MouseIleumPetukhov2021: MERFISH mouse ileum dataset from Petukhov et al., 2021

View source: R/ileum.R

MouseIleumPetukhov2021R Documentation

MERFISH mouse ileum dataset from Petukhov et al., 2021

Description

Obtain the MERFISH mouse ileum dataset from Petukhov et al., 2021

Usage

MouseIleumPetukhov2021(
  segmentation = c("baysor", "cellpose"),
  use.images = TRUE,
  use.polygons = TRUE
)

Arguments

segmentation

character. Should be either "baysor" or "cellpose". Defaults to "baysor". See details.

use.images

logical. Should DAPI and Membrane Na+/K+ - ATPase images be loaded into memory and annotated to the imgData slot of the returned SpatialExperiment? Defaults to TRUE. See details.

use.polygons

logical. Should polygon cell boundaries be annotated to the metadata of the returned SpatialExperiment? Defaults to TRUE. Only available for Baysor segmentation.

Details

Spatial transcriptomics protocols based on in situ sequencing or multiplexed RNA fluorescent hybridization can reveal detailed tissue organization. Distinguishing the boundaries of individual cells in such data is challenging. Current segmentation methods typically approximate cells positions using nuclei stains.

Petukhov et al., 2021, describe Baysor, a segmentation method, which optimizes 2D or 3D cell boundaries considering joint likelihood of transcriptional composition and cell morphology. Baysor can also perform segmentation based on the detected transcripts alone.

Petukhov et al., 2021, compare the results of Baysor segmentation (mRNA-only) to the results of a deep learning-based segmentation method called Cellpose from Stringer et al., 2021. Cellpose applies a machine learning framework for the segmentation of cell bodies, membranes and nuclei from microscopy images.

The function allows to obtain segmented MERFISH mouse ileum data for both segmentation methods.

A note on storing images within a SpatialExperiment: The default use.images = TRUE reduces the 9-frame z-stack images for DAPI stain and Membrane Na+/K+ - ATPase fluorecense to single-frame images (taking the first frame). For working with the 9-frame z-stack images it is recommended to load the images individually from ExperimentHub.

Value

An object of class SpatialExperiment.

Source

https://doi.org/10.5061/dryad.jm63xsjb2

References

Petukhov et al. (2021) Cell segmentation in imaging-based spatial transcriptomics. Nat Biotechnol, 40(3), 345-54.

Stringer et al. (2021) Cellpose: a generalist algorithm for cellular segmentation. Nat Methods, 18(1), 100-6.

Examples

spe <- MouseIleumPetukhov2021()

ccb-hms/MerfishData documentation built on Aug. 7, 2022, 12:05 a.m.