workflowr
reprex
| workflowr | reprex | |
|---|---|---|
| 2 | 16 | |
| 807 | 729 | |
| 0.9% | 0.3% | |
| 5.4 | 7.4 | |
| 2 months ago | 4 months ago | |
| R | R | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
workflowr
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How do you manage results, plots, etc.?
I would start by saying "bioinformatics world" is a very broad term. Most of it does not involve managing multiple models, which is what MLflow seems to be for. Most work is cleaning the data and interpreting the results, which is highly project-specific. Something like workflowr is generally more appropriate, but even that is an overkill for most people.
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Restructuring a large R project. Need advice on how to wire up file paths and associated objects.
Targets stores all your data serialised on disk, and only loads them in as needed by the dependencies. For a standardised folder structure, you can take inspiration from workflowr.
reprex
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Do the work
Provide us with the code in a minimum working example (MWE) form (typically called reprex in the R community). If the process of producing this doesn't help you solve the issue, it at least allows us to (a) copy and paste to run the code, and (b) far more likely to be able to spot the error(s) than when they’re embedded in a load of code that isn’t necessary to highlight the problem. These should be placed in a code block, either every line indented 4 spaces or within backticks. (Credit to Mooks79 for this.) More info here: https://www.reddit.com/r/learnpython/wiki/faq#wiki_how_do_i_format_code.3F
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What is the best way to simplify a ggplot with 10 factors?
Let me start by saying it's generally preferred that you offer a reprex in a post like this, meaning at a minimum you should share (1) the minimal necessary code to reproduce your issue and (2) at least a toy data set that can be used to test your code (so, not a screen shot but maybe something created by dput(WSD), dpasta(WSD), or the like). I personally would prefer that you also format your code as a code block in your post to make it easier to read, but that's not a deal breaker (just me being fastidious).
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Help with RStudio and Giant Odds Ratios
Is reproducible example would be a nice start: https://reprex.tidyverse.org/
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Dplyr t test help
It's really hard to help you debug without a reprex
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Returning matching subsets of data based on multiple conditions
df_sl = data.frame( SubLvlList = c( '1-Z', '2-Z', '1-Y', '2-Y' ) ) data.frame( ReturnMatch = sapply( df_tl[,1], function(x) { df_sl[,1][sapply(df_sl[,1], function(y) {grepl(y, x)})] }, USE.NAMES = FALSE) ) #> ReturnMatch #> 1 1-Z #> 2 1-Z #> 3 2-Z #> 4 2-Z #> 5 1-Y #> 6 1-Y #> 7 2-Y #> 8 2-Y #> 9 1-Z #> 10 1-Z #> 11 2-Z #> 12 2-Z #> 13 1-Y #> 14 1-Y #> 15 2-Y #> 16 2-Y ``` Created on 2023-03-25 with [reprex v2.0.2](https://reprex.tidyverse.org)
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I keep getting error: "Error in t1(.) : could not find function "t1""
Making a reproducible example is a super good way to check that you are running what you think you are running.
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Very new to R and I am trying to merge 2 data frames by similar columns
reprex::reprex()
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HELP
What you have posted is not valid R code. See https://reprex.tidyverse.org/ for example on how to create a reproducible example.
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Why does converting a list to a vector require using the "unlist" function?
``` Created on 2022-11-11 with reprex v2.0.2
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Any idea why the scale of my ggplot is pushed to a corner on the left rather than having it spread across the whole plot?
https://reprex.tidyverse.org A sample of the code might help in understanding what happened
What are some alternatives?
targets - Function-oriented Make-like declarative workflows for R
rna-seq-kallisto-sleuth - A Snakemake workflow for differential expression analysis of RNA-seq data with Kallisto and Sleuth.
box - Write reusable, composable and modular R code
papaja - papaja (Preparing APA Journal Articles) is an R package that provides document formats to produce complete APA manuscripts from RMarkdown-files (PDF and Word documents) and helper functions that facilitate reporting statistics, tables, and plots.
targets-minimal - A minimal example data analysis project with the targets R package
deps - Dependency Management with roxygen-style Comments
blogdown - Create Blogs and Websites with R Markdown
rmarkdown - Dynamic Documents for R
data-science-development-project-template - A logical, reasonably standardized, but flexible project structure for doing and sharing data science research work while developing a software tool.
mindr - an R package which converts markdown files (.md, .Rmd) into mindmaps (brainstorms)
webR-quarto-demos - Experiments with generating a standalone Quarto Document using Web R
electionca - Canadian Elections Data