msireg

R package for co-registration of Mass Spectrometry images with Microscopy images using SimpleITK

https://github.com/sslakkimsetty/msireg

Science Score: 57.0%

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  • codemeta.json file
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  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 2 DOI reference(s) in README
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    Low similarity (13.1%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

R package for co-registration of Mass Spectrometry images with Microscopy images using SimpleITK

Basic Info
  • Host: GitHub
  • Owner: sslakkimsetty
  • License: gpl-3.0
  • Language: HTML
  • Default Branch: main
  • Size: 15.3 MB
Statistics
  • Stars: 5
  • Watchers: 1
  • Forks: 0
  • Open Issues: 2
  • Releases: 0
Created over 3 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.Rmd

---
output: 
    github_document: 
        html_preview: false
---



```{r, include = FALSE}
knitr::opts_chunk$set(
    collapse = TRUE,
    comment = "#>",
    fig.path = "man/figures/README-",
    out.width = "100%"
)
```


# msireg




The goal of _msireg_ is to co-register mass spectrometry images (MSI) with microscopic optical images using `SimpleIK`. 


## Installation

You can install the development version of msireg from [GitHub](https://github.com/) with:

```{r, eval=FALSE} 
if ( !require(devtools) ) { # if not installed already 
    install.packages("devtools") 
}

devtools::install_github("sslakkimsetty/msireg")
```


## Example usage 

```{r, eval=FALSE} 

```


# Details 

_msicoreg_ co-registers MS images with optical images (H&E stained, AF) using the family of registration methods from the `SimpleITK` package. The package offers processing and summarization of MS imaging data and optical images. This package uses spatial shrunken centroids method from the `Cardinal` package to filter out unimportant features. 



# References 

[1] Bemis, K. D., Harry, A., Eberlin, L. S., Ferreira, C., van de Ven, S. M., Mallick, P., Stolowitz, M., and Vitek, O.", "Cardinal: an R package for statistical analysis of mass spectrometry-based imaging experiments. 

[2] L.J.P. van der Maaten and G.E. Hinton. Visualizing High-Dimensional Data Using t-SNE. Journal of Machine Learning Research 9(Nov):2579-2605, 2008. 

[3] Gregoire Pau, Florian Fuchs, Oleg Sklyar, Michael Boutros, and Wolfgang Huber (2010):", "EBImage - an R package for image processing with applications to cellular phenotypes.", "Bioinformatics 

[4] Beare, R., Lowekamp, B., & Yaniv, Z. (2018). Image Segmentation, Registration and Characterization in R with SimpleITK. Journal of Statistical Software, 86(8), 1–35. https://doi.org/10.18637/jss.v086.i08 

[5] Reference for data (in data/) 













Owner

  • Name: Sai Srikanth Lakkimsetty
  • Login: sslakkimsetty
  • Kind: user
  • Location: Boston, MA

PhD student in Vitek Lab at Northeastern University

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Lakkimsetty"
  given-names: "Sai Srikanth"
  orcid: "https://orcid.org/0000-0001-9552-1121"
title: "R package for co-registration of Mass Spectrometry images with Microscopy images using SimpleITK"
version: 0.1
date-released: 2022-09-03
url: "https://github.com/sslakkimsetty/msireg"

GitHub Events

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  • Issues event: 1
  • Watch event: 3
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Dependencies

DESCRIPTION cran
  • BiocParallel * imports
  • Cardinal * imports
  • EBImage * imports
  • Rtsne * imports
  • SimpleITK * imports
  • graphics * imports
  • sp * imports
  • knitr * suggests
  • testthat >= 3.0.0 suggests