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Dockerized MAST (Model-based Analysis of Single-cell Transcriptomics) for computing genes that are differentially expressed in each cluster compared to the rest of the data.

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docker-mast

Dockerized MAST (Model-based Analysis of Single-cell Transcriptomics) for computing genes that are differentially expressed in each cluster compared to the rest of the data.

How to Compute Differentially Expressed Genes

prepare-MAST.ipynb takes a h5ad file and generates:

df.0.RDS
df.0.rest.RDS
df.0.tgz
.
.
.
df.n.RDS
df.n.rest.RDS
df.n.tgz

where 0..n is the cluster number.

df.n.tgz is a tarball gzipped of two files: df.n.RDS and df.n.rest.RDS.

The reason is to analyze each cluster in parallel way (rather than passing the entire h5ad or RDS to each worker).

pairwise-diffexp.R takes two arguments:

  • cluster number
  • output CSV filename

For example, if you specify cluster number 5, it will load df.1.RDS and df.1.rest.RDS and compute the genes that are differentially expressed in cluster 5 compared to the rest of the data.

Running Notebook

./run-notebook.sh

Build Container Image

./build.sh

Push to Docker Registry

Either you can use the docker push command or run push.sh (requires SCING):

./push.sh

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Dockerized MAST (Model-based Analysis of Single-cell Transcriptomics) for computing genes that are differentially expressed in each cluster compared to the rest of the data.

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