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baltica's Introduction

Baltica

Zenodo DOI
bioRxiv pre-print


Baltica: integrated splice junction usage analysis

Features

  • Snakemake workflows for DJU: JunctionSeq, Majiq, rMATS, and Leafcutter
  • Snakemake workflow for de novo transcriptome annotation with Stringtie
  • Process, integrate and annotate the results from the methods
  • Summarise AS class of differently spliced junctions
  • DJU method benchmarks
  • Report on the integrative analysis

Instructions for using Baltica

We tested the instruction below in a computer cluster running Debian Linux distribution and using the Slurm job scheduler. Baltica uses Snakemake and Singularity, which support many different high-performance systems, for instructions on how to use it on different systems, please see Setting up Baltica: long edition or contact us,

Documentation

https://dieterich-lab.github.io/Baltica/.

Setting up Baltica

Instalation instructions

Contribution

Feedback and contribution are welcome. Would you mind submitting via the GitHub issue tracker Please provide the following information while submitting issue reports:

  • Software and operation system versions
  • Command-line call
  • If possible, also provide sample data so we can try to reproduce the error

baltica's People

Contributors

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baltica's Issues

Dealing with unstranded RNA libraries

JunctionSeq outputs coordinates without the strand information when RNA libraries are unstranded.

We can resolve the issue by changing the IRanges::findOverlaps' parameter ignore.strand from FALSE to TRUE. As a consequence, introns from opposite strands would be grouped.

Config check

Test potentially problematic configuration parameters during CLI startup.

change regarding use-modules

R invocation that require the module system should be used with the --vanilla flag to ignore the R profile settings. So rules using Rscrip should have this flag.

The behavior of --use-envmodules and --use-conda should be compared

Problem with rule rseqc_gene_body_coverage:

rule rseqc_gene_body_coverage is taking too long and output the results for a single condition.

Expected result: one coverage plot for every .bam file; Wrong output: coverage plot for a a single .bam file.

Faill to open source file leafcutter.yml

Hey there,

I appreciate your efforts on developing such cool integration method! I am very interested in exploring this method.
However, I am not familiar with singularity and snakemake. I followed your installation guide.
And, passed baltica --help.
However, when I run baltica all data/config.yml --use-singularity, it showed Failed to open source file /home/ychen12/tools/miniconda3/envs/snakemake/lib/python3.9/site-packages/baltica/../envs/leafcutter.yml
Any idea what should I do? Thank you so much for the help!

BTW, I have changed the paths in config.yml based on your tutorial.
Again, many thanks for any suggestion!

Feedback to 1st presentation

This is a crude list of comments/ideas/etc. that came to my mind while looking at the first Baltica presentation:

  • Page 1: Title sounds good to me!
  • Page 2: "The analogy I have in mind is to associate the drastic consequences of the
    change in route to the changes in pathing in the splice graph"
    • Honestly, this is the first time the name "Baltica" makes sense to me :) But seriously, I find it a nice analogy and a fitting name!
  • Page 2: I like the idea of integrating a transcript scheme in the logo, maybe one can "morph" it inside the baltic sea map? On the other hand, it should not be overcrowded in the end
  • Page 6: JunctionSeq is a mixed DEU/DTU method or am I mistaken? It depends on the "analysis.type"?
  • Page 6: We/you probably need to justify, why those three were chosen in the end for the majority voting. In case of Majiq vs. leafcutter, it is pretty easy since it is "exon-centric" vs. "intron-centric", but for JunctionSeq I find it hard to define what it really does (in easy words, negative binomial model is telling enough?). Does something come to your mind?
  • Page 8: At some point you had Whippet on that list as well, how was your experience with that tool?
  • Page 10: "Validate the sucess potential bias in RNA extraction, lib prep or sequencing"
    • Honestly, I don't know what that means, what is a "success potential bias", if you don't mind me asking :)
  • Page 10: "QC as diagnose"
    • I find this an important/helpful point, maybe it is worth to provide the user some kind of QC html file that gives an easy overview about the parameters you listed
  • Page 10: What does junction saturation mean? Would the quantification of junctions not be "open-end", meaning the more, the better? Also, what would the number of reads mapped to introns "tell us"?
  • Pages 12-14: Technical question, will Baltica go through all the steps of each program? E.g. generating the output plots? Would that be needed or could one skip those steps, since you anyway do the majority voting later on?
  • Page 17: Another technical question, how does Baltica deal with the different cut-offs the single tools use? For example, if I remember correctly leafcutter and Majiq calculate the dPSI differently.
  • Page 18: Why the 2nt difference? If I remember correctly the difference between the coordinates was normally rather 1nt or did I get this wrong?
  • Page 20: Wow, that is pretty devastating for Majiq, am I right? In retrospect and this probably makes everything super difficult, but have you checked how something like Whippet or the others would perform in this scenario?
  • Page 21: Many good points! Of course for us personally, the NMD-AS point is very interesting :)
  • Page 22: Again an honest feedback, I did not fully understand the sub-points you made concerning the "incompatibility among DJU results". What I get is that you try to figure out why the single tools differ so much and I fully agree that this is an (academically) very interesting point. Do you have any indications so far, what might be the reason?
  • Page 23: You would do the de novo annotation completely without reference (which is probably the best for "de novo")? However, the transcripts then have some cryptic names or would you still try to reconcile in the end, to which reference transcripts the ones you have match the best?

Differences in annotate_SJ.R diposited in Baltica and scripts folder

Hi,

I saw differences in Baltica's actual release regarding this script ( the one in Baltica's folder) compared to the one located in scripts folder. In the first one I see that the function filter_hits_by_diff is not used, so as far this is the main point of the results integration among all 4 methods (https://dieterich-lab.github.io/Baltica/integration.html#annotating-the-results) I want to know if this has changed by the use of the simple merge by coordinates in the script ( line 354)

Many thanks in advance!

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