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Friederike Dündar friedue Applied Bioinformatics Core | Weill Cornell Medicine New York / Berlin https://abc.med.cornell.edu/ wrestling data of the 'omics universe for >10 years

deeptools/deepTools 493

Tools to process and analyze deep sequencing data.

deeptools/HiCExplorer 143

HiCExplorer is a powerful and easy to use set of tools to process, normalize and visualize Hi-C data.

abcdbug/dbug 9

notes and materials from dbug meetings

friedue/Notes 6

Personal notes about work- and coding-related topics

friedue/AlleleSpecific 2

pipeline for allele-specific mapping of short reads

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issue commentopenjournals/joss-reviews

[REVIEW]: Bam-readcount - rapid generation of basepair-resolution sequence metrics

@lpantano My suggestions have been addressed; I'll wait for @bebatut's verdict, but I have no hesitation to recommend this for publication now.

whedon

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issue closedgenome/bam-readcount

[JOSS REVIEW] Example usage

Related to: https://github.com/openjournals/joss-reviews/issues/3722

Example usage: Do the authors include examples of how to use the software (ideally to solve real-world analysis problems).

As mentioned in the other issue #79, running the test data set was a bit of a pain and I didn't see it encouraged or documented. It'd be great if you could add that, either to the README or some other form of documentation that is linked to in the README.

The output file is a bit overwhelming, so maybe adding a brief example of how to parse it would be helpful. I found [this tutorial about calculating tumor VAFs](https://pmbio.org/module-05-somatic/0005/05/01/Somatic_LOH_Calling/ where you show how to calculate tumor VAFs ) that seemed to do exactly that, so linking to that could be the minimalist solution, adding a .Rmd/HTML to the bam-readcount repo might be even nicer to help people understand more quickly what the different scores represent.

Generally, I feel that it'd be useful to add a more extended blurb on typical use-cases for bam-readcount. I understand it's already part of more extensive pipelines, but since you're publishing it on its own merits here, it'd be great if new users could immediately grasp why they should start using bam-readcount (apart from performance arguments). I personally love visuals, but I understand that's not everyone's preference.

Last suggestion (totally optional): the paper on SARS-CoV2 mutations that you cite sounds like it could provide a great example use case; if the authors would be willing to share their R and python code or to just generate a brief walk-through of the part that uses bam-readcount and how it helped them shape their conclusions, that'd be fantastic.

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friedue

issue commentgenome/bam-readcount

[JOSS REVIEW] Example usage

You could really be capitalizing on the omicron-link to get people to use bam-readcount and familiarize themselves with it without noticing (because they'll be so eager to find out more about omicron). But that's your call and it's totally fine the way you've done it now. Shout-out to @apldx for a job really well done!

friedue

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issue closedgenome/bam-readcount

[JOSS REVIEW] minor edits to the manuscript

Related to: https://github.com/openjournals/joss-reviews/issues/3722

  • [x] please extend the "statement of need" a bit, or rephrase it so that within the first sentence it is already obvious that bam-readcount is not so much just about counting reads, but primarily about collecting metrics that are particularly helpful in judging wether a specific variant call is reliable or not (or maybe that's not even the primary use-case, who knows! :) )
  • [x] similarly, the conclusion should state a bit more clearly what precisely the role of bam-readcount is in the bespoke pipelines and the use cases that are mentioned there
  • [x] lines 37 and 54 should have "its" instead of "it's"

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friedue

issue commentgenome/bam-readcount

[JOSS REVIEW] Example usage

This is a great and timely tutorial! It ticks all the boxes -- it show cases bam-readcount, it demonstrates what its place could be in typical analysis pipelines and it features some hands-on, highly relevant and scientifically interesting results. Well worth the wait! Now you just need to link/highlight this tutorial in the bam-readcount repo README.

friedue

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issue commentgenome/bam-readcount

[JOSS REVIEW] minor edits to the manuscript

Great update to the text! The use-cases of the tool are very clearly described now, great job!

[ ] There's a typo on line 61, and there might be a letter missing in line 50, too ("disks?").

friedue

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Collection of notes and scripts that may come in handy

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Scripts related to single-cell and bulk RNA-seq data of mouse pancreata as presented by Rubio-Navarro et al.

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issue commentLTLA/SingleR

Requesting training data

The "in-built" reference data sets that will work out-of-the-box with SingleR can be found in the celldex package.

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issue commentMarioniLab/miloR

which cells are in a specific neighborhood?

Absolutely, just goes to show that I really should have been reading the supplemental note of the paper. The mention of "overlap" in the vignette was definitely a clue as well.

ainarill

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issue commentMarioniLab/miloR

Extract the matrix of cells and their neighbourhoods

Hi @KASHISH72 As I stated above, the columns correspond to the neighbourhoods (these are just numbered). The neighbourhoods are defined by the index cell, which can be retrieved using the nhoodIndices() function.

Just a comment for future users: the function name is actually nhoodIndex().

It is a little confusing that the colnames of the nhoods() output (where you use the index cells) aren't equivalent with the Nhood entry in the testNhoods() output (where they seem to be simply numbered from 1:n). Not a big issue, of course, but a minor roadblock for users trying to familiarize themselves with the objects

KASHISH72

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issue commentMarioniLab/miloR

which cells are in a specific neighborhood?

Following up on this excellently addressed question -- while following the code above I noticed that some cells have more than one neighborhood they're assigned to (i.e. rowSums(milo) > 0). Could you comment on the interpretation and ramifications of that? Are cells that belong to multiple neighborhoods shown as individual/independent dots in the beeswarm plots and so on?

ainarill

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issue openedjkmorrison/zebrafish-liver

access to the cluster information for reference label use

Hi,

thanks for the great work! I'm searching for scRNA-seq data sets that can be used as reference data sets for various cell types. The data you've presented in the related bioarxiv paper looks very promising and I was wondering if you could provide access to the mapping of cell barcodes to clusters/cell identities as shown in the paper for the WT sample (or for both, I can filter for the WT myself, I guess)? A simple tsv file of barcodes and cell identities suffices (the complete Seurat object is probably rather large). Thanks so much and good luck with your paper revision! Best, Friederike

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issue openedbailey-lab/SeekDeep

trouble with the installation

Hi Nick,

been trying to follow your installation instructions for a server with Linux environment, but repeatedly running into issues. I'll attach the latest wall of text here; if you've got any pointers to what could be amiss, that'd be greatly appreciated.

My default python version is Python 3.8.12., but a call to python2.6 also works

$ python --version
Python 3.8.12

$ python2.6 --version
Python 2.6.6

Thanks a lot!

Friederike seekDeppInstallTrouble.md

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