
Check that the genome version of the baits file matches the reference. Do not
include chrM baits in case the capture kit includes some.
The `--offtarget` flag will include off-target reads. Including them is
recommended except for Amplicon data.
The `--genome` version is needed to annotate exons with gene symbols. Use
hg19/hg38 for human genomes, not b37/b38. You might get a warning that an
annotation package is missing. For hg19, install
`r Biocpkg("TxDb.Hsapiens.UCSC.hg19.knownGene")` in R.
The `--export` argument is optional. If provided, this script will store the
modified intervals as BED file for example (again every
`r Biocpkg("rtracklayer")` format is supported). This is useful when the coverages
are calculated with third-party tools like GATK.
The `--mappability` argument should provide a `r Biocpkg("rtracklayer")`
parsable file with a mappability score in the first meta data column. If
provided, off-target regions will be restricted to regions specified in this
file. On-target regions with low mappability will be excluded. For hg19,
download the file from the UCSC website. Choose the kmer size that best fits
your average mapped read length. For hg38, download recommended 76-kmer or
100-kmer mappability files through the courtesy of the Waldron lab from:
- [GCA_000001405.15_GRCh38_no_alt_analysis\_set_76.bw](https://s3.amazonaws.com/purecn/GCA_000001405.15_GRCh38_no_alt_analysis\_set_76.bw)
- [GCA_000001405.15_GRCh38_no_alt_analysis_set_100.bw](https://s3.amazonaws.com/purecn/GCA_000001405.15_GRCh38_no_alt_analysis_set_100.bw)
See the FAQ section of the main vignette for instruction how to generate such a
file for other references.
Similarly, the `--reptiming` argument takes a replication timing score in the
same format. If provided, GC-normalized and log-transformed coverage is tested
for a linear relationship with this score and normalized accordingly. This is
optional and provides only a minor benefit for coverage normalization, but can
identify samples with high proliferation. Requires `--offtarget` to be useful.
# Create VCF files
`r Biocpkg("PureCN")` does not ship with a variant caller. Use a third-party
tool to generate a VCF for each sample.
Important recommendations:
- Use _MuTect 1.1.7_ if possible; _Mutect 2_ from _GATK 4.1.7+_ is now out of
alpha (earlier _Mutect 2_ versions are not supported and will not work).
- VCFs from most other tumor-only callers such as _VarScan2_ and
_FreeBayes_ are supported, but only very limited artifact filtering will be
performed for these callers. Make sure to provide filtered VCFs. See the FAQ
section in the main vignette for common problems and questions related to
input data.
- Since germline SNPs are needed to infer allele-specific copy numbers, the
provided VCF needs to contain both somatic and germline variants. Make sure
that upstream filtering does not remove high quality SNPs, in particular due
to presence in germline databases. _Mutect 1.1.7_ automatically calls SNPs,
but _Mutect 2_ does not. Make sure to run _Mutect 2_ with
`--genotype-germline-sites true --genotype-pon-sites true`. You will not get
usuable output without those flags.
- Run the variant caller with a 50-75 base pair interval padding to increase the
number of heterozygous SNPs
# Run PureCN with internal segmentation
The following describes `r Biocpkg("PureCN")` runs with internal copy number
normalization and segmentation.
What you will need:
- The interval file generated above
- BAM files of tumor samples.
- BAM files of normal samples (see main vignette for recommendations). These
normal samples are not required to be patient-matched to the tumor samples,
but they need to be processed-matched (same assay run through the same
alignment pipeline, ideally sequenced in the same lab)
- VCF files generated above for all tumor and normal BAM files
## Coverage
For each sample, tumor and normal, calculate GC-normalized coverages:
```
# Calculate and GC-normalize coverage from a BAM file
$ Rscript $PURECN/Coverage.R --outdir $OUT/$SAMPLEID \
--bam ${SAMPLEID}.bam \
--intervals $OUT_REF/baits_hg19_intervals.txt
```
Similar to GATK, this script also takes a text file containing a list of BAM or
coverage file names (one per line). The file extension must be `.list`:
```
# Calculate and GC-normalize coverage from a list of BAM files
$ Rscript $PURECN/Coverage.R --outdir $OUT/normals \
--bam normals.list \
--intervals $OUT_REF/baits_hg19_intervals.txt \
--cores 4
```
Important recommendations:
- Only provide `--keepduplicates` or `--removemapq0` if you know what you are
doing and always use the same command line arguments for tumor and the
normals
- It can be safe to skip the GC-normalization with `--skipgcnorm` when tumor
and normal samples are expected to exhibit similar biases and a sufficient
number of normal samples is available. A good example would be plasma
sequencing. In contrast, old FFPE samples normalized against blood controls
will more likely benefit from GC-normalization.
- A potential negative impact of GC-normalization is much more
likely in very small targeted panels (< 0.5Mb) and worth benchmarking.
- When supported third-party tools are used to calculate coverage (currently
_CNVkit_, _GATK3_ and _GATK4_), it is possible to GC-normalize those
coverages with a matching interval file:
```
# GC-normalize coverage from a GATK DepthOfCoverage file
Rscript $PURECN/Coverage.R --outdir $OUT/$SAMPLEID \
--coverage ${SAMPLEID}.coverage.sample_interval_summary \
--intervals $OUT_REF/baits_hg19_intervals.txt
```
## NormalDB
To build a normal database for coverage normalization, copy the paths to all
(GC-normalized) normal coverage files in a single text file, line-by-line:
```
ls -a $OUT/normals/*_loess.txt.gz | cat > example_normal_coverages.list
# In case no GC-normalization is performed:
# ls -a $OUT/normals/*_coverage.txt.gz | cat > example_normal_coverages.list
$ Rscript $PURECN/NormalDB.R --outdir $OUT_REF \
--coveragefiles example_normal_coverages.list \
--genome hg19 --assay agilent_v6
# When normal panel VCF is available (highly recommended for
# unmatched samples)
$ Rscript $PURECN/NormalDB.R --outdir $OUT_REF \
--coveragefiles example_normal_coverages.list \
--normal_panel $NORMAL_PANEL \
--genome hg19 \
--assay agilent_v6
# For a Mutect2/GATK4 normal panel GenomicsDB (beta)
$ Rscript $PURECN/NormalDB.R --outdir $OUT_REF \
--coveragefiles example_normal_coverages.list \
--normal_panel $GENOMICSDB-WORKSPACE-PATH/pon_db \
--genome hg19 \
--assay agilent_v6
```
Important recommendations:
- Consider generating different databases when differences are significant, e.g.
for samples with different read lengths or insert size distributions
- In particular, do not mix normal data obtained with different capture kits
(e.g. _Agilent SureSelect v4_ and _v6_)
- Provide a normal panel VCF here to precompute mapping bias for faster
runtimes. The only requirement for the VCF is an `AD` format field containing
the number of reference and alt reads for all samples. See the example file
`$PURECN/normalpanel.vcf.gz`.
- For ideal results, examine the `interval_weights.png` file to find good
off-target bin widths. You will need to re-run `IntervalFile.R` with the
`--offtargetwidth` parameter and re-calculate the coverages. `NormalDB.R`
will also give a suggestion for a good minimum width. We do not recommend
going lower than this estimate; setting `--offtargetwidth` to value larger
than this value can decrease noise at the cost of loss in resolution.
Setting it to 1.2-1.5x the minimum recommendation (that should be ideally <
250kb) is a good starting point.
- The `--assay` argument is optional and is only used to add the provided assay
name to all output files
- A warning pointing to the likely use of a wrong baits file means that more
than 5% of targets have close to 0 coverage in all normal samples. A BED file
with the low coverage targets will be generated in `--outdir`. If for any
reason there is no access to the correct file, it is recommended to re-run the
`IntervalFile.R` command and provide this BED file with `--exclude`.
## PureCN
Now that the assay-specific files are created and all coverages calculated, we
run `r Biocpkg("PureCN")` to normalize, segment and determine purity and ploidy:
```
mkdir $OUT/$SAMPLEID
# Without a matched normal (minimal test run)
$ Rscript $PURECN/PureCN.R --out $OUT/$SAMPLEID \
--tumor $OUT/$SAMPLEID/${SAMPLEID}_coverage_loess.txt.gz \
--sampleid $SAMPLEID \
--vcf ${SAMPLEID}_mutect.vcf \
--normaldb $OUT_REF/normalDB_hg19.rds \
--intervals $OUT_REF/baits_hg19_intervals.txt \
--genome hg19
# Production pipeline run
$ Rscript $PURECN/PureCN.R --out $OUT/$SAMPLEID \
--tumor $OUT/$SAMPLEID/${SAMPLEID}_coverage_loess.txt.gz \
--sampleid $SAMPLEID \
--vcf ${SAMPLEID}_mutect.vcf \
--statsfile ${SAMPLEID}_mutect_stats.txt \
--funsegmentation PSCBS \
--normaldb $OUT_REF/normalDB_hg19.rds \
--mappingbiasfile $OUT_REF/mapping_bias_hg19.rds \
--intervals $OUT_REF/baits_hg19_intervals.txt \
--snpblacklist hg19_simpleRepeats.bed \
--genome hg19 \
--force --postoptimize --seed 123
# With a matched normal (test run; for production pipelines we recommend the
# unmatched workflow described above)
$ Rscript $PURECN/PureCN.R --out $OUT/$SAMPLEID \
--tumor $OUT/$SAMPLEID/${SAMPLEID}_coverage_loess.txt.gz \
--normal $OUT/$SAMPLEID/${SAMPLEID_NORMAL}_coverage_loess.txt.gz \
--sampleid $SAMPLEID \
--vcf ${SAMPLEID}_mutect.vcf \
--normaldb $OUT_REF/normalDB_hg19.rds \
--intervals $OUT_REF/baits_hg19_intervals.txt \
--genome hg19
# Recreate output after manual curation of ${SAMPLEID}.csv
$ Rscript $PURECN/PureCN.R --rds $OUT/$SAMPLEID/${SAMPLEID}.rds
```
Important recommendations:
- Even if matched normals are available, it is often better to use the normal
database for coverage normalization. **When a matched normal coverage is
provided with `--normal` then the pool of normal coverage normalization and
denoising steps are skipped!**
- Always provide the normal coverage database to ignore low quality regions in
the segmentation and to increase the sensitivity for homozygous deletions in
high purity samples.
- Double check that in `--tumor` and `--normaldb`, GC-normalization is either
used in both (`*_loess.txt.gz`) or skipped in both (`*_coverage.txt.gz`).
- The normal panel VCF file is useful for mapping bias correction and especially
recommended without matched normals. See the FAQ of the main vignette how to
generate this file. It is not essential for test runs.
- The _MuTect 1.1.7_ stats file (the main output file besides the VCF) should be
provided for better artifact filtering. If the VCF was generated by a pipeline
that performs good artifact filtering, this file is not needed. Do NOT
provide this file for _Mutect 2_.
- The `--postoptimize` flag defines that purity should be optimized using both
variant allelic fractions and copy number instead of copy number only. This
results in a significant runtime increase for whole-exome data.
- If `--out` is a directory, it will use the sample id as file prefix for all
output files. Otherwise `r Biocpkg("PureCN")` will use `--out` as prefix.
- The `--parallel` flag will enable the parallel fitting of local optima. See
`r Biocpkg("BiocParallel")` for details. This script will use the default
backend.
- `--funsegmentation PSCBS` is the new recommendation in 1.22. Support for
interval weights currently requires a patch (see Section
\@ref(installation)). See below for some more details on the best choice of
the method.
- `--model betabin` is the new recommendation in 1.22 with larger panel of
normals (more than 10-15 normal samples). We encourage users to try this
model and appreciate feedback.
- Defaults are well calibrated and should produce close to ideal results for
most samples. A few common cases where changing defaults makes sense:
- High purity and high quality: For cancer types with a high expected
purity, such as ovarian cancer, AND when quality is expected to be very
good (high coverage, young samples), `--maxcopynumber 8`.
(`r Biocpkg("PureCN")` reports copy numbers greater than this value, but
will stop fitting SNP allelic fractions to the exact allele-specific copy
number because this will get impossible very quickly with high copy
numbers - and computationally expensive.)
- Small panels with high coverage: `--padding 100` (or higher), requires
running the variant caller with this padding or without interval file. Use
the same settings for the panel of normals VCF so that SNPs in the
flanking regions have reliable mapping bias estimates. The
`--maxhomozygousloss` parameter might also need some adjustment for very
small panels with large gaps around captured deletions.
- Cell lines: Safely skip the search for low purity solutions in cell lines:
`--maxcopynumber 8`, `--minpurity 0.9`, `--maxpurity 0.99`. Add
`--modelhomozygous` to find regions of LOH in samples without normal
contamination (do not provide this flag when matched normal data are
available in the VCF).
- cfDNA: `--minpurity 0.1`, `--minaf 0.01` (or lower) and `--error 0.0005`
(or lower, when there is UMI-based error correction). Note that the
estimated purity can be very wrong when the true purity is below 5-7%;
these samples are usually flagged as non-aberrant.
- All assays: `--maxsegments` should set to a value so that with few
exceptions only poor quality samples exceed this cutoff. For cancer types
with high heterogenity, it is also recommended to increase
`--maxnonclonal` to 0.3-0.4 (this will increase the runtime significantly
for whole-exome data).
- The choice of the segmentation function can also make a significant
difference and unfortunately there is not yet a universal method that works
best in all scenarios.
- PSCBS: A good and safe starting point, especially with off-target
regions that might exhibit different noise profiles compared to
on-target.
- GATK4: Most recent addition. Not yet well tested in
`r Biocpkg("PureCN")`, but theoretically best choice with a larger
number of SNPs per intervals, for example assays with copy number
backbones. We appreciate feedback.
- CBS: Simple, fast and well tested. Does not support SNP information,
so only recommended for settings with a very small SNPs/intervals
ratio, for example small targeted panels (<1Mb) with healthy off-target
coverage (<150kb resolution and similar log ratio noise compared to
on-target).
- copynumber: For cases with multiple time points or biopsies. This is
automatically chosen with `--additionaltumors` and currently not
supported in a single-sample analysis.
- Hclust/none: For third-party segmentations. `Hclust` clusters segments
in an attempt to calibrate log-ratios across chromosomes, `none`
largely keeps everything as provided.
- A few recommendations for checks whether the `r Biocpkg("PureCN")` setup is
correct:
- The "Mean standard deviation of log-ratios" reported in the log file
should be fairly low for high quality data. Older FFPE data can be around
0.4, but high coverage, relatively recent samples should approach the
0.15 minimum. If off-target is consistently noisier than on-target, it is
probably worth increasing the off-target bin size and start from scratch
(or in case of whole-exome sequencing, ignore off-target reads since they
do not provide much additional information when bins are large and/or
noisy).
- The fraction of targets with SNPs should be between 10 and 15 percent.
If it is significantly lower, make sure that the variant caller was used
with 50-100bp interval padding or no interval file at all. Also check
that the interval file was generated using the baits coordinates, not the
targets (the baits BED file should have a more even size distribution,
e.g. 120bp and multiples of it).
- Read all warnings.
# Run PureCN with third-party segmentation
Our internal `r Biocpkg("PureCN")` normalization combined with the _PSCBS_ or
_GATK4_ segmentation should produce highly competitive results and we encourage
users to try it and compare it to their existing pipelines. However, we realize
that often it is not an option to change tools in production pipelines and we
therefore made it relatively easy to use `r Biocpkg("PureCN")` with third-party
tools. We provide examples for _CNVkit_ and _GATK4_ and it should be
straightforward to adapt those for other tools.
What you will need:
- Output of third-party tools (see details below)
- VCF files for all tumor samples and some normal files (see main vignette for
questions related to required normal samples)
## General usage
If you already have a segmentation from third-party tools (for example _CNVkit_,
_GATK4_, _EXCAVATOR2_). For a minimal test run:
```
Rscript $PURECN/PureCN.R --out $OUT/$SAMPLEID \
--sampleid $SAMPLEID \
--segfile $OUT/$SAMPLEID/${SAMPLEID}.cnvkit.seg \
--vcf ${SAMPLEID}_mutect.vcf \
--intervals $OUT_REF/baits_hg19_intervals.txt \
--genome hg19
```
See the main vignette for more details and file formats.
## Recommended _CNVkit_ usage
For a production pipeline run we provide again more information about the assay
and genome. Here an _CNVkit_ example:
```
# Recommended: Provide a normal panel VCF to remove mapping biases, pre-compute
# position-specific bias for much faster runtimes with large panels
# This needs to be done only once for each assay
Rscript $PURECN/NormalDB.R --outdir $OUT_REF --normal_panel $NORMAL_PANEL \
--assay agilent_v6 --genome hg19 --force
# Export the segmentation in DNAcopy format
cnvkit.py export seg $OUT/$SAMPLEID/${SAMPLEID}_cnvkit.cns --enumerate-chroms \
-o $OUT/$SAMPLEID/${SAMPLEID}_cnvkit.seg
# Run PureCN by providing the *.cnr and *.seg files
Rscript $PURECN/PureCN.R --out $OUT/$SAMPLEID \
--sampleid $SAMPLEID \
--tumor $OUT/$SAMPLEID/${SAMPLEID}_cnvkit.cnr \
--segfile $OUT/$SAMPLEID/${SAMPLEID}_cnvkit.seg \
--mappingbiasfile $OUT_REF/mapping_bias_agilent_v6_hg19.rds \
--vcf ${SAMPLEID}_mutect.vcf \
--statsfile ${SAMPLEID}_mutect_stats.txt \
--snpblacklist hg19_simpleRepeats.bed \
--genome hg19 \
--funsegmentation Hclust \
--force --postoptimize --seed 123
```
Important recommendations:
- The `--funsegmentation` argument controls if the data should to be
re-segmented using germline BAFs (default). Set this value to `none` if the
provided segmentation should be used as is. The recommended `Hclust` will
only cluster provided segments.
- Since _CNVkit_ provides all necessary information in the `*.cnr` output files,
the `--intervals` argument is not required.
- In test runs, especially when the input VCF contains matched normal
information, `--mappingbiasfile` can be skipped
- _CNVkit_ runs without normal reference samples are not recommended
- The `--statsfile` is only supported for _Mutect 1.1.7_. _Mutect 2_ provides
the filter flags directly in the VCF.
## Recommended _GATK4_ usage
```
# Recommended: Provide a normal panel GenomicsDB to remove mapping
# biases, pre-compute position-specific bias for much faster runtimes
# with large panels. This needs to be done only once for each assay.
Rscript $PURECN/NormalDB.R --outdir $OUT_REF \
--normal_panel $GENOMICSDB-WORKSPACE-PATH/pon_db \
--assay agilent_v6 --genome hg19 --force
Rscript $PURECN/PureCN.R --out $OUT/$SAMPLEID \
--sampleid $SAMPLEID \
--tumor $OUT/$SAMPLEID/${SAMPLEID}.hdf5 \
--logratiofile $OUT/$SAMPLEID/${SAMPLEID}.denoisedCR.tsv \
--segfile $OUT/$SAMPLEID/${SAMPLEID}.modelFinal.seg \
--mappingbiasfile $OUT_REF/mapping_bias_agilent_v6_hg19.rds \
--vcf ${SAMPLEID}_mutect2_filtered.vcf \
--snpblacklist hg19_simpleRepeats.bed \
--genome hg19 \
--funsegmentation Hclust \
--force --postoptimize --seed 123
```
Important recommendations:
- The `--funsegmentation` can be set to none in most cases. This will keep the
segmentation largely as provided. `Hclust` clusters segments to avoid
over-segmentation and to calibrate log-ratios across chromosomes. This will
thus alter the GATK4 segmentation, which might not be desired.
- Beta support for providing _CollectAllelicCounts_ output instead of _Mutect_
is available. Use `--vcf ${SAMPLEID}.allelicCounts.tsv` to automatically
import the SNP counts and convert them into a supported VCF. Note that this
will not use any somatic SNV and indel information available in _Mutect_ VCFs
and thus will also not provide any clonality annotation.
# Biomarkers
`Dx.R` provides copy number and mutation metrics commonly used as biomarkers,
most importantly tumor mutational burden (TMB), chromosomal instability (CIN)
and mutational signatures.
```
# Provide a BED file with callable regions, for examples obtained by
# GATK CallableLoci. Useful to calculate mutations per megabase and
# to exclude low quality regions.
grep CALLABLE ${SAMPLEID}_callable_status.bed > \
${SAMPLEID}_callable_status_filtered.bed
# Only count mutations in callable regions, also subtract what was
# ignored in PureCN.R via --snpblacklist, like simple repeats, from the
# mutation per megabase calculation
# Also search for the COSMIC mutation signatures
# (http://cancer.sanger.ac.uk/cosmic/signatures)
Rscript $PureCN/Dx.R --out $OUT/$SAMPLEID/$SAMPLEID \
--rds $OUT/SAMPLEID/${SAMPLEID}.rds \
--callable ${SAMPLEID}_callable_status_filtered.bed \
--exclude hg19_simpleRepeats.bed \
--signatures
# Restrict mutation burden calculation to coding sequences
Rscript $PureCN/FilterCallableLoci.R --genome hg19 \
--infile ${SAMPLEID}_callable_status_filtered.bed \
--outfile ${SAMPLEID}_callable_status_filtered_cds.bed \
--exclude '^HLA'
Rscript $PureCN/Dx.R --out $OUT/$SAMPLEID/${SAMPLEID}_cds \
--rds $OUT/SAMPLEID/${SAMPLEID}.rds \
--callable ${SAMPLEID}_callable_status_filtered_cds.bed \
--exclude hg19_simpleRepeats.bed
```
Important recommendations:
- Run _GATK CallableLoci_ with `--minDepth N` where N is roughly 20% of the mean
target coverage of all samples.
# Reference
Argument name | Corresponding PureCN argument | PureCN function
-----------------------|-------------------------------|----------------
`--fasta` | `reference.file` | `preprocessIntervals`
`--infile` | `interval.file` | `preprocessIntervals`
`--offtarget` | `off.target` | `preprocessIntervals`
`--targetwidth` | `average.target.width` | `preprocessIntervals`
`--mintargetwidth` | `min.target.width` | `preprocessIntervals`
`--smalltargets` | `small.targets` | `preprocessIntervals`
`--offtargetwidth` | `average.off.target.width` | `preprocessIntervals`
`--offtargetseqlevels` | `off.target.seqlevels` | `preprocessIntervals`
`--mappability` | `mappability` | `preprocessIntervals`
`--minmappability` | `min.mappability` | `preprocessIntervals`
`--reptiming` | `reptiming` | `preprocessIntervals`
`--reptimingwidth` | `average.reptiming.width` | `preprocessIntervals`
`--genome` | `txdb`, `org` | `annotateTargets`
`--outfile` | |
`--export` | | `rtracklayer::export`
`--version -v` | |
`--force -f` | |
`--help -h` | |
: (\#tab:intervalfile) IntervalFile
Argument name | Corresponding PureCN argument | PureCN function
-------------------|-------------------------------|----------------
`--bam` | `bam.file` | `calculateBamCoverageByInterval`
`--bai` | `index.file` | `calculateBamCoverageByInterval`
`--coverage` | `coverage.file` | `correctCoverageBias`
`--intervals` | `interval.file` | `correctCoverageBias`
`--method` | `method` | `correctCoverageBias`
`--keepduplicates` | `keep.duplicates` | `calculateBamCoverageByInterval`
`--removemapq0` | `mapqFilter` | `ScanBamParam`
`--skipgcnorm` | | `correctCoverageBias`
`--outdir` | |
`--cores` | | Number of CPUs to use when multiple BAMs are provided
`--parallel` | | Use default `r Biocpkg("BiocParallel")` backend when multiple BAMs are provided
`--seed` | |
`--version -v` | |
`--force -f` | |
`--help -h` | |
: (\#tab:coverage) Coverage
Argument name | Corresponding PureCN argument | PureCN function
-----------------------|-------------------------------|----------------
`--coveragefiles` | `normal.coverage.files` | `createNormalDatabase`
`--normal_panel` | `normal.panel.vcf.file` | `calculateMappingBiasVcf`
`--assay -a` | Optional assay name | Used in output file names.
`--genome -g` | Optional genome version | Used in output file names.
`--genomicsdb_af_field` | For GenomicsDB import, allelic fraction field | `calculateMappingBiasGatk4`
`--outdir -o` | |
`--version -v` | |
`--force -f` | |
`--help -h` | |
: (\#tab:normaldb) NormalDB
Argument name | Corresponding PureCN argument | PureCN function
-----------------------|-------------------------------|----------------
`--sampleid -i` | `sampleid` | `runAbsoluteCN`
`--normal` | `normal.coverage.file` | `runAbsoluteCN`
`--tumor` | `tumor.coverage.file` | `runAbsoluteCN`
`--vcf` | `vcf.file` | `runAbsoluteCN`
`--rds` | `file.rds` | `readCurationFile`
`--mappingbiasfile` | `mapping.bias.file` | `setMappingBiasVcf`
`--normaldb` | `normalDB` (serialized with `saveRDS`) | `calculateTangentNormal`, `filterTargets`
`--segfile` | `seg.file` | `runAbsoluteCN`
`--logratiofile` | `log.ratio` | `runAbsoluteCN`
`--additionaltumors` | `tumor.coverage.files` | `processMultipleSamples`
`--sex` | `sex` | `runAbsoluteCN`
`--genome` | `genome` | `runAbsoluteCN`
`--intervals` | `interval.file` | `runAbsoluteCN`
`--statsfile` | `stats.file` | `filterVcfMuTect`
`--minaf` | `af.range` | `filterVcfBasic`
`--snpblacklist` | `snp.blacklist` | `filterVcfBasic`
`--error` | `error` | `runAbsoluteCN`
`--dbinfoflag` | `DB.info.flag` | `runAbsoluteCN`
`--popafinfofield` | `POPAF.info.field` | `runAbsoluteCN`
`--mincosmiccnt` | `min.cosmic.cnt` | `setPriorVcf`
`--padding` | `interval.padding` | `filterVcfBasic`
`--mintotalcounts` | `min.total.counts` | `filterIntervals`
`--funsegmentation` | `fun.segmentation` | `runAbsoluteCN`
`--alpha` | `alpha` | `segmentationCBS`
`--undosd` | `undo.SD` | `segmentationCBS`
`--changepointspenalty`| `changepoints.penalty` | `segmentationGATK4`
`--additionalcmdargs`| `additional.cmd.args` | `segmentationGATK4`
`--maxsegments` | `max.segments` | `runAbsoluteCN`
`--minpurity` | `test.purity` | `runAbsoluteCN`
`--maxpurity` | `test.purity` | `runAbsoluteCN`
`--minploidy` | `min.ploidy` | `runAbsoluteCN`
`--maxploidy` | `max.ploidy` | `runAbsoluteCN`
`--maxcopynumber` | `test.num.copy` | `runAbsoluteCN`
`--postoptimize` | `post.optimize` | `runAbsoluteCN`
`--bootstrapn` | `n` | `bootstrapResults`
`--modelhomozygous` | `model.homozygous` | `runAbsoluteCN`
`--model` | `model` | `runAbsoluteCN`
`--logratiocalibration` | `log.ratio.calibration` | `runAbsoluteCN`
`--maxnonclonal` | `max.non.clonal` | `runAbsoluteCN`
`--maxhomozygousloss` | `max.homozygous.loss` | `runAbsoluteCN`
`--outvcf` | `return.vcf` | `predictSomatic`
`--out -o` | |
`--parallel` | `BPPARAM` | `runAbsoluteCN`
`--cores` | `BPPARAM` | `runAbsoluteCN`
`--seed` | |
`--version -v` | |
`--force -f` | |
`--help -h` | |
: (\#tab:purecn) PureCN
Argument name | Corresponding PureCN argument | PureCN function
----------------|-------------------------------|----------------
`--rds` | `file.rds` | `readCurationFile`
`--callable` | `callable` | `callMutationBurden`
`--exclude` | `exclude` | `callMutationBurden`
`--maxpriorsomatic` | `max.prior.somatic` | `callMutationBurden`
`--signatures` | | `deconstructSigs::whichSignatures`
`--signature_databases` | | `deconstructSigs::whichSignatures`
`--out` | |
`--version -v` | |
`--force -f` | |
`--help -h` | |
: (\#tab:dx) Dx