reprex
Render bits of R code for sharing, e.g., on GitHub or StackOverflow. (by tidyverse)
rna-seq-kallisto-sleuth
A Snakemake workflow for differential expression analysis of RNA-seq data with Kallisto and Sleuth. (by snakemake-workflows)
| reprex | rna-seq-kallisto-sleuth | |
|---|---|---|
| 16 | 1 | |
| 729 | 63 | |
| 0.3% | - | |
| 7.4 | 5.9 | |
| 4 months ago | 11 days ago | |
| R | Python | |
| GNU General Public License v3.0 or later | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
reprex
Posts with mentions or reviews of reprex.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-08-20.
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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
rna-seq-kallisto-sleuth
Posts with mentions or reviews of rna-seq-kallisto-sleuth.
We have used some of these posts to build our list of alternatives
and similar projects.
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qiime2 but for RNAseq data?
(repo is here: https://github.com/snakemake-workflows/rna-seq-kallisto-sleuth)
What are some alternatives?
When comparing reprex and rna-seq-kallisto-sleuth you can also consider the following projects:
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.
bambu - Reference-guided transcript discovery and quantification for long read RNA-Seq data
workflowr - Organize your project into a research website
clustifyr - Infer cell types in scRNA-seq data using bulk RNA-seq or gene sets
deps - Dependency Management with roxygen-style Comments
drake - An R-focused pipeline toolkit for reproducibility and high-performance computing
rmarkdown - Dynamic Documents for R
biomisc_R - command line bioinformatic scripts written in R
mindr - an R package which converts markdown files (.md, .Rmd) into mindmaps (brainstorms)
targets - Function-oriented Make-like declarative workflows for R
electionca - Canadian Elections Data
wiggleplotr - A small R package to make sequencing read coverage plots in R.
reprex vs papaja
rna-seq-kallisto-sleuth vs bambu
reprex vs workflowr
rna-seq-kallisto-sleuth vs clustifyr
reprex vs deps
rna-seq-kallisto-sleuth vs drake
reprex vs rmarkdown
rna-seq-kallisto-sleuth vs biomisc_R
reprex vs mindr
rna-seq-kallisto-sleuth vs targets
reprex vs electionca
rna-seq-kallisto-sleuth vs wiggleplotr