From 922ea84d8e1f5e3038d73126e6641d4c149c72a7 Mon Sep 17 00:00:00 2001 From: Maria Valdez Cabrera Date: Fri, 6 Sep 2024 12:36:47 -0700 Subject: [PATCH 1/6] Adding logo to Homepage --- README.Rmd | 3 +++ 1 file changed, 3 insertions(+) diff --git a/README.Rmd b/README.Rmd index 162bb28..5544590 100644 --- a/README.Rmd +++ b/README.Rmd @@ -5,6 +5,9 @@ output: github_document ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE) ``` + +#HAPPI + `happi`: a **H**ierarchical **Ap**proach to **P**angenomics **I**nference ## What is `happi`? From f4fdbac566f40a4bd98882c4ba04abd89b5ef514 Mon Sep 17 00:00:00 2001 From: Maria Valdez Cabrera Date: Fri, 6 Sep 2024 12:48:12 -0700 Subject: [PATCH 2/6] Rendering the new homepage with the logo --- README.Rmd | 2 +- README.md | 2 ++ 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/README.Rmd b/README.Rmd index 5544590..8d896d4 100644 --- a/README.Rmd +++ b/README.Rmd @@ -6,7 +6,7 @@ output: github_document knitr::opts_chunk$set(echo = TRUE) ``` -#HAPPI +# HAPPI `happi`: a **H**ierarchical **Ap**proach to **P**angenomics **I**nference diff --git a/README.md b/README.md index c288d2f..43734d4 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,8 @@ +# HAPPI + `happi`: a **H**ierarchical **Ap**proach to **P**angenomics **I**nference From 7a1fba206eb64d03515323f3111455d6a96fa79a Mon Sep 17 00:00:00 2001 From: Maria Valdez Cabrera Date: Fri, 6 Sep 2024 17:26:11 -0700 Subject: [PATCH 3/6] Changing logo size slightly --- README.Rmd | 2 +- README.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/README.Rmd b/README.Rmd index 8d896d4..13b4421 100644 --- a/README.Rmd +++ b/README.Rmd @@ -6,7 +6,7 @@ output: github_document knitr::opts_chunk$set(echo = TRUE) ``` -# HAPPI +# HAPPI `happi`: a **H**ierarchical **Ap**proach to **P**angenomics **I**nference diff --git a/README.md b/README.md index 43734d4..6788a91 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ -# HAPPI +# HAPPI `happi`: a **H**ierarchical **Ap**proach to **P**angenomics **I**nference From c90987021b7b1a940bf28b2774a46f32732bf6e4 Mon Sep 17 00:00:00 2001 From: Maria Valdez Cabrera Date: Sat, 7 Sep 2024 11:59:36 -0700 Subject: [PATCH 4/6] Added placeholder for things microbial ecologist and others may like. Added link to published work --- README.Rmd | 27 ++++++++++++++++++++------- README.md | 5 +++-- 2 files changed, 23 insertions(+), 9 deletions(-) diff --git a/README.Rmd b/README.Rmd index 13b4421..6ba6208 100644 --- a/README.Rmd +++ b/README.Rmd @@ -8,14 +8,28 @@ knitr::opts_chunk$set(echo = TRUE) # HAPPI - `happi`: a **H**ierarchical **Ap**proach to **P**angenomics **I**nference + -## What is `happi`? +#### a **H**ierarchical **Ap**proach to **P**angenomics **I**nference + + `happi` is a method for modeling gene presence in pangenomics that leverages information about genome quality to improve inference. `happi` models the association between an experimental condition and gene presence where the **experimental condition** is the **primary predictor** of interest and **gene presence** is the **outcome** while incorporating user-chosen information on genome quality metrics (e.g. mean coverage, contamination, completion, etc...). You might be interested in using `happi` to conduct your pangenomics hypothesis testing if you work with fragmented genomes such as metagenome assembled genomes (MAGs). `happi` is currently distributed as an `R` package and can be installed using the instructions below. -## Where does `happi` fit into my workflow? +If you are a **microbial ecologist** or **bioinformatician**, some of the things that you may like about `happi` include + +- **AMY TO LIST ITEM 1** + +- **AMY TO LIST ITEM 2** + +If you are a **statistician**, things you may like about `happi` include + +- **AMY TO LIST ITEM 1** + +- **AMY TO LIST ITEM 2** + +### Where does `happi` fit into my workflow? If you're new to shotgun metagenomics we understand that things can feel overwhelming! On top of all the tools and names floating around you're probably wondering where does `happi` fit into the vast suite of bioinformatics tools for metagenomics data and how can you use it in your work? `happi` can be used *after* you have assembled, binned, annotated, and refined your genomes or metagenome-assembled genomes (MAGs) and as such it can be used with any bioinformatics workflow that conducts assembly, binning, annotation, and refinement. @@ -71,13 +85,12 @@ The Snakefile is customizable for your own input data and parameters. Please ref ## How do I export data from anvi'o for use in `happi`? - ## Citation -If you use `happi` please cite our work: +If you use `happi` please cite our work: -An open-access preprint is available [here](https://www.biorxiv.org/content/10.1101/2022.04.26.489591v1.full). +Trinh P, Clausen DS, Willis AD. happi: a hierarchical approach to pangenomics inference. Genome Biology. 2023;24(1):214-214. [Available here](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-023-03040-6) -## Issues/Requests +## Issues/Requests If you have any issues using our software or further questions please submit an issue [here](https://github.com/statdivlab/happi/issues). diff --git a/README.md b/README.md index 6788a91..5eb2a2f 100644 --- a/README.md +++ b/README.md @@ -3,8 +3,9 @@ # HAPPI - `happi`: a -**H**ierarchical **Ap**proach to **P**angenomics **I**nference + + +#### a **H**ierarchical **Ap**proach to **P**angenomics **I**nference ## What is `happi`? From 20aac00156236c3af5c20962ef72dd25ff658072 Mon Sep 17 00:00:00 2001 From: Maria Valdez Cabrera Date: Sat, 7 Sep 2024 12:01:09 -0700 Subject: [PATCH 5/6] Made sure README.md is fully updated to the last Rmd version --- README.md | 22 ++++++++++++++++++---- 1 file changed, 18 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 5eb2a2f..172f1a0 100644 --- a/README.md +++ b/README.md @@ -7,7 +7,7 @@ #### a **H**ierarchical **Ap**proach to **P**angenomics **I**nference -## What is `happi`? + `happi` is a method for modeling gene presence in pangenomics that leverages information about genome quality to improve inference. `happi` @@ -22,7 +22,20 @@ hypothesis testing if you work with fragmented genomes such as metagenome assembled genomes (MAGs). `happi` is currently distributed as an `R` package and can be installed using the instructions below. -## Where does `happi` fit into my workflow? +If you are a **microbial ecologist** or **bioinformatician**, some of +the things that you may like about `happi` include + +- **AMY TO LIST ITEM 1** + +- **AMY TO LIST ITEM 2** + +If you are a **statistician**, things you may like about `happi` include + +- **AMY TO LIST ITEM 1** + +- **AMY TO LIST ITEM 2** + +### Where does `happi` fit into my workflow? If you’re new to shotgun metagenomics we understand that things can feel overwhelming! On top of all the tools and names floating around you’re @@ -109,8 +122,9 @@ Please refer to the sample data files that have been provided in If you use `happi` please cite our work: -An open-access preprint is available -[here](https://www.biorxiv.org/content/10.1101/2022.04.26.489591v1.full). +Trinh P, Clausen DS, Willis AD. happi: a hierarchical approach to +pangenomics inference. Genome Biology. 2023;24(1):214-214. [Available +here](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-023-03040-6) ## Issues/Requests From d82ec4be07477b8b8a46d8dd28c8bb38191fa9e4 Mon Sep 17 00:00:00 2001 From: Maria Valdez Cabrera Date: Sat, 7 Sep 2024 13:03:57 -0700 Subject: [PATCH 6/6] Added R code to showcase syntax in Homepage --- README.Rmd | 24 +++++++++++++++++++++++- README.md | 26 +++++++++++++++++++++++++- 2 files changed, 48 insertions(+), 2 deletions(-) diff --git a/README.Rmd b/README.Rmd index 6ba6208..eadfca4 100644 --- a/README.Rmd +++ b/README.Rmd @@ -10,7 +10,7 @@ knitr::opts_chunk$set(echo = TRUE) -#### a **H**ierarchical **Ap**proach to **P**angenomics **I**nference +a **H**ierarchical **Ap**proach to **P**angenomics **I**nference `happi` is a method for modeling gene presence in pangenomics that leverages information about genome quality to improve inference. `happi` models the association between an experimental condition and gene presence where the **experimental condition** is the **primary predictor** of interest and **gene presence** is the **outcome** while incorporating user-chosen information on genome quality metrics (e.g. mean coverage, contamination, completion, etc...). @@ -60,6 +60,28 @@ functions through the `R` interactive session. You can follow the vignettes by r ``` utils::browseVignettes(package = "happi") ``` + +The syntax to use the main functions from `happi` in `R` is shown in the following example, + +``` +happi_results <- happi(outcome = presence_vector, covariate=x_matrix, quality_var= quality_vector) +happi_results$summary +``` + +where `presence_vector` is a length-n vector indicating the presence/absence (coded as 0 or 1) of the target gene, `x_matrix` is a n x p design matrix for the predictors of interest, and `quality_vector` is a length-n vector indicating the quality of the genome. + +To use `happi`'s nonparametric permutation testing approach, we could run the `happi()` function above with the extra argument `run_npLRT = TRUE` or we can take our `happi` results object as an input to the function `happi::npLRT()` as shown below. + +``` +perm_test_result <- npLRT(happi_results, + change_threshold = 0.1, + spline_df = 3, + nstarts = 1, + epsilon = 0, + firth = T, + method = "splines") +``` + An example snakemake workflow of `happi`'s usage has been made available under the `workflows/` folder of this github directory. To run the example workflow you'll need to install snakemake. We recommend creating a conda environment with your snakemake installation: ``` diff --git a/README.md b/README.md index 172f1a0..a05e39a 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,7 @@ -#### a **H**ierarchical **Ap**proach to **P**angenomics **I**nference +a **H**ierarchical **Ap**proach to **P**angenomics **I**nference @@ -92,6 +92,30 @@ the vignettes by running the following code in `R`: utils::browseVignettes(package = "happi") +The syntax to use the main functions from `happi` in `R` is shown in the +following example, + + happi_results <- happi(outcome = presence_vector, covariate=x_matrix, quality_var= quality_vector) + happi_results$summary + +where `presence_vector` is a length-n vector indicating the +presence/absence (coded as 0 or 1) of the target gene, `x_matrix` is a n +x p design matrix for the predictors of interest, and `quality_vector` +is a length-n vector indicating the quality of the genome. + +To use `happi`’s nonparametric permutation testing approach, we could +run the `happi()` function above with the extra argument +`run_npLRT = TRUE` or we can take our `happi` results object as an input +to the function `happi::npLRT()` as shown below. + + perm_test_result <- npLRT(happi_results, + change_threshold = 0.1, + spline_df = 3, + nstarts = 1, + epsilon = 0, + firth = T, + method = "splines") + An example snakemake workflow of `happi`’s usage has been made available under the `workflows/` folder of this github directory. To run the example workflow you’ll need to install snakemake. We recommend creating