RNA-seq course: Quality control & preprocessing of raw reads

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  • เผยแพร่เมื่อ 23 ส.ค. 2024

ความคิดเห็น • 15

  • @kamyaryazdani8800
    @kamyaryazdani8800 4 ปีที่แล้ว +3

    This tutorial is really great! THANK you so much

  • @theokillian8295
    @theokillian8295 5 ปีที่แล้ว +3

    this is a very informative tutorial, thank you

  • @user-hx8di4cn6b
    @user-hx8di4cn6b 6 ปีที่แล้ว +1

    Very nice tutorial, hope to see your more tutorials! Thank you very much!

    • @ChipsterTutorials
      @ChipsterTutorials  6 ปีที่แล้ว

      Thank you! We are working on new tutorials on single cell RNA-seq at the moment!

  • @mohamedfathi4246
    @mohamedfathi4246 5 ปีที่แล้ว +4

    very nice video, I understood the theoretical background .but it would be great if contains more practical stuff e.g importing files in FASTQC and generating graphs

    • @ChipsterTutorials
      @ChipsterTutorials  5 ปีที่แล้ว +1

      Thank you for the nice comment and good suggestion! Please note that you can find how-to instructions in the playlist "Getting started" at th-cam.com/play/PLjiXAZO27elAV_unFQmpXbB6NbIokQNvt.html

    • @tokoo4skewl
      @tokoo4skewl 5 ปีที่แล้ว

      Chipster Tutorials
      I get the work flow but not sure how to manipulate the input data throughout the workflow for diff exp gene analysis. Is this purely done though the terminal? Or through R ? I haven’t managed to bridge that gap.
      Btw, Great tutorial!

  • @rashmimaurya205
    @rashmimaurya205 3 ปีที่แล้ว

    Thank you so much 😭😭😭😭
    This was very helpful!!

  • @mightyowl1668
    @mightyowl1668 7 ปีที่แล้ว +3

    nice tutorial. could you please give any tutorial for ChIP-seq analysis?

    • @ChipsterTutorials
      @ChipsterTutorials  7 ปีที่แล้ว +1

      Thanks for the feedback & idea! We will keep this in mind when planning new tutorials!

  • @sarabioinfo13
    @sarabioinfo13 3 ปีที่แล้ว

    Thank a lot mam. This is very informative and helpful.

  • @stefaniamontesinos8237
    @stefaniamontesinos8237 3 ปีที่แล้ว +1

    Hi! I've upload my data reads and they're paired-end reads. When I apply trimmomatic on them, it gives me 3 outputs from each data: 1. R1 paired, 2. R2 paired, 3: R3 unpaired. In which one i should apply the next step that is HISAT2? I hope you're doing well. Also, when I annotate my genes in Annotate DESeq2 there's no name for them. All my genes are N/A in the gene name and it doesn't show to what chromosome they are in. Can you help me, please?

    • @ChipsterTutorials
      @ChipsterTutorials  3 ปีที่แล้ว

      Hi Stefania! You want to (most likely, we don't of course now know more about the experimental setup in question!) continue with the read1 and read2 paired read files, and tool "HISAT2 for paired end reads". Regarding the annotations, assuming you are using the tool "Annotate Ensembl identifiers"? In this case, there needs to be human, mouse or rat Ensembl IDs (so something like: ENSG00000000419 or similar) either as row names or in the first column of the input file.

    • @stefaniamontesinos8237
      @stefaniamontesinos8237 3 ปีที่แล้ว +1

      @@ChipsterTutorials Thank you very much! I want to annotate genes for a fungus, which tool would you recommend?