How to tell is sequencing data is unstranded, firststrand, or secondstrand

Question

[williamsbrian5064]

Hi

I have some RNA-Seq data that I received from a colleague. I am trying to figure out if the data is unstranded, firststrand, or secondstrand. Is there an easy way to tell? I am running the data through salmon and this is what the lib_format_counts.json file is giving me. I think it is secondstranded?

read_files  "Sample1"
expected_format "SR"
compatible_fragment_ratio   0.9945605200682789
num_compatible_fragments    18794420
num_assigned_fragments  18897211
num_consistent_mappings 56858584
num_inconsistent_mappings   328289
MSF 0
OSF 0
ISF 0
MSR 0
OSR 0
ISR 0
SF  328289
SR  56858584
MU  0
OU  0
IU  0
U   0

Any ideas?

[grant.hovhannisyan]

Maybe ask the colleague?:)

[Devon Ryan]

What fun is that!

[igor]

Sometimes colleagues forget what they did or remember incorrectly. The data, on the other hand, doesn't lie.

[williamsbrian5064]

haha I would be they haven't been the easiest to get in contact with. You know how it goes.

[igor]

There are some excellent answers posted already, but just in case you want to learn more about strandness, check this previous post: Read pair orientation : Illumina TruSeq Stranded mRNA library

[williamsbrian5064]

Great link! Very helpful info! I appreciate it!

Answer 1

[Devon Ryan]

Yes, this appears to be the standard dUTP/secondstrand/ISR library. As an aside, this is the most likely library prep type these days.

[williamsbrian5064]

Awesome! So the sequencing data is single end. Would this then be considered SR instead ISR?

[Devon Ryan]

Yes, SR rather than ISR.

[williamsbrian5064]

Thanks you so much!

Answer 2

[Bastien Hervé]

If you have no clue, take a look at RSeQC ( infer_experiment.py )

This program is used to “guess” how RNA-seq sequencing were configured, particulary how reads were stranded for strand-specific RNA-seq data, through comparing the “strandness of reads” with the “standness of transcripts”.

Answer 3

[swbarnes2]

You can always eyeball it in IGV. It should be pretty easy to spotcheck half a dozen genes and see which way the reads go.