Hello,
I would like to ask for your opinion regarding a reference transcriptome for mm9. My task is to search for "novel" transcripts in RNA-seq data aligned to mm9, so I am wondering what would be my best option to use as reference?
The latest Ensembl release for mm9 dates back to October 2011, whereas the RefseqGene track is the UCSC Genome Browser is still frequently updated. From both tracks I created gtf files with the genePredToGtf tool.
Suprisingly for me the ancient Ensembl release was much more comprehensive than its up to date RefseqGene counterpart:
This difference has had a great impact on the number of transcripts (in total and also "novel" ones), which I am amble to assemble based on the same alignment with StringTie or Cufflinks using the respective gtf files as reference.
What would be your approach/thoughts to/on this? Any help/suggestions/ideas welcome.
Best
Matthias
I would like to ask for your opinion regarding a reference transcriptome for mm9. My task is to search for "novel" transcripts in RNA-seq data aligned to mm9, so I am wondering what would be my best option to use as reference?
The latest Ensembl release for mm9 dates back to October 2011, whereas the RefseqGene track is the UCSC Genome Browser is still frequently updated. From both tracks I created gtf files with the genePredToGtf tool.
Suprisingly for me the ancient Ensembl release was much more comprehensive than its up to date RefseqGene counterpart:
- Ensembl67 vs. RefseqGene
gffcompare v0.10.1 | Command line was:
#gffcompare -R -A -r [...] -s
#= Summary for dataset: ../2011-10-12_Ensembl67.mm9.gtf
# Query mRNAs : 93727 in 36660 loci (80362 multi-exon transcripts)
# (14094 multi-transcript loci, ~2.6 transcripts per locus)
# Reference mRNAs : 35709 in 23009 loci (32141 multi-exon)
# Super-loci w/ reference transcripts: 21631
#-----------------| Sensitivity | Precision |
Base level: 95.1 | 70.8 |
Exon level: 95.5 | 65.9 |
Intron level: 97.2 | 80.0 |
Intron chain level: 83.0 | 33.2 |
Transcript level: 82.7 | 31.5 |
Locus level: 93.4 | 57.9 |
Matching intron chains: 26683
Matching transcripts: 29520
Matching loci: 21495
Missed exons: 2979/220514 ( 1.4%)
Novel exons: 45609/347137 ( 13.1%)
Missed introns: 1975/199233 ( 1.0%)
Novel introns: 15350/241928 ( 6.3%)
Missed loci: 0/23009 ( 0.0%)
Novel loci: 12559/36660 ( 34.3%) - RefseqGene vs. Ensembl67
gffcompare v0.10.1 | Command line was:
#gffcompare -R -A -r [...] -s
#= Summary for dataset: ../2017-10-17_Refseq.refGene.mm9.gtf
# Query mRNAs : 37083 in 24285 loci (33220 multi-exon transcripts)
# (6744 multi-transcript loci, ~1.5 transcripts per locus)
# Reference mRNAs : 80524 in 24101 loci (75471 multi-exon)
# Super-loci w/ reference transcripts: 21631
#-----------------| Sensitivity | Precision |
Base level: 78.9 | 92.8 |
Exon level: 70.8 | 93.7 |
Intron level: 83.5 | 95.4 |
Intron chain level: 35.4 | 80.3 |
Transcript level: 36.6 | 79.5 |
Locus level: 88.1 | 88.4 |
Matching intron chains: 26683
Matching transcripts: 29499
Matching loci: 21226
Missed exons: 21443/323510 ( 6.6%)
Novel exons: 7342/224839 ( 3.3%)
Missed introns: 5863/231321 ( 2.5%)
Novel introns: 4799/202335 ( 2.4%)
Missed loci: 0/24101 ( 0.0%)
Novel loci: 1276/24285 ( 5.3%)
This difference has had a great impact on the number of transcripts (in total and also "novel" ones), which I am amble to assemble based on the same alignment with StringTie or Cufflinks using the respective gtf files as reference.
What would be your approach/thoughts to/on this? Any help/suggestions/ideas welcome.
Best
Matthias
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