smfishHmrf: smfishHmrf: A package for running hidden markov random field...

In smfishHmrf: Hidden Markov Random Field for Spatial Transcriptomic Data

Description

A package for running hidden markov random field \insertCiteZhu2018smfishHmrf on smFISH and other spatial transcriptomic datasets.

Input

The inputs of HMRF are the following:

• Gene expression matrix

• Cell neighborhood matrix

• Initial centroids of clusters

• Number of clusters

• beta

smfishHmrf has been tested to work on seqFISH, MERFISH, starMAP, 10X Visium and other datasets. See Giotto \insertCiteDries701680smfishHmrf for examples of such datasets and to learn about the technologies. smfishHmrf is a general algorithm, and should probably work with other data types.

Running

The first step is to calculate initial centroids on the gene expression matrix given k (the number of clusters). The function smfishHmrf.generate.centroid.it is used for this purpose.

The next step is to run the HMRF algorithm given the expression matrix, and cell neighborhood matrix. The function smfishHmrf.hmrfem.multi.it.min is used for this purpose.

Variations

You might notice several variations of the functions:

• smfishHmrf.hmrfem.multi.it.min: supports multiple betas; supports file names as inputs. This is the recommended function.

• smfishHmrf.hmrfem.multi.it: supports multiple betas; supports R data structures as inputs.

• smfishHmrf.hmrfem.multi: supports a single beta; supports R data structures as inputs.

• Note: beta is the smoothness parameter of HMRF

Also:

• smfishHmrf.generate.centroid.it: supports file names as inputs. This is the recommended function

• smfishHmrf.generate.centroid: supports R matrices as inputs. Assumes input files have been read into R matrices.

• smfishHmrf.generate.centroid.use.exist: loads existing centroids. Assumes that centroids have been generated previously and saved to disk.

References

\insertRef

Zhu2018smfishHmrf

\insertRef

Dries701680smfishHmrf

smfishHmrf documentation built on Jan. 13, 2021, 12:54 p.m.