How to interpret RNAseq output?

Question

[bxxxmxxxx]

Hi all,

I am completely new to this part of bioinformatics. Some of our samples went through RNAseq and I received fastq.gz files. The part I am confused about is that for each sample I got 4 different files and they end the following way:

• XXXXX_L001_R1_001.fastq.gz
• XXXXX_L001_R2_001.fastq.gz
• XXXXX_L002_R1_001.fastq.gz
• XXXXX_L002_R2_001.fastq.gz

No one else does bioinformatics in my lab, so there isn't really anyone here that knows the answer to this question. Can anyone help me out? Once I figure out what they mean, I can start doing analyses.

[Ming Tommy Tang]

You need to start from the basics, https://diytranscriptomics.com/ course will help you.

[Simon]

Full disclosure - I work for a for-profit company, but there are several commercial software platforms on the market that are designed to help those will little to no bioinformatics expertise at least make a first pass at analyzing their data. The idea being if they then find something of interest in the data they can then collaborate with a bioinformatician to validate the observation. An example of these would be Basepair and we offer a free trial of 6 samples so it's easy to evaluate whether it could help or not. We also offer free bioinformatics support as part of the free trial, so if you are having difficulty interpreting your results we should be able to help you move forward. Good luck!

[Rakesh Tiwari]

I am a bioinformatics postgraduate. I Would like to help you to analyze your samples which is very easily possible for now adays. because its really far from here. You can mail me at [e-mail].

[jkim]

https://knowledge.illumina.com/software/cloud-software/software-cloud-software-reference_material-list/000002035

Hope it helps.

Answer 1

[ATpoint]

L stands for lane. You have two lanes per sample meaning that the library has been sequenced across these two lanes to get sufficient reads. R stands for read. R1 and R2 indicate the forward and reverse read in paired-end mode. You can combine the R1 and R2 respectively per sample using cat to get a single file per read and sample.

From here it is standard processing fir RNA-seq, many tutorials out there. Hth.