Single-cell-RNA-seq-of-the-CRISPR-engineered-endogenous-tauopathy-model
By onscRNA-seq data analysis workflow Step1: bash cellranger_mkfastq.sh This will generate fastq files. Step2: bash cellranger_count_submission.sh This will call another bash file “cellranger_count.sh” and generate count tables Step3: bash run_scrublet_multi.sh This will call “scrublet_multi.py” and generate scrublet results. If seeing error refer to “scrublet_multi_conditional.py”. Step4: bash scRNA_seq.sh This will call “seurat_individual.R” and generate QC plots for each sample. Step5: Run Rscript hassan_merged_seurat.r -l expectedCells/ -s scrublet/ -k outdir/ -j hassan2022 -r refdir path_to_ref_directory This will generate Seurat results. Step6: Proceed with the trajectory and the fly phone DB analysis, using their respective code, on the integrated Seurat object. Step7: pySCENIC Step8: OmicsIntegrator
Code for extracting FSCV spikes
By onCode for extracting FSCV spikes used in Amjad et al. 2024 10.1523/ENEURO.0001-24.2024.
Code for simulating FSCV artifacts
By onCode for simulating FSCV artifacts for algorithm validation in Amjad et al. 2024 10.1523/ENEURO.0001-24.2024
Automated spike sorter utilizing the super paramagnetic clustering algorithm.
By onTomSort is an automated spike sorter utilizing the superparamagnetic clustering (SPC) algorithm.
analysis codes related to “Disruption of lysosomal proteolysis in astrocytes facilitates midbrain organoid proteostasis failure in an early-onset Parkinson’s disease model”
By onAnalysis codes related to "Disruption of lysosomal proteolysis in astrocytes facilitates midbrain organoid proteostasis failure in an early-onset Parkinson’s disease model."
Code for Tang et al 2024
By onCode for Tang et al 2024 (https://doi.org/10.1038/s41586-023-06941-5) - https://doi.org/10.5281/zenodo.10146089
Refinement of efficient encodings of movement in the dorsolateral striatum throughout learning (CODE)
By onCustom MATLAB code was used to perform all the analyses contained within the research publication, "Refinement of efficient encodings of movement in the dorsolateral striatum throughout learning" by Jaidar and Albarran et al., 2024.
SNCA transcript diversity in neurons
By onThis repository contains the code used to generate the plots used in the SNCA transcript expression and ASO modulation manuscript.
LR Project
By onThe LR project aims to study ligands and receptors in cross-disease risk. To reproduce findings, access public datasets and databases listed in KRT.txt. Use provided libraries and run scripts sequentially from 00 to 08 for plots and results.
LR Project, Python code
By onThe LR project investigates ligands and receptors in cross-disease risk. Access public datasets listed in resources/KRT.txt. Use libraries and scripts in order (00 to 08) to reproduce findings. Custom library "mellon" available in the repository.
LR project, R code
By onThe LR project explores ligands and receptors in cross-disease risk. Access public datasets listed in resources/KRT.txt. Use provided libraries and scripts in order (00 to 08) to reproduce results and plots.
cameraCalibrationCMOS
By onCamera calibration in MATLAB helps convert pixel values to photoelectrons or photons for accurate image comparisons. Regular calibration is recommended due to gain drift in EMCCD cameras.
Astrocyte Editing
By onAnalysis code for studying astrocytes, neurons, and astro-neuronal co-cultures' response to alpha-synuclein oligomers is split between two repositories: on RNA sequencing, the other examines RNA editing in cell models and post-mortem brain samples.
FIJI Syn_Bot Macro
By onA macro that counts colocalized synaptic puncta in microscopy images. Analysis involves noise reduction, thresholding, puncta counting, and colocalization calculation.
egustavsson / GBA_GBAP1_manuscript
By onCode used to generate the plots used in manuscript, "The annotation of GBA1 has been concealed by its protein-coding pseudogene GBAP1" (DOI: 10.1126/sciadv.adk1296).
CNV calling pipeline for low coverage single-cell whole genome sequencing data
By onPipeline for analyzing single-cell WGS data amplified with PicoPLEX, PTA, or droplet MDA includes steps for CNV analysis, filtering, and comparison.
scNAT Data for “scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles”
By onThe publication introduces scNAT, a deep learning method that integrates single-cell RNA and T cell receptor sequencing data for improved analysis of immune cell populations.
Scripts for snRNAseq data analysis
By onScripts for analyzing single nuclei sequencing data from healthy and Parkinson's Disease brains include creating a reference database with transposable element annotations and a file for Cell Ranger to produce snRNA count matrices.
Code for analysis of smell test dataset included in: Development of a Simplified Smell Test to Identify Patients with Typical Parkinson’s as Informed by Multiple Cohorts, Machine Learning and External Validation
By onCode used for the analysis of smell test performance as reported in "Development of a Simplified Smell Test to Identify Patients with Typical Parkinson’s as Informed by Multiple Cohorts, Machine Learning and External Validation", Li et al., 2024
Code for clinical dataset analysis included in: Persistent Hyposmia as Surrogate for α-Synuclein-Linked Brain Pathology
By onCode used for the analysis of clinical data as reported in the study "Persistent Hyposmia as Surrogate for α-Synuclein-Linked Brain Pathology" in Mollenhauer, Li et al., MedRxiv 2023
