In vivo high-throughput screening of novel adeno-associated viral capsids identifies variants for transduction of adult neural stem cells within the subventricular zone

This repository contains all code and data that was generated as part of the study above by Kremer and Cerrizuela et al.

The manuscript is now published and available online at https://doi.org/10.1016/j.omtm.2021.07.001.

Part I: Screening of AAV serotypes with RNA sequencing

Data

Raw sequencing results:

The FASTQ files are deposited at GEO (accession GSE145172, AAV_library_1 and AAV_library_3).

Information about input libraries #1 and #3

The table 02_analysis/tables/input_library_info.csv lists the relative abundance of each AAV variant in the input library and the barcode that was assigned to each variant.

Results

All plots of barcode / serotype proportions are here:

02_analysis/plots/

All supplementary tables of barcode / serotype proportions are here:

02_analysis/tables/supplement/

Code

The code to count the barcodes in our FASTQ files is here:

01_counting-barcodes/AAV-lib1/Snakefile
01_counting-barcodes/AAV-lib3/Snakefile
These scripts can be run with Snakemake.

The R code for calculating normalized barcode proportions and for plotting is here:

02_analysis/Lib1-analysis.R
02_analysis/Lib3-analysis.R

Part II: Single cell RNA-seq of cells labeled with AAV1_P5

Data

Raw sequencing results:

The FASTQ files are deposited at GEO (accession GSE145172, single-cell RNA-seq_sample #1 and #2).

Our filtered single cell RNA-seq count matrix, including row- and column labels and metadata:

03_single-cell-RNA-seq/count_matrix/

Code + Results

The shell code used for read mapping and transcript quantification:

03_single-cell-RNA-seq/README.md

The Python code used to get from a raw unfiltered count matrix to our UMAP and clustering:

03_single-cell-RNA-seq/01_scRNA-seq-preprocessing.html (or view the raw Python code)

The R code used for the analyses depicted in Figures 3 and S4h-l, including these plots:

03_single-cell-RNA-seq/02_scRNA-seq-analysis.html (or view the raw R Markdown code)
If you want to view the HTML files above, please download them and open them in a web browser.

A table with the 18 differentially expressed genes:

03_single-cell-RNA-seq/differentially_expressed_genes.csv
These genes appear to be more lowly expressed in transduced cells compared to non-transduced cells.

jizhongzhong / aav-screening Goto Github PK

aav-screening's Introduction

In vivo high-throughput screening of novel adeno-associated viral capsids identifies variants for transduction of adult neural stem cells within the subventricular zone

Part I: Screening of AAV serotypes with RNA sequencing

Data

Raw sequencing results:

Information about input libraries #1 and #3

Results

All plots of barcode / serotype proportions are here:

All supplementary tables of barcode / serotype proportions are here:

Code

The code to count the barcodes in our FASTQ files is here:

The R code for calculating normalized barcode proportions and for plotting is here:

Part II: Single cell RNA-seq of cells labeled with AAV1_P5

Data

Raw sequencing results:

Our filtered single cell RNA-seq count matrix, including row- and column labels and metadata:

Code + Results

The shell code used for read mapping and transcript quantification:

The Python code used to get from a raw unfiltered count matrix to our UMAP and clustering:

The R code used for the analyses depicted in Figures 3 and S4h-l, including these plots:

A table with the 18 differentially expressed genes:

Recommend Projects

Recommend Topics

Recommend Org