How to find adapter contamination information in MultiQC result
Hi, I have got 180 RNASeq samples (.fastq) paired-end for differential gene expression analysis. Initially, I am just trying to run five samples (.fastq).
Each sample has four files (.fastq), so I merged these four files into a single .fastq file in order to make a single fastq file using $cat command.
Then I RUN fastqc for all five samples.!
Here are the MultiQC results of five samples (please open the link--https://freeimage.host/i/dNXxp4). I am not sure how I can find the adapter contamination information here. Please indicate? Also, please let me know, do I need to trim adaptor before analyzing these data. I am considering to use Kallisto as an aligner.
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That is not the way to do it. You need R1 and R2 FASTQ files, or interleaved FASTQ, not concatenated FASTQ.
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MultiQC clearly speaks about adapter content. If your FASTQ has adapter contamination, use software like cutadapt or trimgalore to trim them.
Yes, I have R1 (four parts in fastq.gz) and R2 (four parts .fastq.gz). I concatenated four parts of R1 and four parts of R2 files separately to make a single fastq file of R1.fastq and R2.fastq. Then I am using FastQC and MultiQC for a total of five samples. Please let me know if it is not the way.
Here, is the result of MultiQC. How I can know the adapter contamination or it is good in the result.
All of your FASTQs are hitting the red zone in the last 30-45 BP, so I think you'll need to trim adapters on all of them. Have a look at TrimGalore - it'll help clean up your FASTQs.
I am using Kallisto as an aligner. Does it trim adaptor automatically while aligning?
kallistois not a conventional aligner.I have got 180 RNASeq samples (.fastq) paired-end for differential gene expression analysis. Please suggest the appropriate aligner. Should I use STAR, however it could be very slow since I have a large number of data. Therefore, I was thinking to use kallisto.
Time you're wasting not deciding on a tool is time you could be spending trimming your FASTQs. Seriously though, pick a too and stick to it. STAR and Kallisto both have advantages and disadvantages. Figure out if your lab/institution has an existing pipeline. If not, read both papers and make a pros and cons list. See what you cannot compromise on and pick based on that.
Plus, and hear me out - you could use both and compare!
I used TrimGalore to improve the reads. Here, is FastQC report. Reads after trimming and before TrimGalore. Could you please take a look if the output seems fine? After this process, I am using STAR, but the alignment score is low. Do I need to use Kallisto in this case?
I used the following command to RUN TrimGalore.