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      Advanced Single Cell RNA-Seq Workshop

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Introduction and Lectures
Intro to the Workshop and Core
Schedule
What is Bioinformatics/Genomics?
Experimental Design and Cost Estimation
Single Cell Sample Preparation - Dr. Diana Burkart-Waco
Support
Cheat Sheets
Software and Links
Scripts
Prerequisites
CLI - Logging in and Transferring Files
CLI - Intro to Command-Line
CLI - Advanced Command-Line (extra)
CLI - Running jobs on the Cluster and using modules
R - Getting Started
R - Intro to R
R - Prepare Data in R (extra)
R - Data in R (extra)
More Materials (extra)
Data Reduction
Generating Expression Matrices
Expression project setup
Preprocessing reads with HTStream
Generating Expression Tables
VDJ T cell and B cell
Velocity analysis
Data analysis
scRNA analysis prepare
Mapping Comparison
Anchoring (Comparison dataset)
Shiny App Install/Overview
App Practical Usage
AWS Hosted App (Optional)
Monocle
VDJ T cell and B cell analysis
Velocity analysis
ETC
Closing thoughts
Workshop Photos
Github page
Biocore website

Login to tadpole and navigate to your directory on the share space.

cd /share/workshop/adv_scrna/$USER

srun -t 1-00:00:00 -c 4 -n 1 --mem 16000 --partition production --account adv_scrna_workshop --reservation adv_scrna_workshop  --pty /bin/bash

Immune profiling V(D)J T Cell and B Cell analysis with 10X

Human samples and mouse strains of types C57BL/6 and BALB/c have been tested within the 10X genomics system. If you use another mouse strain or different organism, then you need to create your own primers and reference sequence.

V(D)J

The V(D)J Algorithm

First V(D)J read-pairs aligned to an assembled contig, illustrating the structure of the read data. One to many UMIs are captured for each V(D)J chain. A round of enrichment PCR targeting the 5′ end to the C-region, followed by enzymatic fragmentation results in a pool of molecules originating from the same transcript. The molecules carry the same 10x barcode and UMI sequences, but with different insert lengths, resulting in different R2 start points. The diversity of R2 start points gives complete coverage of the targeted portion of each transcript, which is typically ~650bp.

Recommended sequencing depth is ~5,000 reads per cell.

Test dataset

The dataset we’ll be using is from the 10X website. Specifically we’ll be using the PBMCs from BALB/c mice dataset.

cd /share/workshop/adv_scrna/$USER/scrnaseq_processing
mkdir cd /share/workshop/adv_scrna/$USER/scrnaseq_processing/cellranger_vdj
cd /share/workshop/adv_scrna/$USER/scrnaseq_processing/cellranger_vdj
ln -s /share/biocore/workshops/2020_scRNAseq/VDJ/VDJ_output 00-RawData

Lets buld a reference for Mouse based on Ensembl release-100 VDJ entries

First lets setup a References folder for our experiment.

mkdir -p /share/workshop/adv_scrna/$USER/scrnaseq_processing/reference
cd /share/workshop/adv_scrna/$USER/scrnaseq_processing/reference

We should already have the needed genome and gtf file for Mouse Ensembl version 100

10X Genomics - cellranger vdj

Description of cellranger vdj can be found here

Building indexes for cellranger vdj (takes a long time)

10X Genomics provides pre-built references for human and mouse vdj regions to use with Cell Ranger. Researchers can make custom references for additional species or add custom vdj sequences of interest to the reference. The following tutorial outlines the steps to build a custom vdj reference using the cellranger mkvdjref pipeline and an ensembl genome.

You should already have the Ensembl 100 Mouse genome and GTF file in the reference folder, however if you don’t, you can copy then from here.

cd /share/workshop/adv_scrna/$USER/scrnaseq_processing/reference
ln -s /share/biocore/workshops/2020_scRNAseq/Reference/Mus_musculus.GRCm38.dna.primary_assembly.fa .
ln -s /share/biocore/workshops/2020_scRNAseq/Reference/Mus_musculus.GRCm38.100.gtf .

Running cellranger mkvdjref

cd /share/workshop/adv_scrna/$USER/scrnaseq_processing/reference

module load cellranger/3.1.0

cellranger mkvdjref \
   --genome=GRCm38.cellranger_vdj \
   --fasta=Mus_musculus.GRCm38.dna.primary_assembly.fa \
   --genes=Mus_musculus.GRCm38.100.filtered.gtf \
   --ref-version=3.1.0

This assumes that the following biotypes are present in the gtf files

You can also generate vdj references for IMGT sequences. Additional instructions for building VDJ references can be found here

Running the V(D)J piepline

cd /share/workshop/adv_scrna/$USER/scrnaseq_processing/cellranger_vdj
cellranger vdj \
    --id=vdj_v1_mm_balbc_pbmc_b_sm \
    --fastqs=00-RawData \
    --sample=vdj_v1_mm_balbc_pbmc_b_sm \
    --reference=../reference/GRCm38.cellranger_vdj

The V(D)J pipeline outputs alot of files

the output contains