Hello everyone, I am using Kallisto-Sleuth at the very end of my pipeline in the RNA seq analysis. I'm trying to find on the web (as a newbie) all the reasons in favour of my choice; I would like to ask why choosing Kallisto and Slueth at the end of my pipeline would be a better choice than Deseq2..
Kallisto is not an alternative to deseq2.
Kallisto does the quantification (assigns reads to transcripts). You can run deseq2 on the effective counts output of kallisto (after rounding these counts to integers).
Sleuth is the "alternative" to deseq2.
thanks and sorry if I am a bit confused about this; which pipeline is the best among the following ones: fastq file-->STAR-->bam file-->HTSEQCOUNT-->.txt-->DESEQ2/PCA/DE or fastq file-->KALLISTO-->SLEUTH-->differential expression analysis
or do you prefer any other different approach? finally I am not sure I have understood how to define the best "formula"...how can you say "this is a best solution"? please help me and sorry for my English
There is no gold standard that outperforms the others. Both of the pipes that you mention are valid and perform well. For the end user (and this is just my personal opinion) it all comes down to which pipeline you feel most comfortable with, in terms of documentation and handling. There are a number of benchmarks comparing the approaches, please use PubMed for it. Both DESeq2, Sleuth, as well as the other accepted approaches like edgeR do work, are accepted and well tested. In my experience, end users do use what they first got in contact with, either by searching around, reading blogs or what the instructor used in your first RNA-seq workshop. If you read the blogs of the biostatisticians who develop these tools, even they acknowledge that each approach has its own qualification, without that it outperforms others (see here for an example). So choose whatever you feel most comfortable with, follow the instructions in the manuals and vignettes, and get on with your analysis.
thank you for your replies; I come from a different background and I am just looking at these tools for the first time. Genomax how can I verify the hypotheses? If I don't misread what you said, you are basically state that after 'running' my pipeline I have to verify experimentally the result (so this further assessment should be done in silico, as well?); is there any way to validate my results prior to go on 'the bench'?
Secondly, is it a good idea to use kallisto as input for DESeq2 or maybe it is better to use deseq2 with "the STAR" pipeline? Or probably it could be worth doing fastq file-->KALLISTO-->DESeq2 & fastq file-->KALLISTO-->Sleuth?
is there any way to validate my results prior to go on 'the bench'?
As long as the biological differences are prominent in your dataset results, you get from DESeq2 or Sleuth should be reasonably similar. Someone with domain knowledge of the experiment (if that is not you) should be able to look at the results and get an idea if the results make a story. They will also be able to decide which genes can be selected for further experimental validation.
If it's your own curiosity, then you can run two workflows - it could be seen as a training exercise.
As an example, though, I once ran the following analyses on the same data:
...and got the same results where it mattered.
As genomax says, "as long as the biological differences are prominent in your dataset results", you should get the same results from each of the standard/accepted methods.
I think it is helpful to have more than one pipeline in mind because, as I have run into, sometimes a tool just will not work. I can't open the kallisto created h5 files with sleuth because of the environment in which they are created and have yet to figure out how to change it so it will work. Note: NOT asking that as a question here, simply saying that with these tools it is also a good idea to know your options because sometimes they don't work and you need results by X day without necessarily the time to fix the issue.
Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
version 2.3.6
Sounds like you made that choice without recognizing difference between alignment and mapping.