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SparK: A Publication-quality NGS Visualization Tool

Kurtenbach, S.; Harbour, J. W.

2019-11-16 bioinformatics
10.1101/845529 bioRxiv
Show abstract

While there are sophisticated resources available for displaying NGS data, including the Integrative Genomics Viewer (IGV) and the UCSC genome browser, exporting regions and assembling figures for publication remains challenging. In particular, customizing track appearance and overlaying track replicates is a manual and time-consuming process. Here, we present SparK, a tool which auto-generates publication-ready, high-resolution, true vector graphic figures from any NGS-based tracks, including RNA-seq, ChIP-seq, and ATAC-seq. Novel functions of SparK include averaging of replicates, plotting standard deviation tracks, and highlighting significantly changed areas. SparK is written in Python 3, making it executable on any major OS platform. Using command line prompts to generate figures allows later changes to be made very easy. For instance, if the genomic region of the plot needs to be changed, or tracks need to be added or removed, the figure can easily be re-generated within seconds without the manual process of re-exporting and re-assembling everything. After plotting with SparK, changes to the output SVG vector graphic files are simple to make, including text, lines, and colors. SparK is publicly available on GitHub: https://github.com/harbourlab/SparK.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.