Preferential Subspace Identification Algorithm

Preferential Subspace Identification Algorithm

Spatial-eXpression-R: Cell type identification (including cell type mixtures) and cell type-specific differential expression for spatial transcriptomics

Significance analysis for clustering single-cell RNA-sequencing data

Collaboration between Costa, Martinowich, and Hicks labs investigating basolateral amygdala cell-types across huamn and non-human primate species.

Spatially-aware quality control for spatial transcriptomics

Learning about Docker.

A curated list of Quarto talks, tools, examples & articles! Contributions welcome!

NEural MOdelS, a statistical modeling framework for neuroscience.

Cell type prioritization in single-cell data

R Package: Regularized Principal Component Analysis for Spatial Data

Neyman-Scott point process model to identify sequential firing patterns in high-dimensional spike trains

Methods to discover gene programs on single-cell data

Helper Functions for LIBD Deconvolution

Analyze neuroscience data in the cloud

Systems Neuroscience Computing in Python: user-friendly analysis of large-scale electrophysiology data

Gene ontology terms to compare single cell RNA-seq data

Library to perform Slice Tensor Component Analysis (sliceTCA)

Evolutionary Scale Modeling (esm): Pretrained language models for proteins

Public facing deeplift repo

Single-cell analysis with non-negative matrix factorization

A very simple and barebones tensor decomposition library for CP decomposition a.k.a. PARAFAC a.k.a. TCA

NMF and complete deconvolution algorithm

R package to quantify and remove cell free mRNAs from droplet based scRNA-seq data

Slides giving an overview of NIU's behavioural analysis projects.