To use the latest version on the web:
https://conradlab.shinyapps.io/HISTA/
The Human Infertility Single-cell Testis Atlas (HISTA): An interactive molecular scRNA-Seq reference of the human testis
Developed by Eisa Mahyari Ph.D. @eisamahyari
PI: Don F. Conrad Ph.D.
Oregon Health & Science University (OHSU)
Oregon National Primate Research Center (ONPRC)
Eisa Mahyari, Jingtao Guo, Ana C. Lima, Daniel P. Lewinsohn, Alexandra M. Stendahl, Katinka A. Vigh-Conrad, Xichen Nie, Liina Nagirnaja, Nicole B. Rockweiler, Douglas T.Carrell, James M.Hotaling, Kenneth I.Aston, Donald F.Conrad “Comparative single-cell analysis of biopsies clarifies pathogenic mechanisms in Klinefelter syndrome.” The American Journal of Human Genetics 108, no. 10 (2021): 1924-1945
The Human Infertility Single-cell Testis Atlas (HISTA) is an interactive web tool and a reference for navigating the transcriptome of the human testis. It was developed using joint analyses of scRNA-Seq datasets derived from a dozen donors, including healthy adult controls, juveniles, and several infertility cases. HISTA provides visualization and hypothesis testing tools using 23429 genes measured across 26093 cells. A central feature of HISTA is to combine structured dimensionality reduction with genomic annotation to fine-map cellular characteristics and discover genomic modules.
The testis is a complex reproductive tissue with unique microenvironments and cell types, that recently has been the focus of numerous single-cell transcriptomics (scRNA-Seq) studies to unravel both normal and pathological features1–7. Recently, we published our findings 1 with 26093 cells, derived from testis biopsies of 2 juveniles, 6 normal adults, 1 adult with azoospermia, 1 adult with ejaculatory dysfunction, and 2 adults with Klinefelter Syndrome (KS). To facilitate continued research and to give access and easy navigation of the testis transcriptomic data at the core of our work, we developed the Human Infertility Single-cell Testis Atlas (HISTA).
HISTA was initially used to identify molecular and cellular signatures that distinguished infertility in Klinefelter Syndrome (KS) in comparison to healthy controls as well as other forms of infertility such as non-obstructive azoospermia (NOA) and ejaculatory dysfunction
More recently, Nagirnaja, et al., utilized HISTA to identify molecular subforms of NOA. They observed differences in gene expression in patients with NOA who had different histological diagnoses (such as maturation arrest (MA), Sertoli cell only (SCO), or "unknown"). Using HISTA, they found that the gene signatures were different for patients with MA compared to those with SCO or "unknown" histology
You will need to download the rds file with the data once you install this code base.
https://zenodo.org/record/8206603
#### ---- In R use this script
# libraries
library(dplyr)
library(ggplot2)
library(data.table)
#this file is on the CoradLab/data folder, there may be an older version, the data is the same,
#new version is mostly related to HISTA versioning
SSls = readRDS("./inst/app/data/HISTAv1_dataLS_June2023.rds")
# select genes:
GeneSet_Set = c("BLM", "ATM", "BRCA2")
# GeneSet_Set = colnames(SSls$results$loadings[[1]][,]) # all genes
#select cells:
MyCells = rownames(SSls$datat) # all cells
#compute batch-removed DGE via dot product
GeneExpr <- SSls$results$scores[MyCells, ifelse( SSls$StatFac$Lab == "Removed", FALSE, TRUE)] %*% SSls$results$loadings[[1]][ifelse( SSls$StatFac$Lab == "Removed", FALSE, TRUE), GeneSet]
Mahyari, E. et al. Comparative single-cell analysis of biopsies clarifies pathogenic mechanisms in Klinefelter syndrome. Am. J. Hum. Genet. 108, 1924–1945 (2021).
Nagirnaja, L. et al. Diverse monogenic subforms of human spermatogenic failure. Nat. Commun. 13, 7953 (2022).
Hermann, B. P. et al. The Mammalian Spermatogenesis Single-Cell Transcriptome, from Spermatogonial Stem Cells to Spermatids. Cell Rep. 25, 1650–1667.e8 (2018).
Jung, M. et al. Unified single-cell analysis of testis gene regulation and pathology in five mouse strains. eLife vol. 8 Preprint at https://doi.org/10.7554/elife.43966 (2019).
Wells, D and Hore, V. (2017). SDAtools: SDAtools: A toolkit for SDA. R package version 1.0.
Hore, V. et al. Tensor decomposition for multiple-tissue gene expression experiments. Nat. Genet. 48, 1094–1100 (2016).
Winston Chang, Joe Cheng, JJ Allaire, Yihui Xie and Jonathan McPherson (2019). shiny: Web Application Framework for R. R package version 1.4.0. https://CRAN.R-project.org/package=shiny
Winston Chang and Barbara Borges Ribeiro (2018). shinydashboard: Create Dashboards with 'Shiny'. R package version 0.7.1. https://CRAN.R-project.org/package=shinydashboard
Mahyari, E. & Conrad, D. HISTA. (2021) doi:https://zenodo.org/badge/latestdoi/271643615
Conrad Lab: conradlab.org Packaged created by: @eisamahyari Package maintained by: @eisamahyari
Tested on R 3.6.3 and 4.0.3
devtools::install_github(repo = 'eisascience/HISTA', dependencies = T, upgrade = 'always')
HISTA::launchHISTA()