Welcome to the
spatialLIBD project! It is composed of:
This web application allows you to browse the LIBD human dorsolateral pre-frontal cortex (DLPFC) spatial transcriptomics data generated with the 10x Genomics Visium platform. Through the R/Bioconductor package you can also download the data as well as visualize your own datasets using this web application. Please check the bioRxiv pre-print for more details about this project.
As a quick overview, the data presented here is from portion of the DLPFC that spans six neuronal layers plus white matter (A) for a total of three subjects with two pairs of spatially adjacent replicates (B). Each dissection of DLPFC was designed to span all six layers plus white matter (C). Using this web application you can explore the expression of known genes such as SNAP25 (D, a neuronal gene), MOBP (E, an oligodendrocyte gene), and known layer markers from mouse studies such as PCP4 (F, a known layer 5 marker gene).
This web application was built such that we could annotate the spots to layers as you can see under the spot-level data tab. Once we annotated each spot to a layer, we compressed the information by a pseudo-bulking approach into layer-level data. We then analyzed the expression through a set of models whose results you can also explore through this web application. Finally, you can upload your own gene sets of interest as well as layer enrichment statistics and compare them with our LIBD Human DLPFC Visium dataset.
If you are interested in running this web application locally, you can
do so thanks to the
spatialLIBD R/Bioconductor package that powers
this web application as shown below.
## Run this web application locally spatialLIBD::run_app() ## You will have more control about the length of the ## session and memory usage. ## You could also use this function to visualize your ## own data given some requirements described ## in detail in the package vignette documentation ## at http://research.libd.org/spatialLIBD/.
spatialLIBD package contains functions for:
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("spatialLIBD")
spatialLIBD package you can access the processed data in
it’s final R format. However, we also provide a table of links so you
can download the raw data we received from 10x Genomics.
spatialLIBD you can access the Human DLPFC spatial
transcriptomics data from the 10x Genomics Visium platform. For example,
this is the code you can use to access the layer-level data. For more
details, check the help file for
## Load the package library('spatialLIBD') ## Download the spot-level data sce <- fetch_data(type = 'sce') #> Loading objects: #> sce ## This is a SingleCellExperiment object sce #> class: SingleCellExperiment #> dim: 33538 47681 #> metadata(1): image #> assays(2): counts logcounts #> rownames(33538): ENSG00000243485 ENSG00000237613 ... ENSG00000277475 #> ENSG00000268674 #> rowData names(9): source type ... gene_search is_top_hvg #> colnames(47681): AAACAACGAATAGTTC-1 AAACAAGTATCTCCCA-1 ... #> TTGTTTCCATACAACT-1 TTGTTTGTGTAAATTC-1 #> colData names(73): barcode sample_name ... pseudobulk_UMAP_spatial #> markers_UMAP_spatial #> reducedDimNames(6): PCA TSNE_perplexity50 ... TSNE_perplexity80 #> UMAP_neighbors15 #> spikeNames(0): #> altExpNames(0): ## Note the memory size pryr::object_size(sce) #> 2.08 GB ## Remake the logo image with histology information sce_image_clus( sce = sce, clustervar = 'layer_guess_reordered', sampleid = '151673', colors = libd_layer_colors, ... = ' DLPFC Human Brain Layers\nMade with github.com/LieberInstitute/spatialLIBD' )
Below you can find the links to the raw data we received from 10x Genomics.
Below is the citation output from using
citation('spatialLIBD') in R.
Please run this yourself to check for any updates on how to cite
citation('spatialLIBD') #> #> Collado-Torres L, Maynard KR, Jaffe AE (2020). _LIBD Visium spatial #> transcriptomics human pilot data inspector_. doi: #> 10.18129/B9.bioc.spatialLIBD (URL: #> https://doi.org/10.18129/B9.bioc.spatialLIBD), #> https://github.com/LieberInstitute/spatialLIBD - R package version #> 0.99.5, <URL: http://www.bioconductor.org/packages/spatialLIBD>. #> #> Maynard KR, Collado-Torres L, Weber LM, Uytingco C, Williams SR, II #> JLC, Barry BK, Tran MN, Besich Z, Tippani M, Chew J, Yin Y, Hyde TM, #> Rao N, Hicks SC, Martinowich K, Jaffe AE (2020). "Transcriptome-scale #> spatial gene expression in the human dorsolateral prefrontal cortex." #> _bioRxiv_. doi: 10.1101/xxxyyy (URL: https://doi.org/10.1101/xxxyyy), #> <URL: https://doi.org/10.1101/xxxyyy>. #> #> To see these entries in BibTeX format, use 'print(<citation>, #> bibtex=TRUE)', 'toBibtex(.)', or set #> 'options(citation.bibtex.max=999)'.
Please note that the
spatialLIBD was only made possible thanks to many
other R and bioinformatics software authors. We have cited their work
either in the pre-print or the vignette of the R package.