Fix spelling and grammar

.vscode/settings.json

@@ -0,0 +1,8 @@
+{
+    "cSpell.words": [
+        "epitope",
+        "epitopes",
+        "psuedotyping",
+        "wildtype"
+    ]
+}

introduction/getting-started/index.md

@@ -2,17 +2,16 @@
 
 ## Overview
 
-Using **`dms-viz`** involves two steps. First, using a command line tool called [`configure-dms-viz`](https://pypi.org/project/configure-dms-viz/), you specifcy some information about your dataset to generate a `.json` format specification file. Second, you open up the [web-based tool](https://dms-viz.github.io/) and upload your specification file to generate an interactive visualization. Below are some quickstart instructions to get you oriented.
+Using **`dms-viz`** involves two steps. First, using a command line tool called [`configure-dms-viz`](https://pypi.org/project/configure-dms-viz/), you specify some information about your dataset to generate a `.json` format specification file. Second, you open up the [web-based tool](https://dms-viz.github.io/) and upload your specification file to generate an interactive visualization. Below are some quickstart instructions to get you oriented.
 
 ::: tip Want to Skip Ahead?
-If you're insterested in the detailed command line API, check out the reference [here](/preparing-data/command-line-api/). If you've already formatted your data and you're ready to start visualizing it, check out the instructions for that [here](/visualizing-data/web-tool-api/).
+If you're interested in the detailed command line API, check out the reference [here](/preparing-data/command-line-api/). If you've already formatted your data and you're ready to start visualizing it, check out the instructions for that [here](/visualizing-data/web-tool-api/).
 :::
-
-## Prerequsites
+Prerequisites
 
 To start using **`dms-viz`** with your own data, you'll need to install the command line tool [`configure-dms-viz`](https://pypi.org/project/configure-dms-viz/). To use `configure-dms-viz`, you must ensure that you have the correct version of Python (3.9 or later) installed on your system.
 
-If you are unsure whether you have the correct version of Python installed, open a terminal window (Command Prompt in Windows, Terminal in macOS, or a terminal emulator in Linux) and type the following command and press Enter:
+If you are unsure whether you have the correct version of Python installed, open a terminal window (Command Prompt in Windows, Terminal in macOS, or a terminal emulator in Linux) type the following command and press Enter:
 
 ```bash
 python --version
@@ -36,7 +35,7 @@ Currently, `configure-dms-viz` is distributed on [PyPI](https://pypi.org/), allo
 pip install configure-dms-viz
 ```
 
-Now, `configure-dms-viz` should have been installed and you shouldn't see any error messages. You can double-check that the installation worked correctly typing the following into the terminal:
+Now, `configure-dms-viz` should have been installed and you shouldn't see any error messages. You can double-check that the installation worked correctly by typing the following into the terminal:
 
 ```bash
 configure-dms-viz --help
@@ -49,7 +48,7 @@ You should see the help message for the tool printed to the terminal.
 `configure_dms_viz` is a command-line tool designed to create a `JSON` format specification file for **`dms-viz`**. You provide the data that you'd like to visualize along with additional information to customize the analysis. The resulting specification file can be uploaded to [**`dms-viz`**](https://dms-viz.github.io/) for interactive visualization of your data. Below is an overview of the process of using `configure_dms_viz`.
 
 ::: tip Looking for more details?
-For a detailed explaination of the features of `configure_dms_viz` check out the reference [here](/preparing-data/command-line-api/).
+For a detailed explanation of the features of `configure_dms_viz` check out the reference [here](/preparing-data/command-line-api/).
 :::
 
 `configure-dms-viz` has two commands, `format` and `join`. To format a single dataset for **`dms-viz`**, you execute the `configure-dms-viz format` command with the required and optional arguments as needed:
@@ -98,7 +97,7 @@ configure-dms-viz format \
    --tooltip-cols "{'times_seen': '# Obsv', 'effect': 'Func Eff.'}"
 ```
 
-Here, we've specified that we want the dataset to be called `LyCoV-1404` and we've pointed to file location of the [input data](https://github.com/dms-viz/configure_dms_viz/blob/main/tests/sars2/escape/LyCoV-1404_avg.csv) and [sitemap](https://github.com/dms-viz/configure_dms_viz/blob/main/tests/sars2/site_numbering_map.csv). In addition, we've specified that we want to use the protein structure `6xr8` from the [RSCB PDB](https://www.rcsb.org/) and that we want to visualize the `escape_mean` column of the input dataset. We've also specified some _optional_ arguments including [additional data](/preparing-data/command-line-api/#join-data), [filters](/preparing-data/command-line-api/#filter-cols), [tooltips](/preparing-data/command-line-api/#tooltip-cols), and the [name](/preparing-data/command-line-api/#name) we want to show up for the metric we're visualizing.
+Here, we've specified that we want the dataset to be called `LyCoV-1404` and we've pointed to the file location of the [input data](https://github.com/dms-viz/configure_dms_viz/blob/main/tests/sars2/escape/LyCoV-1404_avg.csv) and [sitemap](https://github.com/dms-viz/configure_dms_viz/blob/main/tests/sars2/site_numbering_map.csv). In addition, we've specified that we want to use the protein structure `6xr8` from the [RSCB PDB](https://www.rcsb.org/) and that we want to visualize the `escape_mean` column of the input dataset. We've also specified some _optional_ arguments including [additional data](/preparing-data/command-line-api/#join-data), [filters](/preparing-data/command-line-api/#filter-cols), [tooltips](/preparing-data/command-line-api/#tooltip-cols), and the [name](/preparing-data/command-line-api/#name) we want to show up for the metric we're visualizing.
 
 The result of this command should be a message printed to the terminal that looks like this:
 
@@ -123,7 +122,7 @@ Success! The visualization json was written to 'tests/sars2/output/LyCoV-1404.js
 
 This message provides some information about the `configure-dms-viz format` run on your dataset. In addition to this message, there should be a `.json` file located where you specified the output path ([`tests/sars2/output/LyCoV-1404.json`](https://github.com/dms-viz/configure_dms_viz/blob/main/tests/sars2/output/LyCoV-1404.json)).
 
-This is how you can use `configure-dms-viz` to format a single dataset. You can optionally combine multiple datasets into a single `.json` specification file using the `configure-dms-viz join` command. this command takes a list of `.json` files as an arguments along with an optional description of the datasets. For more details on combining datasets, check out the [API](/preparing-data/command-line-api/).
+This is how you can use `configure-dms-viz` to format a single dataset. You can optionally combine multiple datasets into a single `.json` specification file using the `configure-dms-viz join` command. this command takes a list of `.json` files as arguments along with an optional description of the datasets. For more details on combining datasets, check out the [API](/preparing-data/command-line-api/).
 
 For now, since we're only visualizing a single dataset, we can skip this step. In the next section, you'll take this `.json` visualization file and visualize your data with [**`dms-viz`**](https://dms-viz.github.io/).
 
@@ -142,8 +141,7 @@ To upload a local file, you simply click on the `Upload Data` section and choose
 Since the `.json` file created above should now be stored locally on your machine, you can upload this file using this approach.
 
 ### Remote
-
-Alternativley, if your raw `.json` file is hosted somewhere online – like on GitHub, for example – you can provide the link to this file by clicking on the `Remote` button under the `Upload Data` section.
+Alternatively, if your raw `.json` file is hosted somewhere online – like on GitHub, for example – you can provide the link to this file by clicking on the `Remote` button under the `Upload Data` section.
 
 <div align="center">
   <img src="/assets/remote-upload-example.png" alt="Remote Upload" />

introduction/what-is-dms-viz/index.md

@@ -1,26 +1,26 @@
 # What is dms-viz?
 
-Hi there 👋, if you've got some mutation-level data that you want to view on an interactive 3D protein structure, you're in the right place! **`dms-viz`** is a tool that helps you take quantitative data associated with mutations to a protein and analyze that data using intutive visual summaries in the context of an interactive 3D protein structure. Visualizations created with **`dms-viz`** are intended to be _flexible_, _customizable_, and _shareable_.
+Hi there 👋, if you've got some mutation-level data that you want to view on an interactive 3D protein structure, you're in the right place! **`dms-viz`** is a tool that helps you take quantitative data associated with mutations to a protein and analyze that data using intuitive visual summaries in the context of an interactive 3D protein structure. Visualizations created with **`dms-viz`** are intended to be _flexible_, _customizable_, and _shareable_.
 
 ::: tip Ready to use the tool?
-You can skip to the [Quickstart](/introduction/getting-started/) to learn how to prepare your own data, or you can see what the visualization tool looks like [here](https://dms-viz.github.io/).
+You can skip to the [Quickstart](/introduction/getting-started/) to learn how to prepare your data, or you can see what the visualization tool looks like [here](https://dms-viz.github.io/).
 :::
 
 ## Purpose
 
 Understanding how mutations impact a protein's functions is valuable for many types of biological questions. High-throughput techniques such as deep-mutational scanning (DMS) have greatly expanded the number of mutation-function datasets. For instance, DMS has been used to determine how mutations to viral proteins affect antibody escape, receptor affinity, and essential functions such as viral genome transcription and replication.
 
-The mutation-based data generated by these approaches is often best understood in the context of a protein’s 3D structure; for instance, to assess questions like how mutations that affect antibody escape relate to the physical antibody binding epitope on the protein. However, current approaches for visualizing mutation data in the context of a protein’s structure are often cumbersome and require multiple steps and softwares. To streamline the visualization of mutation-associated data in the context of a protein structure, we developed a web-based tool, **`dms-viz`**. With **`dms-viz`**, users can straightforwardly visualize mutation-based data such as those from DMS experiments in the context of a 3D protein model in an interactive format.
+The mutation-based data generated by these approaches is often best understood in the context of a protein’s 3D structure; for instance, to assess questions like how mutations that affect antibody escape relate to the physical antibody binding epitope on the protein. However, current approaches for visualizing mutation data in the context of a protein’s structure are often cumbersome and require multiple steps and software. To streamline the visualization of mutation-associated data in the context of a protein structure, we developed a web-based tool, **`dms-viz`**. With **`dms-viz`**, users can straightforwardly visualize mutation-based data such as those from DMS experiments in the context of a 3D protein model in an interactive format.
 
 ## Why use dms-viz?
 
 - **Flexible Inputs**
 
-  Our command-line tool, `configure-dms-viz`, helps streamline data formatting by facillitating the integration of data from different sources into a singular, universal `JSON` specification file. Moreover, `configure-dms-viz` helps you define custom filters and tooltips, and identify common errors.
+  Our command-line tool, `configure-dms-viz`, helps streamline data formatting by facilitating the integration of data from different sources into a singular, universal `JSON` specification file. Moreover, `configure-dms-viz` helps you define custom filters and tooltips, and identify common errors.
 
 - **Customizable Visualizations**
 
-  We've designed **`dms-viz`** with customization in mind. You can tailor the appearance of the protein structure to fit your needs. Futhermore, you can extend the functionality of the tool with custom filters, tooltips, colors, and more.
+  We've designed **`dms-viz`** with customization in mind. You can tailor the appearance of the protein structure to fit your needs. Furthermore, you can extend the functionality of the tool with custom filters, tooltips, colors, and more.
 
 - **Shareable URLs**
 
@@ -30,7 +30,7 @@ The mutation-based data generated by these approaches is often best understood i
 
 **`dms-viz`** has two components:
 
-1. A command line interface (CLI) for formating data that was written in `Python` using the [click](https://click.palletsprojects.com/en/8.1.x/) API.
+1. A command line interface (CLI) for formatting data that was written in `Python` using the [click](https://click.palletsprojects.com/en/8.1.x/) API.
 2. A web-based visualization tool written in 'vanilla' `Javascript` using primarily the libraries [D3.js](https://d3js.org/) for making the visualizations and [NGL.js](https://nglviewer.org/#page-top) for creating interactive molecular structures.
 
 If you're interested in contributing, check out the [Contributing Guide](/project-info/contributing-guide/) for details.