Sample¶

class missionbio.mosaic.sample.Sample(name=None, dna=None, cnv=None, protein=None, cnv_raw=None, protein_raw=None)¶

Container for multiple assays.

Just like the missionbio.mosaic.assay._Assay object, Sample can also be filtered using Python’s slice notation.

It accepts only one key - a list of barcodes, a list of the position of the barcodes, or a Boolean list.

Load the sample.

>>> import missionbio.mosaic.io as mio
>>> sample = mio.load('/path/to/h5')

Selecting the first 100 cells (these aren’t necessarily cells with the highest reads, they’re arbitrary cells).

>>> select_bars = sample.dna.barcodes()[:100]

Slice all assays in the sample.

>>> filtered_sample = sample[select_bars]

Once the analysis is complete, it can be saved and shared using:

>>> mio.save(sample)

Methods

reset([assay])

Resets to the original state.

Multi-assay visualizations

`heatmap`(clusterby, sortby[, drop, flatten])	Multi-assay heatmap.
`clone_vs_analyte`([analyte, plot_width])	Set of summary plots to give a run overview.
`umaps`()	Plots umap arrays from assay objects.

Raw count visualizations

`assay_scatter`([ax, title, highlight])	Plots DNA reads vs Protein reads.
`raw_heatmaps`()	Protein and DNA read distribution.
`read_data`()	Plot read statistics of each barcode.

Mosaic