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Plot structural variant signals from many BAMs and CRAMs

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CircleCI install with bioconda

is a command line tool for rapid, multi-sample structural variant visualization.
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


samplot plot
optional arguments:
-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")
                      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
--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
                      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)
                      Space-delimited list of bed.gz tabixed files of
                      annotations (such as repeats, mappability, etc.)
                      Space-delimited list of names for the tracks in
--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
                      Plot height
-W PLOT_WIDTH, --plot_width PLOT_WIDTH
                      Plot width
                      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
-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)
--common_insert_size  Set common insert size for all plots
                      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)
--dpi DPI             Dots per inches (pixel count, default 300)
--annotation_scalar ANNOTATION_SCALAR
                      scaling factor for the optional annotation/transcript
--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


is available from bioconda and is installable via the conda package manager:
conda install -c bioconda samplot 


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/NA12878restricted.bam \ samplot/test/data/NA12889restricted.bam \ samplot/test/data/NA12890restricted.bam \ -o 4115928726_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 bedtools sort -i Homosapiens.GRCh37.82.gff3.gz \ | bgzip -c > Homosapiens.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 bigWigToBedGraph wgEncodeDukeMapabilityUniqueness35bp.bigWig wgEncodeDukeMapabilityUniqueness35bp.bed bgzip wgEncodeDukeMapabilityUniqueness35bp.bed tabix wgEncodeDukeMapabilityUniqueness35bp.bed.gz

curl \ | bgzip -d -c \ | cut -f 6,7,8,13 \ | bedtools sort -i stdin \ | bgzip -c > rmsk.bed.gz tabix rmsk.bed.gz ```


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

subcommand. This accepts a VCF file and the BAM files of samples you wish to plot, outputting images and an
page for review.


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] [--gff GFF]
                 [--downsample DOWNSAMPLE] [--manual_run]

optional arguments:
-h, --help            show this help message and exit
--vcf VCF, -v VCF     VCF file containing structural variants
-d OUT_DIR, --out-dir OUT_DIR
                      path to write output PNGs
--ped PED             path ped (or .fam) file
--dn_only             plots only putative de novo variants (PED file
--min_call_rate MIN_CALL_RATE
                      only plot variants with at least this call-rate
--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'
-O {png,pdf,eps,jpg}, --output_type {png,pdf,eps,jpg}
                      type of output figure
--max_hets MAX_HETS   only plot variants with at most this many
--min_entries MIN_ENTRIES
                      try to include homref samples as controls to get this
                      many samples in plot
--max_entries MAX_ENTRIES
                      only plot at most this many heterozygotes
--max_mb MAX_MB       skip variants longer than this many megabases
--min_bp MIN_BP       skip variants shorter than this many bases
--important_regions IMPORTANT_REGIONS
                      only report variants that overlap regions in this bed
-b BAMS [BAMS ...], --bams BAMS [BAMS ...]
                      Space-delimited list of BAM/CRAM file names
--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 ommitted.
--command_file COMMAND_FILE
                      store commands in this file.
--format FORMAT       comma separated list of FORMAT fields to include in
                      sample plot title
--gff GFF             genomic regions (.gff with .tbi in same directory)
                      used when building HTML table and table filters
--downsample DOWNSAMPLE
                      Number of normal reads/pairs to plot
--manual_run          don't auto-run the samplot plot commands (command_file
                      will be deleted)

samplot vcf
can be used to quickly apply some basic filters to variants. Filters are applied via the
argument, which may be repeated as many times as desired. Each expression specified with the
option is applied separately in an OR fashion, which
characters may be used within a statement for AND operations.


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 >

This example will create a directory named test (in the current working directory). A file named

will be created inside that directory to explore the images created.

Filters: The above filters will remove all samples/variants from output except: *

variants with at least
of 8 *
variants with
of at least 5

The specific

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

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 >

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

. * If you're primarily interested in rare variants, you can use the
filter to remove variants that appear in more than
samples. * Large variants can now be plotted easily by samplot through use of
samplot plot
argument. However, you can still choose to only plot variants larger than a given size using the
argument. The
argument 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
argument. * Arguments that are optional in
samplot plot
can by given as arguments to
samplot 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:

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 (

) then the top SV bar will go away and only the region that is given by
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.

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