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Because no one can read your mind (yet)
A README is a text file that introduces and explains a project. It contains information that is commonly required to understand what the project is about.
It's an easy way to answer questions that your audience will likely have regarding how to install and use your project and also how to collaborate with you.
Anyone who is working on a programming project, especially if you want others to use it or contribute.
Definitely before you show a project to other people or make it public. You might want to get into the habit of making it the first file you create in a new project.
In the top level directory of the project. This is where someone who is new to your project will start out. Code hosting services such as GitHub, Bitbucket, and GitLab will also look for your README and display it along with the list of files and directories in your project.
While READMEs can be written in any text file format, the most common one that is used nowadays is Markdown. It allows you to add some lightweight formatting. You can learn more about it at the CommonMark website, which also has a helpful reference guide and an interactive tutorial.
Some other formats that you might see are plain text, reStructuredText (common in Python projects), and Textile.
You can use any text editor. There are plugins for many editors (e.g. Atom, Emacs, Sublime Text, Vim, and Visual Studio Code) that allow you to preview Markdown while you are editing it.
You can also use a dedicated Markdown editor like Typora or an online one like StackEdit or Dillinger. You can even use the editable template below.
Markdown Input (editable)
<textarea id="markdown-input" class="bg-white w-full px-4 py-6 rounded-lg font-mono text-sm" style="height: 2028px !important;"># Sequence Analysis of ORF24 from Fowl Aviadenovirus CThis project performs a computational sequence analysis and functional
inference of ORF24 from Fowl aviadenovirus C using Biopython
and standard bioinformatics workflows.
The primary goal is to demonstrate end-to-end sequence handling, quality
control, homology search, and biological interpretation based on
sequence conservation.
The project is designed as an educational and reproducible bioinformatics pipeline, emphasizing correct methodology, documentation, and biological reasoning rather than experimental validation.
- Retrieve and process a viral ORF sequence
- Perform basic sequence quality checks
- Conduct homology search using BLASTp
- Annotate the sequence based on similarity to known proteins
- Provide a biologically sound interpretation grounded in sequence conservation
- Organism: Fowl aviadenovirus C
- Gene / ORF: ORF24
- Sequence Type: Protein (amino acid sequence)
- Source: Public viral genome databases (e.g., NCBI)
- Python (≥3.x)
- Biopython
SeqIOSeqNCBIWWW/NCBIXML(for BLAST handling)
- BLASTp
- Git & GitHub (version control and reproducibility)
-
Sequence Retrieval
- Import ORF24 protein sequence in FASTA format
- Parse and validate sequence using Biopython
-
Quality Control
- Verify sequence length and composition
- Check for invalid or ambiguous residues
-
Homology Search
- Perform BLASTp against protein databases
- Identify homologous ORFs in related adenoviruses
-
Functional Annotation
- Infer potential function based on conserved homologs
- Evaluate degree of conservation across viral species
-
Biological Interpretation
- Translate computational results into biological insight
The selected sequence represents ORF24 from Fowl aviadenovirus C.
Based on BLASTp analysis, this protein shows similarity to ORF proteins
found in other related adenoviruses, suggesting that it is conserved
across viral species.
The conservation of ORF24 indicates that it is likely to have an essential role in the viral life cycle. Proteins preserved across related viruses are typically involved in critical viral processes necessary for survival and propagation.
Although the exact molecular function of ORF24 has not been experimentally confirmed, the observed sequence similarity suggests potential involvement in viral replication, structural organisation, or virus–host interactions.
Overall, this functional prediction is derived from homology-based inference and sequence conservation, and therefore represents a computational hypothesis rather than experimental validation.
- No wet-lab or experimental validation is included
- Results should be interpreted as predictive, not definitive
</textarea>
Rendered
This project performs a computational sequence analysis and functional inference of ORF24 from Fowl aviadenovirus C using Biopython and standard bioinformatics workflows.
The primary goal is to demonstrate end-to-end sequence handling, quality
control, homology search, and biological interpretation based on
sequence conservation.
The project is designed as an educational and reproducible bioinformatics pipeline, emphasizing correct methodology, documentation, and biological reasoning rather than experimental validation.
- Retrieve and process a viral ORF sequence
- Perform basic sequence quality checks
- Conduct homology search using BLASTp
- Annotate the sequence based on similarity to known proteins
- Provide a biologically sound interpretation grounded in sequence conservation
- Organism: Fowl aviadenovirus C
- Gene / ORF: ORF24
- Sequence Type: Protein (amino acid sequence)
- Source: Public viral genome databases (e.g., NCBI)
- Python (≥3.x)
- Biopython
SeqIOSeqNCBIWWW/NCBIXML(for BLAST handling)
- BLASTp
- Git & GitHub (version control and reproducibility)
-
Sequence Retrieval
- Import ORF24 protein sequence in FASTA format
- Parse and validate sequence using Biopython
-
Quality Control
- Verify sequence length and composition
- Check for invalid or ambiguous residues
-
Homology Search
- Perform BLASTp against protein databases
- Identify homologous ORFs in related adenoviruses
-
Functional Annotation
- Infer potential function based on conserved homologs
- Evaluate degree of conservation across viral species
-
Biological Interpretation
- Translate computational results into biological insight
The selected sequence represents ORF24 from Fowl aviadenovirus C.
Based on BLASTp analysis, this protein shows similarity to ORF proteins
found in other related adenoviruses, suggesting that it is conserved across viral species.
The conservation of ORF24 indicates that it is likely to have an essential role in the viral life cycle. Proteins preserved across related viruses are typically involved in critical viral processes necessary for survival and propagation.
Although the exact molecular function of ORF24 has not been experimentally confirmed, the observed sequence similarity suggests potential involvement in viral replication, structural organisation, or virus–host interactions.
Overall, this functional prediction is derived from homology-based inference and sequence conservation, and therefore represents a computational hypothesis rather than experimental validation.
- No wet-lab or experimental validation is included
- Results should be interpreted as predictive, not definitive
Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information.
Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors.
On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method.
Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.
Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.
Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc.
State if you are open to contributions and what your requirements are for accepting them.
For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self.
You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
For open source projects, say how it is licensed.
If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
Not all of the suggestions here will make sense for every project, so it's really up to the developers what information should be included in the README.
Check out Awesome README for a list of more resources.
README.md (or a different file extension if you choose to use a non-Markdown file format). It is traditionally uppercase so that it is more prominent, but it's not a big deal if you think it looks better lowercase.
Please don't hesitate to open an issue or pull request. You can also send me a message on Twitter.
Scientists and companies like Facebook and Neuralink (presumably) are working on it. Perhaps in the future, you'll be able to attach a copy of your thoughts and/or consciousness to your projects. In the meantime, please make READMEs.
A README is a crucial but basic way of documenting your project. While every project should at least have a README, more involved ones can also benefit from a wiki or a dedicated documentation website. GitHub, Bitbucket, and GitLab all support maintaining a wiki alongside your project, and here are some tools and services that can help you generate a documentation website:
And to learn more about technical documentation in general, consider reading these books (I may earn commissions if you buy through these links):
- Docs for Developers: An Engineer’s Field Guide to Technical Writing
- Developing Quality Technical Information: A Handbook for Writers and Editors
- Docs Like Code: Collaborate and Automate to Improve Technical Documentation
- The Product is Docs: Writing Technical Documentation in a Product Development Group
If your project is open source, it's important to include a license. You can use this website to help you pick one.
Make a README is inspired by Keep a Changelog. A changelog is another file that is very useful for programming projects.
Just
having a "Contributing" section in your README is a good start. Another
approach is to split off your guidelines into their own file (CONTRIBUTING.md). If you use GitHub and have this file, then anyone who creates an issue or opens a pull request will get a link to it.
You can also create an issue template and a pull request template. These files give your users and collaborators templates to fill in with the information that you'll need to properly respond. This helps to avoid situations like getting very vague issues. Both GitHub and GitLab will use the templates automatically.
Make a README is maintained by Danny Guo, hosted on GitHub with a MIT license, and powered by Netlify.
As an Amazon Associate, I earn from qualifying purchases.
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