samplot is a command line tool for rapid, multi-sample structural variant
visualization. samplot takes SV coordinates and bam files and produces
high-quality images that highlight any alignment and depth signals that
substantiate the SV.
If you use samplot, please cite https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02380-5
Usage
samplot plot
usage: samplot plot [-h] [-n TITLES [TITLES ...]] [-r REFERENCE] [-z Z] -b
BAMS [BAMS ...] [-o OUTPUT_FILE] [--output_dir OUTPUT_DIR]
-s START -e END -c CHROM [-w WINDOW] [-d MAX_DEPTH]
[-t SV_TYPE] [-T TRANSCRIPT_FILE]
[--transcript_filename TRANSCRIPT_FILENAME]
[--max_coverage_points MAX_COVERAGE_POINTS]
[-A ANNOTATION_FILES [ANNOTATION_FILES ...]]
[--annotation_filenames ANNOTATION_FILENAMES [ANNOTATION_FILENAMES ...]]
[--coverage_tracktype {stack,superimpose,none}] [-a]
[-H PLOT_HEIGHT] [-W PLOT_WIDTH] [-q INCLUDE_MQUAL]
[--separate_mqual SEPARATE_MQUAL] [-j]
[--start_ci START_CI] [--end_ci END_CI]
[--long_read LONG_READ] [--ignore_hp]
[--min_event_size MIN_EVENT_SIZE]
[--xaxis_label_fontsize XAXIS_LABEL_FONTSIZE]
[--yaxis_label_fontsize YAXIS_LABEL_FONTSIZE]
[--legend_fontsize LEGEND_FONTSIZE]
[--annotation_fontsize ANNOTATION_FONTSIZE]
[--hide_annotation_labels] [--coverage_only]
[--max_coverage MAX_COVERAGE] [--same_yaxis_scales]
[--marker_size MARKER_SIZE] [--jitter [JITTER]]
[--dpi DPI] [--annotation_scalar ANNOTATION_SCALAR]
[--zoom ZOOM] [--debug DEBUG]
options:
-h, --help show this help message and exit
-n TITLES [TITLES ...], --titles TITLES [TITLES ...]
Space-delimited list of plot titles. Use quote marks
to include spaces (i.e. "plot 1" "plot 2")
-r REFERENCE, --reference REFERENCE
Reference file for CRAM, required if CRAM files used
-z Z, --z Z Number of stdevs from the mean (default 4)
-b BAMS [BAMS ...], --bams BAMS [BAMS ...]
Space-delimited list of BAM/CRAM file names
-o OUTPUT_FILE, --output_file OUTPUT_FILE
Output file name/type. Defaults to
{type}_{chrom}_{start}_{end}.png
--output_dir OUTPUT_DIR
Output directory name. Defaults to working dir.
Ignored if --output_file is set
-s START, --start START
Start position of region/variant (add multiple for
translocation/BND events)
-e END, --end END End position of region/variant (add multiple for
translocation/BND events)
-c CHROM, --chrom CHROM
Chromosome (add multiple for translocation/BND events)
-w WINDOW, --window WINDOW
Window size (count of bases to include in view),
default(0.5 * len)
-d MAX_DEPTH, --max_depth MAX_DEPTH
Max number of normal pairs to plot
-t SV_TYPE, --sv_type SV_TYPE
SV type. If omitted, plot is created without variant
bar
-T TRANSCRIPT_FILE, --transcript_file TRANSCRIPT_FILE
GFF3 of transcripts
--transcript_filename TRANSCRIPT_FILENAME
Name for transcript track
--max_coverage_points MAX_COVERAGE_POINTS
number of points to plot in coverage axis (downsampled
from region size for speed)
-A ANNOTATION_FILES [ANNOTATION_FILES ...], --annotation_files ANNOTATION_FILES [ANNOTATION_FILES ...]
Space-delimited list of bed.gz tabixed files of
annotations (such as repeats, mappability, etc.)
--annotation_filenames ANNOTATION_FILENAMES [ANNOTATION_FILENAMES ...]
Space-delimited list of names for the tracks in
--annotation_files
--coverage_tracktype {stack,superimpose,none}
type of track to use for low MAPQ coverage plot.
-a, --print_args Print commandline arguments to a json file, useful
with PlotCritic
-H PLOT_HEIGHT, --plot_height PLOT_HEIGHT
Plot height
-W PLOT_WIDTH, --plot_width PLOT_WIDTH
Plot width
-q INCLUDE_MQUAL, --include_mqual INCLUDE_MQUAL
Min mapping quality of reads to be included in plot
(default 1)
--separate_mqual SEPARATE_MQUAL
coverage from reads with MAPQ <= separate_mqual
plotted in lighter grey. To disable, pass in negative
value
-j, --json_only Create only the json file, not the image plot
--start_ci START_CI confidence intervals of SV first breakpoint (distance
from the breakpoint). Must be a comma-separated pair
of ints (i.e. 20,40)
--end_ci END_CI confidence intervals of SV end breakpoint (distance
from the breakpoint). Must be a comma-separated pair
of ints (i.e. 20,40)
--long_read LONG_READ
Min length of a read to be treated as a long-read
(default 1000)
--ignore_hp Choose to ignore HP tag in alignment files
--min_event_size MIN_EVENT_SIZE
Min size of an event in long-read CIGAR to include
(default 20)
--xaxis_label_fontsize XAXIS_LABEL_FONTSIZE
Font size for X-axis labels (default 6)
--yaxis_label_fontsize YAXIS_LABEL_FONTSIZE
Font size for Y-axis labels (default 6)
--legend_fontsize LEGEND_FONTSIZE
Font size for legend labels (default 6)
--annotation_fontsize ANNOTATION_FONTSIZE
Font size for annotation labels (default 6)
--hide_annotation_labels
Hide the label (fourth column text) from annotation
files, useful for regions with many annotations
--coverage_only Hide all reads and show only coverage
--max_coverage MAX_COVERAGE
apply a maximum coverage cutoff. Unlimited by default
--same_yaxis_scales Set the scales of the Y axes to the max of all
--marker_size MARKER_SIZE
Size of marks on pairs and splits (default 3)
--jitter [JITTER] Add uniform random noise to insert sizes. This can be
helpful to resolve overlapping entries. Either a
custom value (<1.0) is supplied or 0.08 will be used.
--dpi DPI Dots per inches (pixel count, default 300)
--annotation_scalar ANNOTATION_SCALAR
scaling factor for the optional annotation/trascript
tracks
--zoom ZOOM Only show +- zoom amount around breakpoints, much
faster for large regions. Ignored if region smaller
than --zoom (default 500000)
--debug DEBUG Print debug statements
Installing
Samplot is available from bioconda and is installable via the conda package manager:
conda install -c bioconda samplot
Examples:
Samplot requires either BAM files or CRAM files as primary input. If you use CRAM, you'll also need a reference genome. You can easily acquire a reference genome file with GGD, which is also available from conda.
Basic use case
Using data from NA12878, NA12889, and NA12890 in the 1000 Genomes Project (available in the test/data directory of samplot), we will inspect a possible deletion in NA12878 at 4:115928726-115931880 with respect to that same region in two unrelated samples NA12889 and NA12890.
The following command will create an image of that region:
time samplot plot \
-n NA12878 NA12889 NA12890 \
-b samplot/test/data/NA12878_restricted.bam \
samplot/test/data/NA12889_restricted.bam \
samplot/test/data/NA12890_restricted.bam \
-o 4_115928726_115931880.png \
-c chr4 \
-s 115928726 \
-e 115931880 \
-t DEL
real 0m3.882s
user 0m3.831s
sys 0m0.328s
The arguments used above are:
-n The names to be shown for each sample in the plot
-b The BAM/CRAM files of the samples (space-delimited)
-o The name of the output file containing the plot
-c The chromosome of the region of interest
-s The start location of the region of interest
-e The end location of the region of interest
-t The type of the variant of interest
This will create an image file named 4_115928726_115931880.png, shown below:
Gene and other genomic feature annotations
Gene annotations (tabixed, gff3 file) and genome features (tabixed, bgzipped, bed file) can be included in the plots.
Get the gene annotations:
wget ftp://ftp.ensembl.org/pub/grch37/release-84/gff3/homo_sapiens/Homo_sapiens.GRCh37.82.gff3.gz
bedtools sort -i Homo_sapiens.GRCh37.82.gff3.gz \
| bgzip -c > Homo_sapiens.GRCh37.82.sort.gff3.gz
tabix Homo_sapiens.GRCh37.82.sort.gff3.gz
Get genome annotations, in this case Repeat Masker tracks and a mappability track:
wget http://hgdownload.cse.ucsc.edu/goldenpath/hg19/encodeDCC/wgEncodeMapability/wgEncodeDukeMapabilityUniqueness35bp.bigWig
bigWigToBedGraph wgEncodeDukeMapabilityUniqueness35bp.bigWig wgEncodeDukeMapabilityUniqueness35bp.bed
bgzip wgEncodeDukeMapabilityUniqueness35bp.bed
tabix wgEncodeDukeMapabilityUniqueness35bp.bed.gz
curl http://hgdownload.soe.ucsc.edu/goldenPath/hg19/database/rmsk.txt.gz \
| bgzip -d -c \
| cut -f 6,7,8,13 \
| bedtools sort -i stdin \
| bgzip -c > rmsk.bed.gz
tabix rmsk.bed.gz
Plot:
samplot plot \
-n NA12878 NA12889 NA12890 \
-b samplot/test/data/NA12878_restricted.bam \
samplot/test/data/NA12889_restricted.bam \
samplot/test/data/NA12890_restricted.bam \
-o 4_115928726_115931880.d100.genes_reps_map.png \
-c chr4 \
-s 115928726 \
-e 115931880 \
-t DEL \
-d 100 \
-T Homo_sapiens.GRCh37.82.sort.gff3.gz \
-A rmsk.bed.gz wgEncodeDukeMapabilityUniqueness35bp.bed.gz
Generating images from a VCF file
To plot images from structural variant calls in a VCF file, use samplot's
vcf subcommand. This accepts a VCF file and the BAM files of samples
you wish to plot, outputting images and an index.html page for review.
Usage
samplot vcf
usage: samplot vcf [-h] [--vcf VCF] [-d OUT_DIR] [--ped PED] [--dn_only]
[--min_call_rate MIN_CALL_RATE] [--filter FILTER]
[-O {png,pdf,eps,jpg}] [--max_hets MAX_HETS]
[--min_entries MIN_ENTRIES] [--max_entries MAX_ENTRIES]
[--max_mb MAX_MB] [--min_bp MIN_BP]
[--important_regions IMPORTANT_REGIONS] -b BAMS [BAMS ...]
[--sample_ids SAMPLE_IDS [SAMPLE_IDS ...]]
[--command_file COMMAND_FILE] [--format FORMAT]
[--gff3 GFF3] [--downsample DOWNSAMPLE] [--manual_run]
[--plot_all] [-t THREADS] [--debug]
options:
-h, --help show this help message and exit
--vcf VCF, -v VCF VCF file containing structural variants (default:
None)
-d OUT_DIR, --out-dir OUT_DIR
path to write output images (default: samplot-out)
--ped PED path to ped (or .fam) file (default: None)
--dn_only plots only putative de novo variants (PED file
required) (default: False)
--min_call_rate MIN_CALL_RATE
only plot variants with at least this call-rate
(default: None)
--filter FILTER simple filter that samples must meet. Join multiple
filters with '&' and specify --filter multiple times
for 'or' e.g. DHFFC < 0.7 & SVTYPE = 'DEL' (default:
[])
-O {png,pdf,eps,jpg}, --output_type {png,pdf,eps,jpg}
type of output figure (default: png)
--max_hets MAX_HETS only plot variants with at most this many
heterozygotes (default: None)
--min_entries MIN_ENTRIES
try to include homref samples as controls to get this
many samples in plot (default: 6)
--max_entries MAX_ENTRIES
only plot at most this many heterozygotes (default:
10)
--max_mb MAX_MB skip variants longer than this many megabases
(default: None)
--min_bp MIN_BP skip variants shorter than this many bases (default:
20)
--important_regions IMPORTANT_REGIONS
only report variants that overlap regions in this bed
file (default: None)
-b BAMS [BAMS ...], --bams BAMS [BAMS ...]
Space-delimited list of BAM/CRAM file names (default:
None)
--sample_ids SAMPLE_IDS [SAMPLE_IDS ...]
Space-delimited list of sample IDs, must have same
order as BAM/CRAM file names. BAM RG tag required if
this is omitted. (default: None)
--command_file COMMAND_FILE
store commands in this file. (default:
samplot_vcf_cmds.tmp)
--format FORMAT comma separated list of FORMAT fields to include in
sample plot title (default: AS,AP,DHFFC)
--gff3 GFF3 genomic regions (.gff with .tbi in same directory)
used when building HTML table and table filters
(default: None)
--downsample DOWNSAMPLE
Number of normal reads/pairs to plot (default: 1)
--manual_run disables auto-run for the plotting commands (default:
False)
--plot_all plots all samples and all variants - limited by any
filtering arguments set (default: False)
-t THREADS, --threads THREADS
Number of threads to use to generate plots. Default: 1
--debug prints out the reason for skipping any skipped variant
entry (default: False)
samplot vcf can be used to quickly apply some basic filters to variants. Filters are applied via the --filter argument, which may be repeated as many times as desired. Each expression specified with the --filter option is applied separately in an OR fashion, which & characters may be used within a statement for AND operations.
Example:
samplot vcf \
--filter "SVTYPE == 'DEL' & SU >= 8" \
--filter "SVTYPE == 'INV' & SU >= 5" \
--vcf example.vcf\
-d test/\
-O png\
--important_regions regions.bed\
-b example.bam > samplot_commands.sh
This example will create a directory named test (in the current working directory). A file named index.html will be created inside that directory to explore the images created.
Filters: The above filters will remove all samples/variants from output except:
DUPvariants with at leastSUof 8INVvariants withSUof at least 5
The specific FORMAT fields available in your VCF file may be different. I recommend SV VCF annotation with duphold by brentp.
For more complex expression-based VCF filtering, try brentp's slivar, which provides similar but more broad options for filter expressions.
Region restriction. Variants can also be filtered by overlap with a set of region (for example, gene coordinates for genes correlated with a disease). The important_regions argument provides a BED file of such regions for this example.
Filtering for de novo SVs
Using a PED file with samplot vcf allows filtering for variants that may be spontaneous/de novo variants. This filter is a simple Mendelian violation test. If a sample 1) has valid parent IDs in the PED file, 2) has a non-homref genotype (1/0, 0/1, or 1/1 in VCF), 3) passes filters, and 4) both parents have homref genotypes (0/0 in VCF), the sample may have a de novo variant. Filter parameters are not applied to the parents. The sample is plotted along with both parents, which are labeled as father and mother in the image.
Example call with the addition of a PED file:
samplot vcf \
--filter "SVTYPE == 'DEL' & SU >= 8" \
--filter "SVTYPE == 'INV' & SU >= 5" \
--vcf example.vcf\
-d test/\
-O png\
--ped family.ped\
--important_regions regions.bed\
-b example.bam > samplot_commands.sh
Additional notes.
- Variants where fewer than 95% of samples have a call (whether reference or alternate) will be excluded by default. This can be altered via the command-line argument
min_call_rate. - If you're primarily interested in rare variants, you can use the
max_hetsfilter to remove variants that appear in more thanmax_hetssamples. - Large variants can now be plotted easily by samplot through use of
samplot plot'szoomargument. However, you can still choose to only plot variants larger than a given size using themax_mbargument. Thezoomargument takes an integer parameter and shows only the intervals within +/- that parameter on either side of the breakpoints. A dotted line connects the ends of the variant call bar at the top of the window, showing that the region between breakpoint intervals is not shown. - By default, if fewer than 6 samples have a variant and additional homref samples are given, control samples will be added from the homref group to reach a total of 6 samples in the plot. This number may be altered using the
min_entriesargument. - Arguments that are optional in
samplot plotcan by given as arguments tosamplot vcf. They will be applied to each image generated.
CRAM inputs
Samplot also support CRAM input, which requires a reference fasta file for reading as noted above. Notice that the reference file is not included in this repository due to size. This time we'll plot an interesting duplication at X:101055330-101067156.
samplot plot \
-n NA12878 NA12889 NA12890 \
-b samplot/test/data/NA12878_restricted.cram \
samplot/test/data/NA12889_restricted.cram \
samplot/test/data/NA12890_restricted.cram \
-o cramX_101055330_101067156.png
-c chrX \
-s 101055330 \
-e 101067156 \
-t DUP \
-r hg19.fa
The arguments used above are the same as those used for the basic use case, with the addition of the following:
-r The reference file used for reading CRAM files
Plotting without the SV
Samplot can also plot genomic regions that are unrelated to an SV. If you do
not pass the SV type option (-t) then the top SV bar will go away and only
the region that is given by -c -s and -e will be displayed.
Long read (Oxford nanopore and PacBio) and linked read support
Any alignment that is longer than 1000 bp is treated as a long read, and the plot design will focus on aligned regions and gaps. Aligned regions are in orange, and gaps follow the same DEL/DUP/INV color code used for short reads. The height of the alignment is based on the size of its largest gap.
If the bam file has an MI tag, then the reads will be treated as linked reads. The plots will be similar to short read plots, but all alignments with the same MI is plotted at the same height according to alignment with the largest gap in the group. A green line connects all alignments in a group.
