How to find adapter contamination information in MultiQC result
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22 months ago
Kumar ▴ 130

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. RNA-Seq MultiQC FastQC • 1.3k views ADD COMMENT 0 Entering edit mode 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 usingcat command.

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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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.

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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.

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

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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.

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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.

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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!

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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/