Bambu for plant data

[baibhav-bioinfo]

Hello,
Very helpful tool.
I am using Nanopore DRS dataset belonging to sorghum plant.
(1) can I use your general model directly to identify the novel transcripts in my dataset or do I need to train a model for plant or something?
(2) sorghum does have a pretty good annotated reference transcriptome. so what should be my NDR value if I am just interested in identifying novel transcripts which I will add in existing to make an updated transcriptome.

[cying111]

Hi,

Glad to hear you're using Bambu for sorghum plant DRS data—sounds exciting!

1. For your first question, the answer depends on your data size. If you have enough data to train a model, that's ideal. By default, Bambu will attempt to train a model based on the provided data and will issue a warning if the data isn't sufficient.
2. For your second question, you can leave NDR = NULL if you're unsure. Bambu will then recommend an NDR value corresponding to 10% of the human transcriptome.

Hope this helps! Let us know if you have any other questions.
Thanks!
Warm regards,
Ying

[baibhav-bioinfo]

hello, thankyou so much for the swift response
as its written in documentation that the pretrained model do perform well on arabidopsis data too.
can i use the same pretrained model in my case too?
I am using following command to get the novel transcripts discovery from 3 condition and 3 rep data in each

se.multiSample_discovery_only_NDR_null <- bambu(reads = c("a6_r1.bam", "a6_r2.bam", "a6_r3.bam", "b6_r1.bam", "b6_r2.bam", "b6_r3.bam", "c6_r1.bam", "c6_r2.bam", "c6_r3.bam"), annotations = annotations, genome = "SbicolorRTx430_552_v2.0.fa", quant = FALSE, NDR = NULL)

bambu recommends a NDR of 0.085 (as sorghum is well annotated)

is this command good enough (maybe not ideal) for the novel transcript discovery? or do i have to go for species specific training?

if yes, can you guide me though it, i would appreciate it

[cying111]

Hi,

The current command already does species-specific training by default. So you can go ahead with it.

Hope this clarifies your question!

Thank you
Ying