ProteinPaint and GenomePaint Examples 15 Visualizations

Visualize Juicebox .hic files from Hi-C experiments. The Hi-C track also supports a whole genome view, example here. Learn more about the Hi-C track.

View sequence alignment data from BAM files. Features include: viewing soft clips, on-the-fly checks for mismatches, switching between single and paired mode, etc. The unique features specific to ProteinPaint include: A “global” view of almost all the reads i...

View genomic feature annotation with the JSON BED track. Hover over an area of interest to see the characterization of that genomic feature. Learn more about the JSON BED track.

View quantitative data at genomic positions with the BigWig track. Learn more about the BigWig track.

The expression rank track shows the ranking of gene expression in each sample, amongst all samples from the same cancer group. Expression rankings are rendered as bar plots under the 0 to 100 scale, 0 for lowest among the group, 100 for highest. Hover over a b...

The FusionEditor elegantly depicts one or more sample's fusion events in a prioritized list by CICERO rate and event group. Click on a rated group (e.g. HQ in-frame 7) to reveal the fusion events related to the Cicero output. Hover over or click the fusion eve...

View coding mutations and gene fusions in curated datasets, available from St. Jude. The full view of the protein by default and groups mutations by amino acid positions. The discs representing mutations at the same amino acid position are aligned to the same...

Explore RNA splice junction data for one or more RNA-seq samples. Scroll over the splice junctions to view the base length, position, and read count. When available, alternate exon usage data appears between the splice junction display and RefGene isoforms. Cl...

In the Stranded BigWig track, view complex data such as RNAseq with forward and reverse strands. Learn more about the creating Stranded BigWig tracks.

St. Jude's own Dr.Xiaotu Ma coined the term "AI Check" after designing this visualization. Compare the allelic imbalance of heterozygous SNP markers in a tumor genome against a patient's germline genome, as a targeted method for evaluating loss-of-he...

The VCF track features a population frequency filter, coverage-VAF plot, sample line plot, boxplot by genotype, and sophisticated methods for displaying metadata (see summary here). The current implement only accepts SNV/indel data. Learn more about the VCF tr...

The allele-specific expression (ASE) track annotates the tumor gene expression. Scroll through the color coded FPKM values on the right to reveal the ASE status: mono-allelic, bi-allelic, uncertain, or no information available. Clicking on the DNA markers repr...

Click on the 'Tracks' button, second to the right, in the visualization header. Click on the button under 'FACET' to open a popup window to see tracks arranged by sample vs. assay. Tracks can be shown in groups by clicking on the row or column links as well as...

Use the interactive MA and Volcano plot for exploring differentially expressed genes. Hover over the data points to view calculated values per gene. Hovering also reveals the location of the gene in both plots. Clicking on the data point opens the genome brows...

The profile gene value (PVG) track is a combination of genomic profiling results and gene-level numerical values over a set of sample. Hover over the bars to reveal more information about the chromatin states. Pair with the chromatin data other types of gene v...

The ARC track shows the interactions of each region mapped from Hi-C data. In this track, the arcs are drawn between the centers of each region regions. The intensity of each arc corresponds to the proximity score as the color legend scale indicates. Interacti...

This splice junction cohort shows the results of splicing reads for over 1740 samples for the TP53 gene. Canonical, alternative splicing are shown as well as unannotated cases. These splice types are also color coded. Each splice is denoted by a circle in pr...