Create BioTuring Compressed Study (bcs) file
Project description
pyBCS
This is a python library to create a BioTuring Compressed Study (bcs
) file from an AnnData (scanpy) object.
bcs
files can be imported directly into BBrowser, a software for single-cell data.
Visit our github for more detail.
Installation
pip install pyBCS-bioturing
Example
Scanpy
from pyBCS import scanpy2bcs
scanpy2bcs.format_data("/mnt/example/data.h5ad", "/mnt/example/data.bcs",
input_format="h5ad", graph_based="louvain")
If your data has antibody-derived tags (ADT), you can put ADT expression data in the obs
as cell metadata with a distinguishable suffix. For example, ADT expression of CD45
will be CD45_TotalSeqC
. In such cases, you can declare cite_seq_suffix
when using format_data()
:
scanpy2bcs.format_data("/mnt/example/data.h5ad", "/mnt/example/data.bcs",
input_format="h5ad", graph_based="louvain", cite_seq_suffix="TotalSeqC")
SPRING
from pyBCS import scanpy2bcs
scanpy2bcs.format_data("/mnt/example/spring_study", "/mnt/example/data.bcs",
input_format="spring",
graph_based="louvain")
Loom
from pyBCS import scanpy2bcs
scanpy2bcs.format_data("/mnt/example/data.loom", "/mnt/example/data.bcs",
input_format="loom",
barcode_name="CellID",
feature_name="Gene",
dimred_keys={"tsne":["tsne1", "tsne2"]})
Abloom
from pyBCS import scanpy2bcs
scanpy2bcs.format_data("/mnt/example/data.loom", "/mnt/example/data.bcs",
input_format="abloom",
barcode_name="observation_id",
feature_name="accession_id",
graph_based="cluster")
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