We would be excited to host your scRNA-seq data from the eye!
If you would like to host your scRNA-seq data on Spectacle, you can do so in the following ways:
1. Share your original Seurat object with the Spectacle Team
The Spectacle team will process and upload your dataset
Please save and share your Seurat object as an .RData object
@meta.data slot must meet meta data requirements (see below)
2. Share the following three files in .csv/similar formats:
A processed expression matrix (genes x cells)
Meta data (see meta data requirements below)
Meta data requirements
Required: column for classified cell type, cluster number, species, tissue, library name (i.e., donor-1, mouse-1, etc)
Optional: independent columns for each biological variable compared (e.g., fovea vs periphery, disease vs control, etc)
How to share files
Please email email@example.com to plan a data-sharing option that works best for you
When to share files
We can accomodate files pre-peer review or after acceptance of your publication
If requested, we can generate a secret access code to provide reviewers.
Only scRNA-seq studies from the eye will be considered.
Please allow 2-4 weeks between sharing files to live access
The intent of Spectacle is to share datasets from the primary literature. If you do not plan on publishing your dataset or
submitting the raw data to a public repository like GEO, Spectacle may not be the best fit for your study.
Spectacle v0.1.0 (bifocals)
v0.1.0: September 7, 2020
First release corresponding to the manuscript described in
Experimental Eye Research.
v0.2.0: December 9, 2020
Introduced a toggle for gene expression to be explored in 'cartoon' form. Under the heat map tab, the user
may request to visualize the average gene expression for each cell population overlaid with a cartoon drawing
of the retina and/or RPE/choroid. This is more intuitive for the user and decreases plot rendering time
(as tens of thousands of points do not need to re-render for each new gene being queried).
Added all_retina_rpe_chor dataset; which used canonical correlation analysis to integrate cells from all currently published studies.
Added 'quick start' documentation that is visible upon loading Spectacle.
v0.2.1: December 17, 2020
Fixed violin plot for the all_retina_rpe_chor dataset that misordered cell types on the dendrogram.
v0.3.0: February 6, 2021
NEW DATASET: added foveal (1 mm) vs parafoveal (4 mm) human retina (8 paired samples from 4 donors).
NEW FEATURE: added regional expression explorer, which can be accessed from the lefthand menu,
to compare regional gene expression across 6 datasets.
Moved Spectacle to a new server, eliminating very slow loading times or connection timeouts from some internet providers.
Removed 'server timeouts' feature, making all plots fully interactive.
Added link to Mullins laboratory webpage.
v0.3.1: March 17, 2021
Fixed violin plot bug that prevented genes names with hyphens from rendering.
Spectacle v1.0.0 (aviators)
v1.0.0: July 4, 2021
Re-coded Spectacle features into Shiny modules, condensing code and improving efficiency.
NEW FEATURE: added dual-expression feature, which allows the user to visualize coexpression of two genes.
To access, the user must (1) load a dataset, (2) select the heatmap tab, (3) de-select the cartoon visualization slider,
(4) activate the coexpression slider.
Modified differential expression to include a maximum of 500 cells per identity (FindMarkers(max.cells.per.ident = 500)).
This accelerates differential expression with minimal changes to results.
Biological variables such as region and disease status can be used to color cells. Options are displayed in
the `color cells` dropdown menu beneath the Dimensionality Reduction Plot (or Reclustering Plot).
If a gene has zero expression across all cells, all dots in the heatmap are colored grey.
Improved handling of point sizes and legend labels.
Spectacle v2.0.0 (phoropters)
v2.0.0: Jan 25, 2021
Added 71 new datasets consistent of over 1.5M cells.
NEW FEATURE: Violin Plots now allow for visualization of expression between biological variables (if present in a dataset)
Various performance enhancements
Powered by cellcuratoR
cellcuratoR is an R package for sharing interactive single-cell expression data from Seurat. Any single-cell RNA
sequencing dataset processed with Seurat (v3) can be converted into objects interpretable by cellcuratoR. Code and
documentation are available at
as well as animated instructions for navigating the user interface.