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Reference Genome

#1-ii. Reference Genomes
Obtain a reference genome from iGenomes. In this example analysis we will use the human GRCh38 version of the genome. Furthermore, we are actually going to perform the analysis using only a single chromosome (chr22) and the ERCC spike-in to make it run faster...
Create the necessary working directory
cd $RNA_HOME
export REF_BASE=/home/ubuntu/workspace/data/fasta/GRCh38/chr22_with_ERCC92
export REF_FASTA=${REF_BASE}.fa
echo $REF_FASTA
The complete data from which these files were obtained can be found at: ftp://ftp.ensembl.org/pub/release-85/fasta/homo_sapiens/dna/. You could use wget to download the Homo_sapiens.GRCh38.dna_sm.primary_assembly.fa.gz file, then unzip/untar.
This has been done for you and that data placed on your AWS instance. It contains chr22 and ERCC transcript fasta files in both a single combined file and individual files.
cd /home/ubuntu/workspace/data//fasta/GRCh38/
ls
View the first 10 lines of this file
head $REF_FASTA
How many lines and characters are in this file?
wc $REF_FASTA
View 10 lines from approximately the middle of this file
head -n 425000 $REF_FASTA | tail
Note: Instead of the above, you might consider getting reference genomes and associated annotations from UCSC. e.g., http://hgdownload.cse.ucsc.edu/goldenPath/hg19/chromosomes/. Wherever you get them from, the names of your reference sequences (chromosomes) must those matched in your annotation gtf files (described in the next section).
| Previous Section | This Section | Next Section | |:---------------------------------:|:--------------------------------------:|:---------------------------:| | Installation | Reference Genomes | Annotations |
NOTICE: This resource has been moved to rnabio.org. The version here will be maintained for legacy use only. All future development and maintenance will occur only at rnabio.org. Please proceed to rnabio.org for the current version of this course.
Table of Contents
Module 0: Authors | Citation | Syntax | Intro to AWS | Log into AWS | Unix | Environment | Resources
Module 1: Installation | Reference Genomes | Annotations | Indexing | Data | Data QC
Module 2: Adapter Trim | Alignment | IGV | Alignment Visualization | Alignment QC
Module 3: Expression | Differential Expression | DE Visualization
Module 4: Alignment Free - Kallisto
Module 5: Ref Guided | De novo | Merging | Differential Splicing | Splicing Visualization
Module 6: Trinity
Module 7: Trinotate
Appendix: Saving Results | Abbreviations | Lectures | Practical Exercise Solutions | Integrated Assignment | Proposed Improvements | AWS Setup