API

Import CHESSBOARD as:

import chessboard.api as cb

Read and Write: io

Functions for reading and writing data. Users need to read input data into a CHESSBOARD io.Data object to perform all downstream operations, data manipulation and analysis. CHESSBOARD currently accept 2 input data types.

  1. MAJIQ builder .majiq files. These files contain junction spanning read counts from MAJIQ [Vaquero-Garcia16].

  2. Equivalent data processed through another junction mapping software in the form of .tsv files.

io.Data(reads, samples, lsvs, psi)

CHESSBOARD object for storing and manipulating data.

io.createFromMajiq(dir, outfilename[, ...])

Process and save MAJIQ generated data.

io.loadData(file)

Load MAJIQ generated data.

io.loadTSV(file1, file2)

Load data from .tsv files.

io.saveData(data, file)

Save the current state of a CHESSBOARD object.

io.loadCBObject(file)

Load saved CHESSBOARD object.

Data Preprocessing: prefilter

Functions for prefiltering informative LSVs as described in Wang et al. 2022.

prefilter.VarFilter(data, var_thresh)

Variance filter

prefilter.PBSFilter(data[, n_boot, alpha])

PBS KS Filter

Prior Estimation: priors

Functions for estimating priors.

priors.EstimateMissingPriors(data, background)

Posterior Summary: postsum

Functions for summarizing posterior samples.

postsum.generatePointEstimate(data, minprob)

Generate a clustering point estimate from MCMC samples.

Downstream Analysis: analysis

Functions for summarizing posterior samples.

analysis.outputLSVLists(data, file)

Output Excel .xlsx file containing summary statistics

analysis.computeLikelihood(data, x, r)

Compute likelihood on held out test data.

Visualization: vis

Visualization tools.

vis.PlotECDF(data)

ECDF plot

vis.PlotPointEstimate(data[, save])

Heatmap cluster plot

vis.PlotPointEstimate(data[, save])

Heatmap cluster plot

vis.Heatmap(data[, row_labels, col_labels, ...])

Heatmap plot

vis.Histogram(data, i)

LSV Histogram