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Catalog
ASAP is committed to accelerating the pace of discovery and informing a path to a cure for Parkinson’s disease through collaboration, research-enabling resources, and data sharing. We’ve created this catalog to showcase the research outputs and tools developed by ASAP-funded programs.
Article
Response to: “Is Gauchian genotyping of GBA1 variants reliable?”
Preprint: To understand the cause of these discrepancies, the team reviewed their data, and concluded that they are misinterpreting Gauchian results in 8 of the 11 discrepant samples, and incorrectly using Gauchian to analyze low-coverage 1kGP samples.
Article
Sex distribution of GBA1 variant carriers with dementia with Lewy Bodies and Parkinson’s disease
Sex distribution of GBA1 variant carriers with dementia with Lewy Bodies and Parkinson’s disease.
Protocol
Section 1: Enzymatic DNA Fragmentation (Manually)
This protocol details manual enzymatic DNA Fragmentation prior to Section 2: NGS library preparation for sequencing.
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Protocol
Manual isolation of nuclei from human brain using CellRaft device and single nucleus Whole Genome Amplification
Protocol for manual nuclear isolation from human brain tissue using Cell Raft device for single cell Whole Genome Amplification Protocol for manual nuclear isolation from human brain tissue using Cell Raft device for single cell Whole Genome Amplification
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Protocol
Nova-ST Spatial Transcriptomics protocol
Nova-ST is an open-source, high-resolution sequencing-based spatial transcriptomics workflow. This method gives comparable resolution to BGI Stereoseq, SeqScope & PIXEL seq. Nova-ST is derived from dense nano-patterned randomly barcoded Illumina NovaSeq 6000 S4 sequencing flow cells.
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Protocol
HyDrop Bead Generation & PCR Barcoding v1.0
Protocol for producing dissolvable barcoded hydrogel beads used in HyDrop experiments.
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Protocol
Microfluidic Chip Production v1.1 V.2
Protocol for producing microfluidic chips used in HyDrop experiment.
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Protocol
HyDrop-RNA v1.0
Step-by-step protocol for performing HyDrop-RNA. The duration of each step assumes an experienced protocol user. For a first-time user, we recommend doubling the expected time for each step.
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Code
Probedesign pipeline for the inhouse generation of seqFISH probes
The probe design pipeline works by inputting the transcript id’s for which probes have to be designed. Additional probe design parameters such as GC% or melting temperature can be changed via the config file. The pipeline will output the designed probes in fasta format and a csv file with the results of all filtering steps.
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Article
Detection of mosaic and population-level structural variants with Sniffles2
Published: The authors developed Sniffles2, a faster and more accurate method to analyze long-ready structural variation calling. This method also solves the problem of family to population-level SV calling to produce fully genotyped VCF files. View original preprint.
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Article
Multiple genome alignment in the telomere-to-telomere assembly era
Published: This review provides an overview of the algorithmic template that most multiple genome alignment methods follow. We also discuss prospective areas of improvement of multiple genome alignment for keeping up with continuously arriving high-quality T2T assembled genomes and for unlocking clinically-relevant insights.
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Article
More of less: novel multi-ome profiling of single human neurons
Review: Epigenetic modifications to DNA and chromatin interact to influence gene expression and cellular phenotypes, but defining these omics layers in complex tissues is a daunting task. In this issue of Cell Genomics, Luo et al. describe a novel single-cell multi-omic method, simultaneously profiling transcriptome, DNA methylome, and chromatin accessibility, to shed light on human neurons.
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Article
HyDrop: droplet-based scATAC-seq and scRNA-seq using dissolvable hydrogel beads. Article
Published: The data available in this repository can be used to replicate all the figures in the authors’ manuscript using their data analysis tutorial available here: https://github.com/aertslab/hydrop_data_analysis.
View original preprint.
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