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.
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.
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.
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.
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.
CellLevel_QC: Extracting cell level QC metrics from CellRanger barcoded bams
By onJava code in this repository retrieves cell level mapping data (intronic reads, intergenic reads, multimapped reads, etc) from CellRanger output. Compatible with CellRanger v5 and v6, may work with newer versions and Spaceranger output.
scASE_py: Python pacakge for loading single cell allele specific data
By onPython package for single cell allele-specific expression (ASE) output manipulation available at https://github.com/seanken/ASE_pipeline. R package for downstream analysis at https://github.com/seanken/scAlleleExpression.
Single cell allele specific expression processing pipeline for long read data
By onPipeline processes long read single cell/nucleus 10X data (ONT, PacBio, MAS-Seq) to generate gene/isoform-level allele-specific expression (ASE) counts.
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 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
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
Nextflow pipeline for Nanopore WGS analysis
By onNextflow pipeline to process whole genome long-read sequencing data generated in the context of ASAP project.
CREsted (Cis-Regulatory Element Sequence Training, Explanation and Design): a deep learning package for training enhancer models on single-cell ATAC sequencing (scATAC-seq) data
By onCREsted offers detailed analyses and tutorials for studying enhancer codes and creating synthetic enhancer sequences at cell type-specific, nucleotide-level resolution.
HA_Skeleton_Analysis
By onThis script assesses the complexity of extracellular matrix network through a skeleton analysis
Directionality_GMX
By onThis script calculates a directionality index to assess the randomness of cell movement
Analyses of metabolite profiling of Drosophila Parkinson’s Disease model for identifying novel glial-based therapeutic targets
By onGenetic screening and metabolomics show glial adenosine metabolism as a potential treatment for Parkinson’s disease. Analysis includes measuring metabolite levels in synuclein expressing/control fly brains with different methods.
