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commands for windows
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6. all_steps_wynton.sh (shell script for running all the analysis steps on UCSF Wynton command-line interface using the practice data provided)
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7. steps_on_wynton_part1.txt (text file with steps used on wynton to setup the folders, upload the data and create a singularity container)
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8. steps_on_wynton_part2.txt (text file with steps used on wynton to run the bulk RNA-seq analysis using the demo files)
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9. all_steps_docker_desktop.sh (shell script with commands for running all the analysis steps using Docker Desktop and the demo files)
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9. all_steps_docker_desktop_mac.sh (commands for running all the analysis steps using Docker Desktop and the demo files on MacOS)
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10. all_steps_docker_desktop_windows.sh (commands for running all the analysis steps using Docker Desktop and the demo files on Windows)
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intro-rna-seq/all_steps_docker_desktop_mac.sh
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intro-rna-seq/all_steps_docker_desktop_mac.sh
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#!/bin/bash
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# This script should be run on your local laptop or computer
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# Please make sure you have installed Docker Desktop using the instructions at: https://www.docker.com/products/docker-desktop/
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# Before running this script, do the following
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## 1. open the Docker Dekstop and make sure it is running
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## 2. Download the workshop materials at https://github.com/gladstone-institutes/Bioinformatics-Workshops/raw/master/intro-rna-seq/Intro_to_RNA-seq_data_analysis.zip?raw=true.
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## 3. Unzip the workshop materials in the Downloads folder
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## 4. Open a new terminal window
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#check if docker is running
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#the below command will print out the docker version if docker is running
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docker --version
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#get the docker image from https://hub.docker.com/r/nfcore/rnaseq/
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#we will be using this image for all the analyses
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docker pull nfcore/rnaseq
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#check if the docker image was downloaded successfully
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docker images
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#spin up a docker container
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#change the path below to the path on your computer where the downloaded materials are unzipped
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##for M1 chip mac, use the below command
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docker run --platform linux/amd64 --name rna_bash --rm -it -v ~/Downloads/Intro_to_RNA-seq_data_analysis:/home nfcore/rnaseq bash
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##for all other computers, use the below command
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docker run --name rna_bash --rm -it -v ~/Downloads/Intro_to_RNA-seq_data_analysis:/home nfcore/rnaseq bash
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#a new prompt will apear and the conatiner is now active
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#the home directory should have all the contents of the downloaded materials folder
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#go to the home directory in the docker container
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cd home
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#run fastqc
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fastqc Bacteria_GATTACA_L001_R1_001.fastq
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#trim the reads using cutadapt
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cutadapt -a file:Adapter_Sequence.fasta -o trimmed.fastq Bacteria_GATTACA_L001_R1_001.fastq
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#run fastqc on the trimmed reads
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fastqc trimmed.fastq
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#create a new folder
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mkdir star_index
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#create the STAR index
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STAR --runMode genomeGenerate --genomeDir ./star_index --genomeFastaFiles rDNA_sequence.fasta --genomeSAindexNbases 3
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#run STAR for the trimmed reads
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STAR --genomeDir ./star_index --readFilesIn ./trimmed.fastq
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#generate the read count matrix using featureCounts
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featureCounts -a rDNA.gtf -t CDS -o counts.txt Aligned.out.sam
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# END #
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intro-rna-seq/all_steps_docker_desktop_windows.sh
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intro-rna-seq/all_steps_docker_desktop_windows.sh
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#!/bin/bash
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# This script should be run on your local laptop or computer
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# Please make sure you have installed Docker Desktop using the instructions at: https://www.docker.com/products/docker-desktop/
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# Before running this script, do the following
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## 1. open the Docker Dekstop and make sure it is running
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## If Docker Desktop gives a pop-up that it requires a newer WSL kernel version, open a new command prompt window and run the below command:
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## $ wsl --update
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## Restart Docker Desktop
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## 2. Download the workshop materials at https://github.com/gladstone-institutes/Bioinformatics-Workshops/raw/master/intro-rna-seq/Intro_to_RNA-seq_data_analysis.zip?raw=true.
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## 3. Unzip the workshop materials in the Downloads folder
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## 4. Open a new command prompt window
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##run the below commands in the command prompt window
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#check if docker is running
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#the below command will print out the docker version if docker is running
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docker --version
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#get the docker image from https://hub.docker.com/r/nfcore/rnaseq/
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#we will be using this image for all the analyses
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docker pull nfcore/rnaseq
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#check if the docker image was downloaded successfully
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docker images
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#spin up a docker container
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#change the path below to the path on your computer where the downloaded materials are unzipped
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docker run --name rna_bash --rm -it -v C:\Users\ayushi.agrawal\Downloads\Intro_to_RNA-seq_data_analysis\Intro_to_RNA-seq_data_analysis:/home nfcore/rnaseq bash
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#a new prompt will apear and the conatiner is now active
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#the home directory should have all the contents of the downloaded materials folder
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#go to the home directory in the docker container
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cd home
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#run fastqc
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fastqc Bacteria_GATTACA_L001_R1_001.fastq
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#trim the reads using cutadapt
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cutadapt -a file:Adapter_Sequence.fasta -o trimmed.fastq Bacteria_GATTACA_L001_R1_001.fastq
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#run fastqc on the trimmed reads
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fastqc trimmed.fastq
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#STAR does not work on windows so, we will be using another aligner "HISAT2" for the demo
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#create a new folder
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mkdir hisat2_index
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#create the hisat2 index
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hisat2-build -p 7 rDNA_sequence.fasta hisat2_index/rDNA_
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#run hisat2 for the trimmed reads
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#HISAT2 and STAR are different aligners with different defaults, scoring algorithms, etc. This might result in different outputs from the two aligners.
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hisat2 -p 7 -x hisat2_index/rDNA_ -U ./trimmed.fastq -S hisat2_aligned_out.sam
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#generate the read count matrix using featureCounts
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featureCounts -a rDNA.gtf -t CDS -o counts.txt hisat2_aligned_out.sam
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# END #
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