I'm working on an RNASeq batch of data and I'm interested in discriminating gene isoforms. I performed the analysis using the classic tuxedo suite bowtie+tophat+cufflinks. I've seen many papers using alternate pipelines such as Alexa-Seq or RNASeqV2 in order to process this type of data.
I wonder if someone more experienced could briefly point out what are the main advantages/disadvantages of these alternative approaches.
Thanks.
Hi Marco,
A nice overview how all these tools for gene/transcript expression ptofilling work can be found here:
http://arxiv.org/PS_cache/arxiv/pdf/1104/1104.3889v2.pdf
Althought it is already a few years old it can give you the theoretical overview.
I would just maybe add to the list mentioned by Lior one more position:
http://bioinformatics.oxfordjournals.org/content/28/13/1721.short
Within a few weeks there should apear online a Naure Biotech paper from a SEQC consortium (I am one of the leading authors; manuscript has just been accepted) about cross-site and cross-platform RNA-seq study, which also compares different RNA-seq piplelines.
Once we will get pre-prints can send a copy to you.
Best wishes,
Paweł
Hi Marco,
A nice overview how all these tools for gene/transcript expression ptofilling work can be found here:
http://arxiv.org/PS_cache/arxiv/pdf/1104/1104.3889v2.pdf
Althought it is already a few years old it can give you the theoretical overview.
I would just maybe add to the list mentioned by Lior one more position:
http://bioinformatics.oxfordjournals.org/content/28/13/1721.short
Within a few weeks there should apear online a Naure Biotech paper from a SEQC consortium (I am one of the leading authors; manuscript has just been accepted) about cross-site and cross-platform RNA-seq study, which also compares different RNA-seq piplelines.
Once we will get pre-prints can send a copy to you.
Best wishes,
Paweł
Thank you very much for you answer,
I had a look at many reviews in the last week and things are becoming more clear to me.
A copy of your paper would be really highly appreciated!
Thanks,
Marco
Since I received private messages asking further information on RNASeqV2, this is TCGA pipeline for generating Level3 RnaSeqV2 data (from cghub)
https://www.cghub.ucsc.edu/docs/tcga/UNC_mRNAseq_summary.pdf
Steps: (Mapslice+RSEM)
1. Format fastq1+fastq2 (paired ends) for Mapsplice
2. Mapsplice
3. Add read groups
4. Convert back to phred33
5. Sort by coordinate (samtools)
6. Flagstat (samtools)
7. Indexing (samtools)
8. Sort by chromosome, then read id
9. Translate to transcriptome coords
10. Filter indels, large inserts, zero mapping quality from transcriptome bam
11. RSEM
12. Strip trailing tabs from rsem.isoforms.results
13. Prune isoforms from gene quant file
14. Normalize gene quant
15. Normalize isoform quant
16. Junction counts
17. Exon counts
18. Cleanup large intermediate output
- Badges
- Science topic
- Similar topics
- Computer Science and Engineering
- Bioinformatics