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chromer

package for interacting with the chromosome counts database (CCDB) at https://taux.evolseq.net/CCDB_web/

https://github.com/ropensci/chromer

Science Score: 23.0%

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    Found 1 DOI reference(s) in README
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    1 of 7 committers (14.3%) from academic institutions
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    Low similarity (15.2%) to scientific vocabulary

Keywords

r r-package rstats

Keywords from Contributors

genome stable open-educational-resources lesson geospatial-data english data-wrangling data-carpentry carpentries paleoecology
Last synced: 10 months ago · JSON representation

Repository

package for interacting with the chromosome counts database (CCDB) at https://taux.evolseq.net/CCDB_web/

Basic Info
Statistics
  • Stars: 12
  • Watchers: 9
  • Forks: 4
  • Open Issues: 1
  • Releases: 5
Topics
r r-package rstats
Created over 11 years ago · Last pushed 12 months ago
Metadata Files
Readme License

README.md

R-CMD-check CRAN status <!-- badges: end -->

chromer chromer logo

This package provides programmatic access to the Chromosome Counts Database (CCDB) API. The CCDB is a community resource for plant chromosome numbers. For more details on the database, see the associated publication by Rice et al. (2014) doi:10.1111/nph.13191 in New Phytologist.

This package is maintained by Karl Broman and was formerly maintained by Paula Andrea Martinez and Matthew Pennell, none of whom are affiliated with the CCDB group. The URL for Chromer docs is https://docs.ropensci.org/chromer/.

Installing

The package can be installed directly from CRAN, but it is currently outdated -- PLEASE install directly from GitHub

r install.packages("chromer")

or, for the latest version, you can install directly from GitHub using remotes

```r

install.packages("remotes")

remotes::install_github("ropensci/chromer") ```

Querying the CCDB

It is possible to query the database in three ways: by species, genus, family, and majorGroup. For example, if we are interested in the genus Solanum (Solanaceae), which contains the potato, tomato, and eggplant, we would query the database as follows

r library(chromer) sol_gen <- chrom_counts(taxa = "Solanum", rank = "genus") head(sol_gen) nrow(sol_gen)

There are over 3000 records for Solanum alone! If we are interested in a particular species, such as tomatoes, we can search for the species directly.

r sol_tom <- chrom_counts(taxa = "Solanum_lycopersicum", rank = "species") head(sol_tom)

Note that taxa="Solanum lycopersicum" (including a space between the genus and species name) will also work here.

If we wanted to get data on the whole family, we simply type

r sol_fam <- chrom_counts(taxa = "Solanaceae", rank = "family") head(sol_fam)

Or, expand the scope much further and get all Angiosperms (this will take some time)

r ang <- chrom_counts(taxa = "Angiosperms", rank = "majorGroup") head(ang)

There are two options for returning data. The first (default) is to only return the species name information (including taxonomic resolutions made by Taxonome) and the haploid and diploid counts. Setting the argument full=TRUE

r sol_gen_full <- chrom_counts("Solanum", rank = "genus", full = TRUE)

returns a bunch more info on the records.

r head(sol_gen_full)

Summarizing the data

The Chromosome Counts Database is a fantastic resource but as it is a compilation of a large number of resources and studies, the data is somewhat messy and challenging to work with. We have written a little function that does some post-processing to make it easier to handle. The function summarize_counts() does the following:

  1. Aggregates multiple records for the same species

  2. Infers the gametophytic (haploid) number of chromosomes when only the sporophytic (diploid) counts are available.

  3. Parses the records for numeric values. In some cases chromosomal counts also include text characters (e.g., #-#; c.#; #,#,#; and many other varieties). As there are many possible ways that chromosomal counts may be listed in the database, the function takes the naive approach and simply searches the strings for integers. In most cases, this is sensible but may produces weird results on occasion. Some degree of manual curation will probably be necessary and the output of the summary should be used with caution in downstream analyses.

To summarize and clean the count data obtained from chrom_counts() simply use

r summarize_counts(sol_gen)

Meta

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Owner

  • Name: rOpenSci
  • Login: ropensci
  • Kind: organization
  • Email: info@ropensci.org
  • Location: Berkeley, CA

GitHub Events

Total
  • Issues event: 3
  • Issue comment event: 3
Last Year
  • Issues event: 3
  • Issue comment event: 3

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 103
  • Total Committers: 7
  • Avg Commits per committer: 14.714
  • Development Distribution Score (DDS): 0.495
Past Year
  • Commits: 15
  • Committers: 1
  • Avg Commits per committer: 15.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Karl Broman k****n@g****m 52
matthew pennell m****l@g****m 32
Paula Andrea Martinez o****0 10
Scott Chamberlain m****s@g****m 4
Karthik Ram k****m@g****m 2
steven2249 s****w@b****u 2
Rich FitzJohn r****n@g****m 1
Committer Domains (Top 20 + Academic)
berkeley.edu: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 34
  • Total pull requests: 9
  • Average time to close issues: 9 months
  • Average time to close pull requests: 3 months
  • Total issue authors: 16
  • Total pull request authors: 6
  • Average comments per issue: 2.97
  • Average comments per pull request: 0.22
  • Merged pull requests: 9
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 0
  • Average time to close issues: 13 days
  • Average time to close pull requests: N/A
  • Issue authors: 2
  • Pull request authors: 0
  • Average comments per issue: 2.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • mwpennell (10)
  • kbroman (5)
  • karthik (5)
  • sckott (3)
  • chrisfan24 (1)
  • chenqh0618 (1)
  • zhangrengang (1)
  • maelle (1)
  • Wipada-suksaensri (1)
  • lucaslima1618 (1)
  • RANSHOSHANI (1)
  • wtesto (1)
  • thm52126 (1)
  • Tbuchloh1 (1)
  • fbalao (1)
Pull Request Authors
  • kbroman (4)
  • orchid00 (2)
  • sckott (1)
  • karthik (1)
  • stevenysw (1)
  • richfitz (1)
Top Labels
Issue Labels
help wanted (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 406 last-month
  • Total docker downloads: 88,618
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 8
  • Total maintainers: 1
cran.r-project.org: chromer

Interface to Chromosome Counts Database API

  • Versions: 8
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 406 Last month
  • Docker Downloads: 88,618
Rankings
Forks count: 12.8%
Stargazers count: 19.8%
Average: 27.3%
Dependent packages count: 29.8%
Dependent repos count: 35.5%
Downloads: 38.4%
Maintainers (1)
broman@wisc.edu
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • R >= 2.15 depends
  • data.table * imports
  • dplyr * imports
  • httr * imports
  • stats * imports
  • roxygen2 >= 5.0.1 suggests
  • testthat * suggests
.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v2 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite