[Microbiome] Add tutorial for MAGs building and annotation from raw reads #6556
Conversation
bebatut
force-pushed
the
mags-building
branch
2 times, most recently
from
f1be644 to
cc01163
Compare
bebatut
force-pushed
the
mags-building
branch
from
cc01163 to
b99bf18
Compare
paulzierep
left a comment
paulzierep
left a comment
There was a problem hiding this comment.
Need to continue with the main tutorial later.
|
|
||
| 7. **Recommended**: click **Import** (left of Run) to make your own local copy under *Workflows / My Workflows*. | ||
|
|
||
| You may have to refresh your history to see the queued jobs |
| @@ -0,0 +1,44 @@ | |||
| # Generate input datasets for the training | |||
There was a problem hiding this comment.
This needs a update, now its just two samples, no preprocessing, right ?
There was a problem hiding this comment.
This Markdown is not for learners. It was meant to be as a documentation on how that data were generated
paulzierep
left a comment
paulzierep
left a comment
There was a problem hiding this comment.
Amazing work, if you could address the comments still, I think we should merge it for now !
| > > Forward (Read 1) - Before | 34.5 | 34.6 | ||
| > > Forward (Read 1) - After | 34.5 | 34.6 | ||
| > > Reverse (Read 2) - Before | 33.4 | 32.7 | ||
| > > Reverse (Read 2) - After | 33.4 | 32.7 |
There was a problem hiding this comment.
maybe a comment why this does not change ?
There was a problem hiding this comment.
I guess they deposited trimmed reads
| > > <solution-title></solution-title> | ||
| > > | ||
| > > 1. 2.8% for SRR24759598 and 1.1% for SRR24759616 | ||
| > > 2. 2.8% for SRR24759598 and 1.1% for SRR24759616 |
There was a problem hiding this comment.
this is not the number of reads ... but if we take percentage the question is a bit useless no ?
| > > <comment-title></comment-title> | ||
| > > metaSPAdes is an alternative assembler. | ||
| > > | ||
| > > MEGAHIT is less computationally intensive and generate higher quality single and shorter contigs but shorter. metaSPAdes is very computationally intensive, but generates longer/more complete assemblies. |
There was a problem hiding this comment.
strange sentence, and maybe point to https://doi.org/10.1093/bib/bbad087 for a benchmark
|
|
||
| Beyond simply comparing the total number of bins, we can also examine the **contigs per bin** for each binning tool, which provides deeper insight into the **quality and granularity** of the reconstructed microbial genomes. | ||
|
|
||
| For that, we will use the `collection X, collection Y, and others (as list)` collection of collection. This structure contains two sub-collections—one for each sample. Within each sub-collection, there are four tables, each corresponding to a different binning tool (MetaBAT2, MaxBin2, SemiBin, and CONCOCT). Each table consists of two columns: the contig identifier and its assigned bin ID. |
There was a problem hiding this comment.
For that, we will use the collection X, collection Y, and others (as list) collection of collection. - not clear
Co-authored-by: paulzierep <paul.zierep@googlemail.com>
|
thanks @bebatut |
2 participants
In complement of the MAGs learning pathway, this tutorial takes raw reads from a publication and, using workflows from IWC:
Each step is explained (with a link to the corresponding dedicated tutorial for a more advanced explanation), and the results are commented on.
I prepared histories with preprocessed data on UseGalaxy.eu, UseGalaxy.org, UseGalaxy.org.au, and UseGalaxy.fr.