How to find adapter contamination information in MultiQC result

Question

[Kumar]

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.

[Ram]

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.

That is not the way to do it. You need R1 and R2 FASTQ files, or interleaved FASTQ, not concatenated FASTQ.

Please use imgbb to add your image. Follow this guide: How to add images to a Biostars post

MultiQC clearly speaks about adapter content. If your FASTQ has adapter contamination, use software like cutadapt or trimgalore to trim them.

[Kumar]

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.

[Ram]

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.

[Kumar]

I am using Kallisto as an aligner. Does it trim adaptor automatically while aligning?

[GenoMax]

kallisto is not a conventional aligner.

kallisto is a program for quantifying abundances of transcripts from bulk and single-cell RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads. It is based on the novel idea of pseudoalignment for rapidly determining the compatibility of reads with targets, without the need for alignment.

[Kumar]

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.

[Ram]

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!

[Kumar]

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.

$trim_galore --illumina --paired --fastqc -o /DataAnalysis/mutant/