ISM_3prime

[rb520826]

I have a column output in my SQANTI3 classification file entitled 'ISM_3prime'. I would like to use it but first I want to understand where it came from. I am using the latest version of SQANTI3 and using a slightly adapted json file:

{
"full-splice_match": [
{
"perc_A_downstream_TTS":[0,59]
}
],
"rest": [
{
"perc_A_downstream_TTS":[0,59],
"RTS_stage":"FALSE"
}
]
}

So I have specified anything for ISM or subcategories. Basically I just want to check that the 'Yes' which appears in the column 'ISM_3prime' applies to the ISM transcript having 3' support. Is this correct?

This is the header of my SQANTI3 classification file:
isoform chrom strand length exons structural_category associated_gene associated_transcript ref_length ref_exons diff_to_TSS diff_to_TTS diff_to_gene_TSS diff_to_gene_TTS subcategory RTS_stage all_canonical min_sample_cov min_cov min_cov_pos sd_cov FL n_indels n_indels_junc bite iso_exp gene_exp ratio_exp FSM_class coding ORF_length CDS_length CDS_start CDS_end CDS_genomic_start CDS_genomic_end predicted_NMD perc_A_downstream_TTS seq_A_downstream_TTS dist_to_cage_peak within_cage_peak dist_to_polya_site within_polyA_site polyA_motif polyA_dist polyA_motif_found ORF_seq ratio_TSS filter_result novelGene exonCat within_50_cage within_50_TTS within_50_TSS RNASeq_supported within_polya_site ISM_3prime structural_category_exons monomulti

Thank you in advance and also for a great tool :)

[pabloati]

Hi, have you modified the classification file somehow to obtain the columns after "filter_result"? Could you share as well the command you use to run sqanti?

In theory, you could use filter to keep only IMS_3'prime with the following addtion to your rules:

{
"full-splice_match": [
{
"perc_A_downstream_TTS":[0,59]
}
],
"incomplete-splice_match":[
{
"subcategory":"3prime_fragment"
}
],
"rest": [
{
"perc_A_downstream_TTS":[0,59],
"RTS_stage":"FALSE"
}
]
}

Let me knwo if that works :)

[rb520826]

Hi, thank you for your reply! This is the command for SQANTI that we have:
## run sqanti
echo "Run Sqanti"
source activate sqanti2_py3
python ${SQANTI3_DIR}/sqanti3_qc.py $3/${prefix}.gff ${refAnno} ${refFile} -o WholeTargeted_collapsed${chr_chunk}
--report skip --genename --skipORF
--CAGE_peak ${CAGE_PEAK} --polyA_motif_list ${POLYA}

## run sqanti filter
echo "Run Sqanti filter"
python ${SQANTI3_DIR}/sqanti3_filter.py rules \
  --output WholeTargeted_collapsed_filtered${chr_chunk} \
  --skip_report --gtf WholeTargeted_collapsed${chr_chunk}_corrected.gtf \
  --json_filter ${SQANTI_JSON} WholeTargeted_collapsed${chr_chunk}_classification.txt

From the classification txt file I was just doing a simple 'grep' of the rows which had 'yes' in the 'ISM_3prime' column. I just was wondering where the 'ISM_3prime' support came from really - just wanting a little more understanding and background.
Thanks!

[pabloati]

From what I am seeing, you are running a quite outdated version of SQANTI3. I would recommend first that you update SQANTI3 to the latest release 5.5.2. Also, don't forget to update the conda environment, I see you have the sqanti2 old environment.

The extra columns that you are seeing after "filter_result" in the classifcation file should not be there and they show redundant information. If you rerun your dataset with the latest release, they will dissapear, and your results will be much more accurate.

If you want to filter to eliminate the ISM 3' or keep them, follow the instructions above :)