This is a protocol preprint. Preprints are preliminary reports that have not undergone peer review. They should not be considered conclusive, used to inform clinical practice, or referenced by the media as validated information.
Method Article
Alternative splicing analysis of RNA-seq data using SAJR
Thomas Doktor
Andresen's lab, University of Southern Denmark
Corresponding Author
License:
This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License
Here we describe a fast an efficient protocol for analyzing alternative splicing using SAJR.
Keywords
RNA-seq, alternative splicing
Here we describe a fast an efficient protocol for analyzing alternative splicing using ‘cutadapt’ [1] to trim reads before alignment with ‘STAR’ [2], subsequent merging of samples using ‘samtools’ [3] and finally analysis of splicing with ‘SAJR’ [4]. We also added annotation of novel splicing events and conversion of SAJR specific ids to standard gene ids using ‘bedtools’ [5] and custom perl scripts.
First part of the protocol is preparing and mapping reads.
- Trim reads to remove adapter sequences. Example using ‘cutadapt’ and Nextera adapters: cutadapt --trim-n -m 15 -o trimmed.S1_1.fastq.gz -p trimmed.S1_2.fastq.gz -a CTGTCTCTTATACACATCTCCGAGCCCACGAGA -A CTGTCTCTTATACACATCTGACGCTGCCGACGA S1_1.fastq.gz S1_2.fastq.gz
Align the samples to the genome using ‘STAR.’
Merge all BAM files into a single BAM file using ‘samtools merge’.
Second part of the protocol is preparing a reference as well as identifying novel splicing patterns and annotating these.
Convert a GTF reference to an SAJR specific GFF reference using SAJR’s annotation conversion mode.
Run SAJR in de novo annotation mode to find novel splice-forms using the merged BAM file and the known annotation to produce a novel annotation, novel.gff
- Run SAJR in annotation comparison mode to compare the novel annotation with the known annotation and use get_genename_from_junction_comparison.pl to filter the results: get_genename_from_junction_comparison.pl sajr.comp > sajr.novel2known.tsv
- Use bedtools and get_genename_from_segment_overlap.pl to associate SAJR ids with known gene ids from the reference: bedtools intersect -s -f 1.0 -loj -a novel.gff -b known.gff > novel_overlap_known.gff
get_genename_from_segment_overlap.pl novel_overlap_known.gff > novel2known_from_overlap.tsv
- Use bedtools and annotate_novel_segments.pl to annotate novel spliced regions: bedtools intersect -s -f 1.0 -r -loj -a novel.gff -b known.gff > novel_overlap_known_stringent.gff
annotate_novel_segments.pl novel_overlap_known_stringent.gff > novel_overlap_known_stringent_novel.tsv
The final part of the protocol is estimating inclusion levels in each sample, and testing for differences between groups of samples.
Run SAJR in count mode for each sample using the novel.gff reference.
- Use the R package part of SAJR to identify alternative splicing, see sajr_analysis.R for an example workflow incorporating annotation of novel spliced regions.
The whole analysis can be completed within 24 hours for 36 samples with a total of app. 450 mio reads running on 16 cores.
The expected outcome is a list of significant alternative splicing events with with optional indication of novel splicing patterns.
1 Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. 2011 17, doi:10.14806/ej.17.1.200
pp. 10-12 (2011).
2 Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15-21, doi:10.1093/bioinformatics/bts635 (2013).
3 Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078-2079, doi:10.1093/bioinformatics/btp352 (2009).
4 Mazin, P. et al. Widespread splicing changes in human brain development and aging. Molecular systems biology 9, 633, doi:10.1038/msb.2012.67 (2013).
5 Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841-842, doi:10.1093/bioinformatics/btq033 (2010).
This is a list of supplementary files associated with this preprint. Click to download.
- scripts.zip
Scripts Scripts Zip file containing perl scripts used in the protocol and example R script.
Version History
CURRENT STATUS: Posted
Version 1
Posted 12 Mar, 2018
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Subject Areas
Computational biology and bioinformatics
Associated Publications
Splicing factor 1 modulates dietary restriction and TORC1 pathway longevity in C. elegans
by Caroline Heintz, Thomas K. Doktor, Anne Lanjuin, +11
Nature (31 May, 2017)
Method Article
Alternative splicing analysis of RNA-seq data using SAJR
Thomas Doktor
Andresen's lab, University of Southern Denmark
Corresponding Author
Version History
CURRENT STATUS: Posted
Version 1
Posted 12 Mar, 2018
Metrics
Comments: 0
HTML Views: ...
Subject Areas
Computational biology and bioinformatics
License:
This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License
Here we describe a fast an efficient protocol for analyzing alternative splicing using SAJR.
Here we describe a fast an efficient protocol for analyzing alternative splicing using ‘cutadapt’ [1] to trim reads before alignment with ‘STAR’ [2], subsequent merging of samples using ‘samtools’ [3] and finally analysis of splicing with ‘SAJR’ [4]. We also added annotation of novel splicing events and conversion of SAJR specific ids to standard gene ids using ‘bedtools’ [5] and custom perl scripts.
First part of the protocol is preparing and mapping reads.
- Trim reads to remove adapter sequences. Example using ‘cutadapt’ and Nextera adapters: cutadapt --trim-n -m 15 -o trimmed.S1_1.fastq.gz -p trimmed.S1_2.fastq.gz -a CTGTCTCTTATACACATCTCCGAGCCCACGAGA -A CTGTCTCTTATACACATCTGACGCTGCCGACGA S1_1.fastq.gz S1_2.fastq.gz
Align the samples to the genome using ‘STAR.’
Merge all BAM files into a single BAM file using ‘samtools merge’.
Second part of the protocol is preparing a reference as well as identifying novel splicing patterns and annotating these.
Convert a GTF reference to an SAJR specific GFF reference using SAJR’s annotation conversion mode.
Run SAJR in de novo annotation mode to find novel splice-forms using the merged BAM file and the known annotation to produce a novel annotation, novel.gff
- Run SAJR in annotation comparison mode to compare the novel annotation with the known annotation and use get_genename_from_junction_comparison.pl to filter the results: get_genename_from_junction_comparison.pl sajr.comp > sajr.novel2known.tsv
- Use bedtools and get_genename_from_segment_overlap.pl to associate SAJR ids with known gene ids from the reference: bedtools intersect -s -f 1.0 -loj -a novel.gff -b known.gff > novel_overlap_known.gff
get_genename_from_segment_overlap.pl novel_overlap_known.gff > novel2known_from_overlap.tsv
- Use bedtools and annotate_novel_segments.pl to annotate novel spliced regions: bedtools intersect -s -f 1.0 -r -loj -a novel.gff -b known.gff > novel_overlap_known_stringent.gff
annotate_novel_segments.pl novel_overlap_known_stringent.gff > novel_overlap_known_stringent_novel.tsv
The final part of the protocol is estimating inclusion levels in each sample, and testing for differences between groups of samples.
Run SAJR in count mode for each sample using the novel.gff reference.
- Use the R package part of SAJR to identify alternative splicing, see sajr_analysis.R for an example workflow incorporating annotation of novel spliced regions.
The whole analysis can be completed within 24 hours for 36 samples with a total of app. 450 mio reads running on 16 cores.
The expected outcome is a list of significant alternative splicing events with with optional indication of novel splicing patterns.
1 Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. 2011 17, doi:10.14806/ej.17.1.200
pp. 10-12 (2011).
2 Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15-21, doi:10.1093/bioinformatics/bts635 (2013).
3 Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078-2079, doi:10.1093/bioinformatics/btp352 (2009).
4 Mazin, P. et al. Widespread splicing changes in human brain development and aging. Molecular systems biology 9, 633, doi:10.1038/msb.2012.67 (2013).
5 Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841-842, doi:10.1093/bioinformatics/btq033 (2010).
Associated Publications
Splicing factor 1 modulates dietary restriction and TORC1 pathway longevity in C. elegans
by Caroline Heintz, Thomas K. Doktor, Anne Lanjuin, +11
Nature (31 May, 2017)