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PlotList

dat/PlotList.dat defines integration event and regions of interest.

The goal of this stage is to generate the PlotList.dat file, a key step for downstream plotting and analysis. Each line of PlotList.dat will generally yield one structure plot and one expresssion plot figure.

PlotList File Format

PlotList.dat is a tab separated (TSV) format with the columns,

  • barcode
  • event.name (unique)
  • chrom.a (first chromosome of coordinate pair)
  • event.a.start, event.a.end (indicates region of e.g. SV event)
  • range.a.start, range.a.end
  • chrom.b, (second chromosome of coordiante pair)
  • event.b.start, event.b.end, range.b.start, range.b.end

The event positions identify the predicted integration event. The range positions define a region of interest around the integration event which will be used for plotting of structure plots. (This region is not used for expression plots). The "padding" around the integration event to the context:

range.a.start = event.start - context 
range.a.end = event.end + context

Clustering

To automatically generate regions of interest, we group multiple nearby breakpoints on the same chromosome pair into clusters to serve as preliminary integration event predictions.

With each breakpoint between chromA and chromB represented by a point with coordinates (posA, posB), the clustering algorithm draws a square with sides length L/2 centered at each breakpoint, and all breakpoints within overlapping squares are grouped into one cluster. Details in makeBreakpointRegions.py.

TCGA_Virus

Nearby Pindel breakpoints between the same chromosome and virus (those occurring within 50Kbp of one another along both genomes) were clustered into integration events, which defined regions of interest for all subsequent analyses. Note that for the sample of interest all three breakpoints were nearby.

We include an additional 50Kbps "padding" around the integration event to include in structure plot. Note that expression analysis uses integration event positions from PlotList, but includes a larger domain to identify genes of interest for that analysis.

Getting started

If regions of interest for downstream analysis are known, clustering and prioritization is not necessary. A simple approach then is to create a BPR file to define regions of interest to be used as input into 3_make_PlotList.sh, which will calculate the range values.

Clustering of discordant reads to prioritize regions of interest is demonstrated in the 1000SV workflow.