Hacktoberfest 2026: the issues maintainers tagged for October, open and beginner-friendly. Browse Hacktoberfest issues

Rarecurve output range

Open
#85 3 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Assessment

Difficulty
3/5
Estimated time
1-2 days
Newbie friendliness
25/100
Issue type
Feature
Clarity
Needs clarification
Activity status
Stale
Tech stack
r

Research direction

Start with the calls to mp_rrarefy(), mp_cal_rarecurve(), and mp_plot_rarecurve(), then inspect the generated RareAbundanceRarecurve data and the plot coordinate limits. Determine whether the depth is limited during rarecurve calculation or only during plotting; done means the output can represent depth up to 2e7 reads and the requested observations range.

Written by the indexing model from the issue text.

Description

Rareplot

Hello...I apologize if this question seems basic, but I was wondering if you could help me figure out how to increase the range of the outputted rarecurve (i.e. the depth [readsNums] and observations [value]). I wish to see the depth up to 2e7 reads. I tried to simply extend the coordinates of the output but this did not work. Thank you for your time!
Code:
mpse %<>% mp_rrarefy() %<>%
mp_cal_rarecurve(
.abundance = Abundance,
chunks = 350, action = "add", force=FALSE
)

set.seed(1234)
plotmpse<- mpse %>%
mp_plot_rarecurve(
.rare = RareAbundanceRarecurve,
.alpha = "Observe",
.group = CollectionPhase,
plot.group = TRUE
) + theme_bw() + coord_cartesian(xlim=c(0,2000), ylim = c(0,100))+
scale_color_manual(values=c("#789ED0", "#F79D40", "#72BF56", "#E4655A", "#AB8BCB")) +
scale_fill_manual(values=c("#789ED0", "#F79D40", "#72BF56", "#E4655A", "#AB8BCB"))
plotmpse

Dominant language
R
Stars
196
Forks
36
PR merge metrics
No merged PRs in 30d

Getting set up

This project ships no dev container, Dockerfile or contributing guide, so setting up is up to you: start from its README, and see our first-contribution guide for the general steps.

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

More from YuLab-SMU/MicrobiotaProcess

All issues in YuLab-SMU/MicrobiotaProcess

Similar issues

More R issues

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.