Svist4get capabilities are demonstrated in [16], where figures were produced with svist4get Python API. Here we show several practical use cases of the command-line interface by visualizing particular genomic windows related to genes and transcripts using existing genome annotation. The command line parameters to reproduce the presented images are provided in Additional file 2.
The basic cases (Figs. 1 and 2) are illustrated by using yeast ribosome profiling (Ribo-Seq) and RNA-Seq data from [17] downloaded from GWIPs-viz [18], and yeast genome reference annotation from Ensembl [19]. For convenience, in the svist4get package, we include truncated sample data that is used for demonstration purposes. Visualization of tissue-specific expression of different transcript isoforms (Fig. 3) uses mouse Ribo-Seq data [20, 21] that was downloaded from GWIPs-viz [18, 22] and GENCODE M13 [23] mouse genome annotation.
Basic visualization of genomic windows
We employed svist4get to generate a visualization of the genomic window containing the YFL031W transcript of HAC1 gene (Fig. 1). Based on genome annotation and a transcript identifier, svist4get selects a genomic window that includes a particular transcript. Alternative scenarios include the selection of a genomic window based on gene identifier and visualization of all transcripts in a given window (Additional file 2). Svist4get renders the transcript structure (based on genome annotation) as the top track, below it places the signal tracks (based on data in bedGraph format), and the structure of open reading frames (0, + 1, + 2, based on the nucleotide sequence of the displayed window) is shown at the bottom.
Visualizing a genomic window at the single-nucleotide resolution
We also used svist4get to show a surrounding region of a translation initiation site of DFG16 yeast gene (Fig. 2), including an upstream open reading frame (ORF). The general layout of tracks in Fig. 2 is similar to that of Fig. 1. An additional track is used to show arbitrary genomic segments with user-defined labels (upstream ORF and CDS). A smaller genomic region surrounding DFG16 translation initiation site was selected based on transcript ID. A wider template (the predefined configuration file) allowed single-nucleotide resolution.
Visualizing ribosome occ2upancy in overlapping transcripts
We also show a multi-track visualization illustrating differential ribosome occupancy in mouse kidney and liver Ribo-Seq data (Fig. 3). Reconcilable parts of introns of two annotated transcripts are collapsed (red vertical marks on the transcript structure tracks) to facilitate a non-interrupted view of the translated shortened open reading frame that is specific to the liver.
Advanced features and customization
A basic bedGraph track is potentially useful to display various transcriptomic and genomic signals, such as DNase-Seq or ChIP-Seq. However, it is often necessary to visually separate signals on the primary and the reverse complementary DNA strands. To this end, svist4get provides paired bedGraph tracks, which use a single Y-axis to plot signals from a given pair of bedGraph files in the positive and negative value ranges (Fig. 4). Figure 4 also demonstrates multiple highlighting by showcasing translated segments of the MATa locus transcripts.
The visualization of svist4get is highly customizable. Some essential options, such as custom track coloring, are available directly through the command-line interface. Other parameters, such as color palette, bitmap DPI setting, font typeface, and page size are defined in configuration files (see Additional file 2 for details). The package includes default color palette and editable configuration files for generating figures to fit one- and two-column layout of an A4 page.
