I noticed that if I assign gene names with the t2g file I get slightly different results compared to if I use biomart. Most of the gene counts are very similar. When I compare the data on a scatter plot I get a pearson correlation of 0.98. However, it seems that the t2g file produced from biomart includes some additional transcripts from a scaffold patch for some genes. I checked the gtf file from the same version and those are not included even though they are included in the cdna fasta file. Is it important to include the counts from the patches?
Hello,
I am working with bulk RNA seq data. I created a reference like shown below:
kallisto index -i mouse_version111cdna Mus_musculus.GRCm39.cdna.all.fa.gz
Then I created a t2g file using a script I had found in github (https://github.com/pachterlab/kallisto-transcriptome-indices/releases/download/ensembl-96/t2g.py):
python t2g.py --use_version <Mus_musculus.GRCm39.111.gtf.gz> transcripts_to_genesmousev111.txt
I noticed that if I assign gene names with the t2g file I get slightly different results compared to if I use biomart. Most of the gene counts are very similar. When I compare the data on a scatter plot I get a pearson correlation of 0.98. However, it seems that the t2g file produced from biomart includes some additional transcripts from a scaffold patch for some genes. I checked the gtf file from the same version and those are not included even though they are included in the cdna fasta file. Is it important to include the counts from the patches?
Thank you