Create a markdown table from prepreprint summaries

Usage

tt_preprints(preprints, cols = c("title", "summary"), width = c(1, 3))

Arguments

preprints: Output from get_preprints() followed by add_prompt() followed by add_summary().
cols: Columns to display in the resulting markdown table.
width: Vector of relative widths equal to length(cols).

Value

A tinytable table.

Examples

# Use built-in example data
example_preprints
#> # A tibble: 90 × 6
#>    subject        title                            url   abstract prompt summary
#>    <chr>          <chr>                            <chr> <chr>    <chr>  <chr>  
#>  1 bioinformatics Integrity and miss grouping as … http… "The hi… "I am… "The p…
#>  2 bioinformatics Sainsc: a computational tool fo… http… "Spatia… "I am… "Sains…
#>  3 bioinformatics BRACE: A novel Bayesian-based i… http… "Bayesi… "I am… "Alter…
#>  4 bioinformatics Topological embedding and direc… http… "Cancer… "I am… "Resea…
#>  5 bioinformatics SeuratExtend: Streamlining Sing… http… "Single… "I am… "Seura…
#>  6 bioinformatics An Evolutionary Statistics Tool… http… "We pre… "I am… "The \…
#>  7 bioinformatics A map of integrated cis-regulat… http… "Cis-re… "I am… "The a…
#>  8 bioinformatics MOSTPLAS: A Self-correction Mul… http… "Plasmi… "I am… "Plasm…
#>  9 bioinformatics Bootstrap Evaluation of Associa… http… "Motiva… "I am… "The a…
#> 10 bioinformatics Thermodynamic modeling of Csr/R… http… "Backgr… "I am… "Resea…
#> # ℹ 80 more rows
tt_preprints(example_preprints[1:2,])
#> 
#> +-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
#> | title                                                                                                                                                                               | summary                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
#> +=====================================================================================================================================================================================+=========================================================================================================================================================================================================================================================================================================================================================================================================================================================================================+
#> | [Integrity and miss grouping as support for clusters in agglomerative hierarchical methods: the R-package octopucs](http://biorxiv.org/cgi/content/short/2024.08.01.606070v1?rss=1) | The proposed method assesses cluster support throughout hierarchical analyses by compiling a consensus topology and using ecological concepts of reciprocal complementarities to define cluster integrity and contamination. This approach allows for building support for groups even when there is partial membership match after resampling, and was implemented in the R package octopucs, which showed robust detection of changes in group memberships compared to other methods. |
#> +-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
#> | [Sainsc: a computational tool for segmentation-free analysis of in-situ capture](http://biorxiv.org/cgi/content/short/2024.08.02.603879v1?rss=1)                                    | Sainsc is a computational tool that enables segmentation-free analysis of spatially resolved transcriptomics data, allowing for accurate cell-type assignment at the subcellular level without requiring manual cell border delineation. The tool provides efficient processing of high-resolution spatial data and can generate maps of cell types with corresponding confidence scores, making it a valuable resource for biomedical researchers working with complex tissue samples. |
#> +-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+