/** * file: chatgpt_karbytes_02august2025_p0.txt * type: plain-text * date: 06_AUGUST_2025 * author: karbytes * license: PUBLIC_DOMAIN */ The following is a plain-text transcript of a conversation between karbytes and ChatGPT-4o which took place between 11:59PM Pacific Standard Time on 01_AUGUST_2025 and 11:59PM Pacific Standard Time on 02_AUGUST_2025. The conversation pertains to karbytes preparing to incorporate a FASTA file of karbytes' entire human genome into karbytes' blogging website (which is named Karbytes For Life Blog dot WordPress dot Com). The ChatGPT conversation which is featured in this plain-text file is a follow-up to the older ChatGPT conversation which is archived at the following Uniform Resource Locator: https://raw.githubusercontent.com/karlinarayberinger/KARLINA_OBJECT_extension_pack_46/main/chatgpt_karbytes_24july2025_p0.txt * * * karbytes: I'm saving up money to get my whole genome sequenced with Dante Labs and was wondering if the resulting FASTA format file I would be downloading could be uploaded to GitHub (given that it is a much larger file than 25 megabytes). ChatGPT: Good question — you’re right to consider file size and GitHub’s limits before planning to upload your whole genome FASTA. Here are the key points: 1. File size expectations A human whole genome in FASTA format (just the raw sequence, no quality scores) is usually around 3–4 GB. If you also get a FASTQ file (with quality scores), that can easily exceed 100 GB. A compressed FASTA (like .fa.gz) might shrink to ~800 MB – 1 GB, but still well above 25 MB. 2. GitHub file size limits Individual file upload limit: 100 MB (hard limit on the web interface). GitHub encourages keeping repos under 1 GB total. For larger files (up to 2 GB each), you need to use Git Large File Storage (Git LFS). Git LFS works, but it comes with bandwidth quotas: free plan allows 1 GB storage & 1 GB bandwidth per month (you’d need to pay for more if people actually download the file often). 3. Practical options Git LFS: Viable if you want your genome on GitHub and are okay with potentially paying for extra storage/bandwidth. External hosting + GitHub link: Store the FASTA file in a large file service (e.g. Google Drive, Dropbox, Internet Archive, Zenodo, or even your own server) and link from your GitHub repo. This avoids GitHub’s LFS costs. Chunking: Split the FASTA into multiple parts under 100 MB each and upload separately, though this is clunky. 4. Privacy consideration Keep in mind: uploading your genome publicly is effectively irreversible. Anyone could download it, and it contains identifying information. If you want it public, GitHub is technically fine (with Git LFS), but you may also want a repository that’s deliberately oriented toward data hosting (like Zenodo, Dryad, or the Internet Archive). ✅ So, short answer: Yes — you could upload your FASTA to GitHub, but only if you use Git LFS. Otherwise, the file size is too big. If you’d like to avoid GitHub LFS quotas, I’d recommend hosting the file externally and just linking to it from your repo. Do you want me to show you how to set up Git LFS for a large file like your genome FASTA (so you could still keep it in your GitHub repo), or would you prefer I show you the external hosting route? karbytes: What is Git LFS? ChatGPT: Great question 👍 — Git LFS (short for Git Large File Storage) is an extension to Git that allows you to version and store files that are too large for normal Git tracking, such as big datasets, videos, audio files, or (in your case) genome FASTA files. Here’s a breakdown: 🔹 Why Git LFS Exists Standard Git stores the entire history of every file in your repo. That’s fine for text/code, but with big files (like a 3 GB FASTA), Git would: Quickly blow up repo size. Make clones and pulls painfully slow. Often exceed GitHub’s 100 MB per-file limit. Git LFS solves this by storing only a small pointer file in the repo, while the actual big file lives in a special LFS storage server. 🔹 How Git LFS Works You install Git LFS on your machine. You tell Git LFS which file types to track (e.g. *.fasta). When you add & commit those files, Git saves only a pointer file in your repo. The actual big file is uploaded to GitHub’s LFS servers. When someone clones your repo, Git LFS downloads the real files separately. 🔹 GitHub LFS Limits Free Plan: 1 GB of LFS storage 1 GB of LFS bandwidth per month Paid plans allow more (you can buy extra storage/bandwidth in 50 GB packs). Without LFS, you can’t push files bigger than 100 MB to GitHub at all. 🔹 Basic Example [bash] # Install Git LFS (one-time) git lfs install # Tell Git LFS to track FASTA files git lfs track "*.fasta" # Add the .gitattributes file Git LFS created git add .gitattributes # Add your genome file git add genome.fasta # Commit git commit -m "Add whole genome FASTA via Git LFS" # Push to GitHub git push origin main [end bash] Now your repo will contain a tiny pointer file for genome.fasta, while the real FASTA is on GitHub’s LFS server. 🔹 Analogy Think of Git LFS like a coat check: Git repo: keeps the claim ticket (pointer). LFS storage: holds the actual heavy coat (your genome). When you (or others) need the coat, Git LFS fetches it using the claim ticket. ⚡ Question for you: Do you plan for your genome FASTA to be publicly downloadable from GitHub, or mostly just stored there for your own archival purposes? That will help me suggest whether Git LFS is the right path or if external hosting might suit you better. karbytes: I am trying to make my genome FASTA publicly downloadable (and also saveable to the WayBack Machine). Would I be able to do that if I break the FASTA file into chunks and then upload those chunk files? ChatGPT: Yes — breaking your genome FASTA into chunks is a workable strategy for publishing it on GitHub without Git LFS, though there are some trade‑offs to consider. 🔹 How Chunking Could Work Split your FASTA into multiple files, each <100 MB (the GitHub per‑file hard limit). Upload those files into your repo (GitHub web interface or Git). Provide a script or instructions for how to recombine the chunks back into the original FASTA. Example: Splitting [bash] # Split into 95 MB chunks split -b 95M genome.fasta genome_part_ [end bash] This produces files like: [preformatted_text] genome_part_aa genome_part_ab genome_part_ac ... [end preformatted_text] Example: Rejoining [bash] cat genome_part_* > genome.fasta [end bash] That restores the original FASTA. 🔹 Pros ✅ No need for Git LFS (so no bandwidth/storage quotas). ✅ Keeps everything in one GitHub repo (and thus archiveable via the WayBack Machine). ✅ Works with GitHub’s 100 MB hard limit. ✅ WayBack Machine would capture each chunk file separately. 🔹 Cons ❌ Inconvenient for users (they must download multiple files and reassemble). ❌ More cluttered repo (dozens of parts for a 3–4 GB file). ❌ Less efficient for archival: the WayBack Machine may need to crawl many separate URLs. ❌ Some risk of human error when recombining. 🔹 Alternative for Easier Access If your goal is public download + WayBack Machine archiving, you might get better results by: Hosting the full FASTA on Internet Archive (which allows multi‑GB files with no quota). Linking that file from your GitHub repo. The WayBack Machine will capture both the GitHub page and the external download link. This way, your GitHub repo holds the “pointer” (and possibly a small sample or README), while the full genome lives in a more data‑friendly host. ✅ Answer: Yes, you can split your FASTA into <100 MB chunks and upload them to GitHub, then provide a recombination method. It will work, and the WayBack Machine will archive each chunk. But for a smoother experience, hosting the full FASTA on a big‑file‑friendly service (like Internet Archive) and linking from GitHub might be cleaner. Do you want me to draft a step‑by‑step plan for doing the chunked GitHub upload method so you can maximize WayBack Machine archival, or would you prefer I outline the Internet Archive route (which might be more user‑friendly)? karbytes: Are there upload or storage size limits for files being stored on Google Drive? ChatGPT: Yes — Google Drive does have file upload and storage limits, but they’re much more generous than GitHub. Here’s a breakdown (as of 2025): 🔹 Google Drive Upload & Storage Limits Per‑File Size Limit You can upload files up to 5 TB each, provided your account has enough available storage space. So your whole genome FASTA (3–4 GB) is well within the limit. Even a full FASTQ (100+ GB) fits comfortably, if you have storage space. Total Storage Space Depends on your plan: Free Google account: 15 GB total shared across Drive, Gmail, and Google Photos. Google One paid plans: 100 GB, 200 GB, 2 TB, and higher tiers (up to 30 TB). Daily Upload Limits Up to 750 GB per day across all files. Files larger than 750 GB can still be uploaded, but the remainder of that file will finish uploading (you just can’t start new uploads that day). File Types Virtually any type is allowed, including .fasta, .fastq, .vcf, etc. 🔹 Public Access / Sharing You can set a file’s permissions to “Anyone with the link can view” for public access. However, Google Drive links sometimes expire or get flagged if the file is heavily downloaded. The WayBack Machine can capture the link page but often can’t archive the actual file contents, since Google Drive requires a special request for the file download. 🔹 Practical Implication for Your Genome FASTA Google Drive easily supports a 3–4 GB FASTA file. But: if you want archival permanence (especially with the WayBack Machine), Drive isn’t ideal. The WayBack Machine usually won’t archive the actual genome file — just the Drive download page. For permanence, the Internet Archive (archive.org) or Zenodo are better choices, since those hosts allow direct archival of the actual data file. ✅ Answer: Google Drive allows files up to 5 TB (far larger than your genome FASTA), so storage space isn’t the issue — but Drive links aren’t always permanent and don’t play well with WayBack Machine. If permanence and public archival are priorities, Internet Archive or Zenodo are better than Drive. ⚡ Do you want me to compare Google Drive vs Internet Archive vs GitHub (chunked) specifically for your use case (public genome FASTA + WayBack Machine archival)? That might help narrow down the best option. karbytes: Are there file size limits for files which are uploaded to my Internet Archive library? ChatGPT: Internet Archive (Archive.org) is a great option for hosting and preserving large files. Here's how it handles large uploads: 📤 File Size & Upload Limits No strict hard limit on file size or number of files. You can upload very large files. However, for stability: It’s recommended to keep individual files under ~50 GB Ideally, each item (which may contain multiple files) should be under about 500 GB and fewer than ~1000 files per item. Some users have successfully uploaded files much larger than 50 GB, but uploads over that threshold may fail or timeout. Older accounts report an internal timeout (around 24-hour mark), which caused uploads over ~4 GB to fail; resuming or breaking into smaller files helped. There’s also an overall recommendation to keep items under ~400 GiB for reliability during creation and derivation (processing). 🧠 Practical Guidance for Your Genome File A 3–4 GB FASTA (possibly compressed to ~800 MB) is well within safe upload size. You can upload it as a single file, ideally under ~50 GB, with no issues. If you also include additional files (like metadata, README, etc.), ensure the total remains under ~500 GB and fewer than ~1000 files per item. If you ever need to upload files above ~50 GB, consider splitting into smaller parts or using the BitTorrent upload method, which supports resumable multi-day uploads and is more robust for very large datasets. ✅ Summary Table [preformatted_text] Item ---------------------------------------| Recommendation ----------------------------| Notes Single FASTA (~3–4 GB) ---------------------| ✅ Safe -----------------------------------| Well within limits Compressed FASTA (~800 MB) -----------------| ✅ Safe -----------------------------------| Ideal for compact storage Large files (~>50 GB) ----------------------| ⚠️ Risky ----------------------------------| May timeout or fail; splitting recommended Entire item size + all files ---------------| 👍 Keep < 500 GB & < 1000 files -----------| Helps maintain stability and derivation processing [end preformatted_text] 🧩 What About Archiving with Wayback Machine? Internet Archive fully archives uploaded files—including your genome FASTA—so the actual data is preserved, not just a download page (unlike Google Drive). If always-online time is a concern, consider using the Torrent upload method: Archives fetch via BitTorrent, allowing interrupted uploads to resume and ensuring full file integrity. 🧠 Final Verdict Yes, you can comfortably upload your genome FASTA to your Internet Archive library. For best results: Upload as a single file under ~50 GB, or compressed to under 1 GB. Keep the total item (including other files) under ~500 GB and fewer than ~1000 files. If future uploads might exceed these, consider torrent-based uploading or splitting. Would you like help drafting a step‑by‑step upload plan—possibly using the torrent approach for maximum reliability and archival quality? karbytes: It seems that files which are hosted in my Internet Archive library cannot be saved to the WayBack Machine. ChatGPT: You’ve noticed something important 👍 — you’re right: Files you upload into your Internet Archive library (archive.org items) don’t get separately “Wayback‑captured” the way ordinary web pages do. Here’s why, and what it means for your genome FASTA: 🔹 Why Your Internet Archive Uploads Aren’t in the Wayback Machine The Wayback Machine is a web crawler: it snapshots publicly available web pages and the resources linked on them. The Internet Archive library (your uploads) is a different system: when you upload to Archive.org, your files are stored in their data repository, not automatically crawled and mirrored into the Wayback Machine. So a file in your Internet Archive library will live at a permanent archive.org URL (like https://archive.org/details/your_item_name) but won’t also show up if you try to “Save Page Now” the file link to the Wayback Machine. 🔹 Key Distinction [preformatted_text] Feature ------------------| Wayback Machine ----------------------------------------| Internet Archive Library Source -------------------| Automated (or manual) web snapshots --------------------| Direct user uploads Persistence --------------| Mirrors web pages, prone to robots.txt deletions -------| Long‑term repository, much more stable File capture -------------| Often skips large/binary files -------------------------| Stores full original files you upload Your genome FASTA --------| May fail (too large / crawler limits) ------------------| ✅ Works fine, permanent item hosting [end preformatted_text] 🔹 What This Means for You If your main goals are: Public access to your genome FASTA Long‑term archival (not depending on third‑party servers staying online) → The Internet Archive library is actually the better place than trying to force the Wayback Machine to capture a 3–4 GB FASTA. The Wayback Machine is ideal for HTML pages and small media. For large scientific data, Archive.org’s library service is what researchers use (think datasets, audio/video collections, etc.). 🔹 Hybrid Approach (if you want both) Upload your genome FASTA to Internet Archive library (for permanent hosting). Create a GitHub page or blog post describing it, with a link to the archive.org item. Then use Wayback Machine → Save Page Now on that GitHub/blog post page. This way, the Wayback Machine preserves the page and the link, while the full file is stored in the Internet Archive library. That gives you both the Wayback snapshot of the description/link and the permanent Internet Archive hosting of the genome file. ✅ Bottom line: You’re correct — your Internet Archive uploads won’t themselves be Wayback‑saved, but they don’t need to be. Instead, you can Wayback‑save the page that links to them, ensuring both discoverability and permanence. ⚡ Would you like me to show you how to structure a GitHub page or blog entry so the Wayback Machine capture will nicely index and preserve the link to your genome FASTA on Archive.org? karbytes: I think it is best that I do the following: (a) upload my entire genome FASTA file to my Internet Archive library and provide a hyperlink to that Internet Archive file library on a special page of my website for referencing my whole genome data and (b) breaking my FASTA file into multiple smaller text files which are stored on my GitHub account and which are referenced via raw file hyperlinks on that genome web page of my blog (so that those parts files can be saved to the WayBack Machine). Also, I would link to a program which would recombine those parts files into the original FASTA file and link that program file to that genome page of my blog. ChatGPT: That’s an excellent plan — it combines the permanence and stability of the Internet Archive with the Wayback‑friendly granular backup of GitHub. Let’s break down what you outlined so you can see the benefits and any adjustments you might consider. ✅ Your Proposed Strategy (a) Full Genome on Internet Archive Upload entire FASTA to your Internet Archive library. Link to it from a dedicated “My Genome” page on your blog. This ensures a single permanent copy, accessible for scientific use, without chunking. Benefits: Archive.org is well‑suited to multi‑GB files. Provides a canonical, stable file location. Good discoverability (Archive.org content is indexed by search engines). (b) Chunked FASTA on GitHub Use split to break the FASTA into <100 MB text files. Upload chunks to GitHub (normal repo, no LFS needed). Use raw GitHub links to reference each chunk from your genome page. Wayback Machine can crawl and preserve each chunk. Benefits: Each chunk is Wayback‑savable (GitHub raw files are standard HTTPS). Redundancy: if Archive.org is unavailable, chunks remain retrievable. Works around GitHub’s 100 MB per‑file limit. (c) Recombination Program Provide a script that reconstructs the full FASTA from chunks. Example script (Bash): [bash] #!/bin/bash # Usage: ./recombine_genome.sh output.fasta cat genome_part_* > "$1" echo "Recombined genome saved as $1" [end bash] Or a cross‑platform Python script for wider accessibility: [python] # recombine_genome.py import sys import glob if len(sys.argv) < 2: print("Usage: python recombine_genome.py output.fasta") sys.exit(1) with open(sys.argv[1], "wb") as out: for part in sorted(glob.glob("genome_part_*")): with open(part, "rb") as f: out.write(f.read()) print(f"Recombined genome saved as {sys.argv[1]}") [end python] Benefits: Ensures anyone can reconstruct the full FASTA. Preserves scientific usability. 📌 Suggested Structure for Your Genome Page Here’s a clean outline for the special blog page: Title: My Whole Genome (FASTA Format) Introduction: “This page hosts my entire human genome in FASTA format, made publicly available for open scientific reference. Below you will find permanent archive and Wayback‑savable copies.” Download Options: Full FASTA (Internet Archive): [Link] Chunked FASTA (GitHub, Wayback‑savable): Part 1 [Raw GitHub Link] Part 2 [Raw GitHub Link] … Recombination Script: [GitHub Link to Script] Instructions: Download all FASTA parts. Download the recombination script. Run the script to reassemble the full genome. License / Disclaimer: (e.g. This genome is released into the public domain for educational and research use.) 🔹 Why This Hybrid Plan is Solid Resiliency: Two different archives (Internet Archive + GitHub + Wayback). Permanence: Archive.org ensures long‑term stability. Redundancy: Wayback snapshots of GitHub parts protect against loss. Usability: With a provided recombination script, your genome remains scientifically usable. ⚡ If you’d like, I can generate a ready‑to‑use HTML snippet for your genome page (with placeholders for the Archive.org and GitHub links) so you can drop it straight into your WordPress blog. Would you like me to do that? karbytes: Yes please! ChatGPT: Perfect 👍 I’ll make a clean, copy‑paste‑ready HTML snippet for your WordPress genome page. You can just swap in the real links once your uploads are ready. Here’s the draft: [html]

My Whole Genome (FASTA Format)

This page hosts my entire human genome in FASTA format, made publicly available for open scientific reference and archival purposes. Two download options are provided below: a single permanent file hosted on the Internet Archive and a Wayback Machine–savable version split into smaller parts hosted on GitHub. A recombination script is also provided to rebuild the genome from the parts files.

Full Genome (Single File)

Download the entire FASTA file from the Internet Archive:
Internet Archive Genome FASTA

Chunked Genome (GitHub Parts)

Download all parts below. Each part is under 100 MB for GitHub compatibility and Wayback Machine archiving. After downloading all parts, use the recombination script (see next section) to rebuild the full genome FASTA.

Recombination Script

Use the following script to recombine the genome parts into a single FASTA file:

Instructions

  1. Download either the full FASTA file (Internet Archive) or all GitHub parts.
  2. If using the GitHub parts, also download the recombination script.
  3. Run the script on your local computer to rebuild the FASTA file.
  4. The final file will be your full genome FASTA.

License & Disclaimer

This genome is released into the public domain for educational and research use. Use at your own discretion.

[end html] 🔹 What You’ll Need to Do Replace: YOUR_ARCHIVE_ITEM_NAME with your Internet Archive item slug. YOUR_GITHUB_USERNAME/YOUR_REPO with your actual GitHub username and repo name. Add as many
  • entries under Chunked Genome as needed. Upload the recombination scripts to GitHub and link them. Publish this page on your WordPress site. ⚡ If you’d like, I can also give you the ready‑to‑use Bash and Python recombination scripts (with comments and error‑handling) so you don’t have to write them yourself. Would you like me to prep those too? karbytes: Yes please! ChatGPT: Excellent 👍 — here are both Bash and Python recombination scripts, with comments and error handling, so your readers can reliably reconstruct the genome FASTA from your GitHub parts. 🐚 Bash Recombination Script (recombine_genome.sh) [bash] #!/bin/bash # --------------------------------------------------------- # Script: recombine_genome.sh # Purpose: Recombine genome FASTA parts into one file. # Usage: ./recombine_genome.sh output.fasta # --------------------------------------------------------- # Check for correct number of arguments if [ "$#" -ne 1 ]; then echo "Usage: $0 output.fasta" exit 1 fi OUTPUT_FILE="$1" # Check for presence of parts if ls genome_part_* 1> /dev/null 2>&1; then echo "Combining genome_part_* files into $OUTPUT_FILE ..." cat genome_part_* > "$OUTPUT_FILE" echo "Done! Output saved as $OUTPUT_FILE" else echo "Error: No genome_part_* files found in the current directory." exit 1 fi [end bash] Instructions for users: [bash] chmod +x recombine_genome.sh ./recombine_genome.sh my_genome.fasta [end bash] 🐍 Python Recombination Script (recombine_genome.py) [python] #!/usr/bin/env python3 """ --------------------------------------------------------- Script: recombine_genome.py Purpose: Recombine genome FASTA parts into one file. Usage: python recombine_genome.py output.fasta --------------------------------------------------------- """ import sys import glob import os # Ensure output file argument is provided if len(sys.argv) != 2: print("Usage: python recombine_genome.py output.fasta") sys.exit(1) output_file = sys.argv[1] parts = sorted(glob.glob("genome_part_*")) # Check that parts exist if not parts: print("Error: No genome_part_* files found in the current directory.") sys.exit(1) print(f"Combining {len(parts)} genome parts into {output_file}...") with open(output_file, "wb") as out: for part in parts: print(f" - Adding {part}") with open(part, "rb") as f: out.write(f.read()) print(f"Done! Output saved as {output_file}") [end python] Instructions for users: [bash] python recombine_genome.py my_genome.fasta [end bash] ✅ Notes for Your Blog Page Place these two scripts in your GitHub repo along with the genome chunks. On your genome page, link to both scripts (so readers can choose whichever language works for them). If you want, you can also provide a checksum file (like SHA256) of the recombined FASTA so readers can verify integrity. ⚡ Would you like me to also create a checksum generator script (so users can verify the recombined genome FASTA matches your original file exactly)? That would make your archive more robust and scientifically trustworthy. karbytes: Yes please! ChatGPT: Perfect 👍 — adding a checksum verification step is a very smart idea, especially for something as critical as your genome FASTA. It ensures that anyone who reconstructs the file from your GitHub parts can confirm it’s bit‑for‑bit identical to the original. Here’s a ready‑to‑use checksum generator & verifier in both Bash and Python. 🐚 Bash Checksum Script (genome_checksum.sh) [bash] #!/bin/bash # --------------------------------------------------------- # Script: genome_checksum.sh # Purpose: Generate and/or verify SHA256 checksum for genome FASTA # Usage: # ./genome_checksum.sh generate my_genome.fasta # ./genome_checksum.sh verify my_genome.fasta checksum.txt # --------------------------------------------------------- if [ "$1" == "generate" ] && [ "$#" -eq 2 ]; then sha256sum "$2" > checksum.txt echo "Checksum saved to checksum.txt" elif [ "$1" == "verify" ] && [ "$#" -eq 3 ]; then sha256sum -c "$3" else echo "Usage:" echo " $0 generate " echo " $0 verify " exit 1 fi [end bash] Example Usage [bash] chmod +x genome_checksum.sh # Generate checksum ./genome_checksum.sh generate my_genome.fasta # Verify checksum later ./genome_checksum.sh verify my_genome.fasta checksum.txt [end bash] 🐍 Python Checksum Script (genome_checksum.py) [python] #!/usr/bin/env python3 """ --------------------------------------------------------- Script: genome_checksum.py Purpose: Generate and/or verify SHA256 checksum for genome FASTA Usage: python genome_checksum.py generate my_genome.fasta python genome_checksum.py verify my_genome.fasta checksum.txt --------------------------------------------------------- """ import hashlib import sys def sha256sum(filename): h = hashlib.sha256() with open(filename, "rb") as f: for chunk in iter(lambda: f.read(8192), b""): h.update(chunk) return h.hexdigest() if len(sys.argv) < 3: print("Usage:") print(" python genome_checksum.py generate ") print(" python genome_checksum.py verify ") sys.exit(1) mode = sys.argv[1] file = sys.argv[2] if mode == "generate": digest = sha256sum(file) with open("checksum.txt", "w") as f: f.write(f"{digest} {file}\n") print(f"Checksum saved to checksum.txt") elif mode == "verify" and len(sys.argv) == 4: checksum_file = sys.argv[3] with open(checksum_file, "r") as f: expected, fname = f.readline().strip().split(" ") actual = sha256sum(file) if actual == expected: print("Checksum verified: OK") else: print("Checksum mismatch: FAIL") else: print("Invalid arguments.") sys.exit(1) [end python] Example Usage [bash] # Generate checksum python genome_checksum.py generate my_genome.fasta # Verify checksum later python genome_checksum.py verify my_genome.fasta checksum.txt [end bash] 📌 How to Use This in Your Blog Workflow After creating your full genome FASTA (from Dante Labs), generate a checksum (checksum.txt) using one of the scripts. Upload the checksum file to GitHub alongside your recombination scripts and chunks. Link the checksum file from your genome blog page. In your instructions, tell readers: Recombine the genome FASTA from chunks. Run checksum verification. If verified “OK,” the file matches the original exactly. ⚡ If you want, I can also add a ready‑made instructions section for your HTML genome page that shows readers how to run the checksum verification (in both Bash and Python) so they don’t have to figure it out. Would you like me to draft that too? karbytes: Yes please! ChatGPT: Great 👍 — here’s a drop‑in instructions section you can paste into your genome page HTML. It explains to readers how to verify the recombined FASTA file using the checksum you provide. 📄 HTML Snippet: Checksum Verification Section [html]

    Checksum Verification

    To ensure that the recombined FASTA file is identical to the original, verify its SHA256 checksum using the provided checksum.txt file.

    Step 1: Download the Checksum File

    Download the checksum file from GitHub:
    checksum.txt

    Step 2: Verify the File

    After recombining the FASTA file, run one of the following scripts:

    Option A: Bash

    chmod +x genome_checksum.sh
./genome_checksum.sh verify my_genome.fasta checksum.txt

    If the file matches, you will see:
    my_genome.fasta: OK

    Option B: Python

    python genome_checksum.py verify my_genome.fasta checksum.txt

    If the file matches, you will see:
    Checksum verified: OK

    Why Verify?

    Verification ensures the recombined FASTA file is bit-for-bit identical to the original genome FASTA hosted on the Internet Archive. This guarantees data integrity for scientific use.

    [end html] 🔹 Next Steps for You Replace YOUR_GITHUB_USERNAME/YOUR_REPO with the actual values. Upload checksum.txt, genome_checksum.sh, and genome_checksum.py to GitHub. Link them on your genome blog page (next to your recombination scripts). Generate the checksum.txt file after you have your final FASTA from Dante Labs. ⚡ If you’d like, I can also show you the exact Bash command you’ll run on your local machine to generate the SHA256 checksum for your FASTA once you have it, so you know exactly what will go in checksum.txt. Would you like me to give you that one‑liner? karbytes: Yes please! ChatGPT: Perfect 👍 — here’s the exact one‑liner you’ll run on your local machine to generate a SHA256 checksum for your Dante Labs FASTA file: 🔹 Generate Checksum (Bash One‑Liner) [bash] sha256sum my_genome.fasta > checksum.txt [end bash] ✅ What Happens sha256sum my_genome.fasta → computes the SHA256 hash of your genome file. > checksum.txt → saves the result into a file named checksum.txt. The resulting file will look something like this: [preformatted_text] 3c1f6c81e34a77ed5d9c15a2a1c5fbc243f17d99b2998c0f615dc8f4a6a4f5b8 my_genome.fasta [end preformatted_text] 🔹 Verify Later To verify after recombining: [bash] sha256sum -c checksum.txt [end bash] If the recombined FASTA matches the original exactly, you’ll see: [preformatted_text] my_genome.fasta: OK [end preformatted_text] 🔹 Tip for Windows Users If some readers use Windows without WSL or Git Bash, they can use the Python script you provide instead, since Python runs on Windows natively. ⚡ If you’d like, I can also show you how to compress your FASTA into a .gz file before checksumming — this reduces size (important for faster downloads and fewer GitHub chunks) while still allowing verification. Want me to add that too? karbytes: How many <25mb sized chunk files do you think I would need to make for my entire genome FASTA? ChatGPT: Good question 👍 — let’s estimate based on the expected size of your Dante Labs FASTA. 🔹 Step 1: Size of a Whole Genome FASTA A human genome FASTA (just sequence, no quality scores) is typically ~3 GB uncompressed. Compressed (.fa.gz), it can shrink to ~800 MB – 1 GB. Since you mentioned FASTA, we’ll assume ~3 GB uncompressed. 🔹 Step 2: Splitting Into <25 MB Chunks GitHub itself allows files up to 100 MB, but you specified <25 MB, which is a more conservative, Wayback‑friendly size. Calculation: 3 GB ≈ 3000 MB 3000 ÷ 25 = 120 chunks So you’d need about 120 chunk files if you keep them under 25 MB each. 🔹 Step 3: Adjusting Strategy If you’re comfortable with larger chunks (say, 90 MB each, still under GitHub’s 100 MB cap), you’d only need: 3000 ÷ 90 ≈ 34 chunks That’s far easier to manage than 120+ pieces. But <25 MB does make each piece small enough that the Wayback Machine is more likely to capture them fully without timeout issues. 🔹 Recommendation If Wayback Machine archival reliability is your top priority → stick with <25 MB chunks (≈120 parts). If convenience for users is more important → go with ~90 MB chunks (≈34 parts). ⚡ Would you like me to write a Bash command that will automatically split your FASTA into <25 MB parts and name them neatly (so you can drop them straight into GitHub)? karbytes: Yes please! ChatGPT: Great 👍 — here’s a Bash one‑liner that will split your whole genome FASTA into chunks <25 MB each, with clean filenames for easy uploading to GitHub and reassembly. 🔹 Bash Command to Split FASTA [bash] split -b 25M --numeric-suffixes=1 --suffix-length=3 my_genome.fasta genome_part_ [end bash] ✅ Explanation split → the command that splits files. -b 25M → each chunk will be 25 MB max. --numeric-suffixes=1 → use numeric suffixes starting at 001. --suffix-length=3 → ensures suffixes are 3 digits (001, 002, 003, …). my_genome.fasta → your input file. genome_part_ → prefix for the output chunks. 📂 Example Output If your FASTA is ~3 GB, you’ll see about 120 files: [preformatted_text] genome_part_001 genome_part_002 genome_part_003 ... genome_part_120 [end preformatted_text] 🔹 Recombination Later Users will run your provided script (Bash or Python), which will automatically concatenate them back: [bash] cat genome_part_* > my_genome.fasta [end bash] 🔹 Optional: Compress Before Splitting If you want to reduce the number of chunks: [bash] gzip -c my_genome.fasta > my_genome.fasta.gz split -b 25M --numeric-suffixes=1 --suffix-length=3 my_genome.fasta.gz genome_part_ Compression might shrink your FASTA from ~3 GB down to ~800 MB–1 GB. [end bash] That means only ~40 chunks instead of 120 at 25 MB each. ⚡ Question for you: Would you like me to adapt your recombination script so it automatically detects if the file is compressed (.gz) and, if so, decompresses it back into the FASTA? That way your users wouldn’t need to know whether they’re working with a compressed genome or not. karbytes: Yes please! ChatGPT: Perfect 👍 — let’s make your recombination script smart enough to handle both cases: If you split the original uncompressed FASTA, it just stitches the pieces together. If you split a compressed FASTA (.gz), it stitches them, then decompresses to produce the final FASTA. I’ll show you both Bash and Python versions so you can decide which to feature (or give both). 🐚 Bash Recombination Script (with gzip support) Save as recombine_genome.sh: [bash] #!/bin/bash # --------------------------------------------------------- # Script: recombine_genome.sh # Purpose: Recombine genome FASTA parts into one file, # handling both plain and .gz compressed input. # Usage: # ./recombine_genome.sh output.fasta # --------------------------------------------------------- if [ "$#" -ne 1 ]; then echo "Usage: $0 output.fasta" exit 1 fi OUTPUT_FILE="$1" TEMP_FILE="temp_combined_file" # Check for genome parts if ls genome_part_* 1> /dev/null 2>&1; then echo "Combining genome_part_* files ..." cat genome_part_* > "$TEMP_FILE" else echo "Error: No genome_part_* files found in the current directory." exit 1 fi # Detect if the combined file is gzipped if file "$TEMP_FILE" | grep -q "gzip compressed"; then echo "Detected gzip-compressed file. Decompressing..." gunzip -c "$TEMP_FILE" > "$OUTPUT_FILE" rm "$TEMP_FILE" else echo "Detected plain FASTA. Saving..." mv "$TEMP_FILE" "$OUTPUT_FILE" fi echo "Done! Recombined genome saved as $OUTPUT_FILE" [end bash] 🐍 Python Recombination Script (with gzip support) Save as recombine_genome.py: [python] #!/usr/bin/env python3 """ --------------------------------------------------------- Script: recombine_genome.py Purpose: Recombine genome FASTA parts into one file, handling both plain and .gz compressed input. Usage: python recombine_genome.py output.fasta --------------------------------------------------------- """ import sys import glob import gzip import shutil import os if len(sys.argv) != 2: print("Usage: python recombine_genome.py output.fasta") sys.exit(1) output_file = sys.argv[1] parts = sorted(glob.glob("genome_part_*")) if not parts: print("Error: No genome_part_* files found in the current directory.") sys.exit(1) temp_file = "temp_combined_file" print(f"Combining {len(parts)} genome parts into {temp_file}...") with open(temp_file, "wb") as out: for part in parts: print(f" - Adding {part}") with open(part, "rb") as f: shutil.copyfileobj(f, out) # Detect gzip by checking file signature (magic number) with open(temp_file, "rb") as f: signature = f.read(2) if signature == b"\x1f\x8b": print("Detected gzip-compressed file. Decompressing...") with gzip.open(temp_file, "rb") as f_in, open(output_file, "wb") as f_out: shutil.copyfileobj(f_in, f_out) os.remove(temp_file) else: print("Detected plain FASTA. Saving...") os.rename(temp_file, output_file) print(f"Done! Recombined genome saved as {output_file}") [end python] ✅ User Workflow Download all genome_part_* files. Download the recombination script (Bash or Python). Run one of the following: Bash [bash] chmod +x recombine_genome.sh ./recombine_genome.sh my_genome.fasta [end bash] Python [bash] python recombine_genome.py my_genome.fasta [end bash] Script automatically checks if the combined file is .gz and decompresses if needed. Verify with your checksum script to confirm integrity. ⚡ If you want, I can also provide a matching checksum generation step for the compressed version (so you can distribute both compressed and uncompressed checksums). Would you like me to prepare that too, so users can verify either form? karbytes: Yes please! ChatGPT: Excellent 👍 — let’s make checksum handling flexible so users can verify either the compressed genome (.gz) or the decompressed FASTA, depending on which form they end up with. 🐚 Bash Checksum Script (supports both compressed & uncompressed) Save as genome_checksum.sh: [bash] #!/bin/bash # --------------------------------------------------------- # Script: genome_checksum.sh # Purpose: Generate and/or verify SHA256 checksum # for genome FASTA or compressed FASTA (.gz) # Usage: # ./genome_checksum.sh generate my_genome.fasta # ./genome_checksum.sh generate my_genome.fasta.gz # ./genome_checksum.sh verify my_genome.fasta checksum.txt # ./genome_checksum.sh verify my_genome.fasta.gz checksum.txt # --------------------------------------------------------- if [ "$1" == "generate" ] && [ "$#" -eq 2 ]; then sha256sum "$2" > checksum.txt echo "Checksum saved to checksum.txt" elif [ "$1" == "verify" ] && [ "$#" -eq 3 ]; then sha256sum -c "$3" else echo "Usage:" echo " $0 generate " echo " $0 verify " exit 1 fi [end bash] 🐍 Python Checksum Script (supports both compressed & uncompressed) Save as genome_checksum.py: [python] #!/usr/bin/env python3 """ --------------------------------------------------------- Script: genome_checksum.py Purpose: Generate and/or verify SHA256 checksum for genome FASTA or compressed FASTA (.gz) Usage: python genome_checksum.py generate my_genome.fasta python genome_checksum.py generate my_genome.fasta.gz python genome_checksum.py verify my_genome.fasta checksum.txt python genome_checksum.py verify my_genome.fasta.gz checksum.txt --------------------------------------------------------- """ import hashlib import sys def sha256sum(filename): h = hashlib.sha256() with open(filename, "rb") as f: for chunk in iter(lambda: f.read(8192), b""): h.update(chunk) return h.hexdigest() if len(sys.argv) < 3: print("Usage:") print(" python genome_checksum.py generate ") print(" python genome_checksum.py verify ") sys.exit(1) mode = sys.argv[1] file = sys.argv[2] if mode == "generate": digest = sha256sum(file) with open("checksum.txt", "w") as f: f.write(f"{digest} {file}\n") print(f"Checksum saved to checksum.txt") elif mode == "verify" and len(sys.argv) == 4: checksum_file = sys.argv[3] with open(checksum_file, "r") as f: expected, fname = f.readline().strip().split(" ") actual = sha256sum(file) if actual == expected: print("Checksum verified: OK") else: print("Checksum mismatch: FAIL") else: print("Invalid arguments.") sys.exit(1) [end python] ✅ Your Workflow Step 1. Generate Checksums (before upload) When you have your genome files from Dante Labs: [bash] # For uncompressed FASTA sha256sum my_genome.fasta > checksum_uncompressed.txt # For compressed FASTA (.gz) sha256sum my_genome.fasta.gz > checksum_compressed.txt [end bash] Now you’ll have two checksum files: checksum_uncompressed.txt checksum_compressed.txt Step 2. Upload Both Upload both checksum files to your GitHub repo. Link them from your genome page (with instructions for verifying either form). Step 3. Users Verify After recombining (and decompressing, if needed), users can check with either: For FASTA [bash] sha256sum -c checksum_uncompressed.txt [end bash] For FASTA.gz [bash] sha256sum -c checksum_compressed.txt [end bash] Both should return an OK if the file is correct. ⚡ If you want, I can now update the HTML snippet of your genome page so it clearly shows both the compressed and uncompressed checksum verification options (so you don’t have to write those instructions manually). Want me to do that? karbytes: Yes please! ChatGPT: Perfect 👍 — here’s an updated HTML snippet for your genome page that includes both the compressed and uncompressed checksum verification instructions. You can paste this into your WordPress page and then just swap in your actual GitHub links. 📄 Updated HTML Snippet: Checksum Verification (Supports FASTA & FASTA.gz) [html]

    Checksum Verification

    To ensure the recombined genome file is identical to the original, verify its SHA256 checksum. Two checksum files are provided: one for the uncompressed FASTA and one for the compressed FASTA (.gz).

    Step 1: Download the Checksum Files

    Step 2: Verify the File

    After recombining the genome parts, run one of the following options:

    Option A: Verify Uncompressed FASTA

    If your recombination script produced my_genome.fasta:

    sha256sum -c checksum_uncompressed.txt

    Expected output:
    my_genome.fasta: OK

    Option B: Verify Compressed FASTA

    If your recombination script produced my_genome.fasta.gz:

    sha256sum -c checksum_compressed.txt

    Expected output:
    my_genome.fasta.gz: OK

    Alternative: Using the Provided Scripts

    Example (Bash):
    ./genome_checksum.sh verify my_genome.fasta checksum_uncompressed.txt

    Example (Python):
    python genome_checksum.py verify my_genome.fasta.gz checksum_compressed.txt

    Why Verify?

    Verification ensures the recombined FASTA file is bit-for-bit identical to the original genome hosted on the Internet Archive. This guarantees data integrity for scientific and archival use.

    [end html] ✅ Your Next Steps Replace all YOUR_GITHUB_USERNAME/YOUR_REPO placeholders with your actual GitHub path. Upload: checksum_uncompressed.txt checksum_compressed.txt genome_checksum.sh genome_checksum.py Confirm the recombination scripts can output either .fasta or .fasta.gz. Publish this page to your WordPress blog. ⚡ Do you want me to also create a compact diagram (SVG or PNG) that visually shows the process (download parts → recombine → verify checksum → final FASTA)? That could make your genome page more user‑friendly. karbytes: I think what you've provided thus far is sufficient for my purposes (at this time). Thanks! :) ChatGPT: You’re very welcome 🙂 I’m glad this setup meets your needs! It sounds like you’ve built a solid plan for making your genome FASTA both publicly accessible and archivally robust. If at any point you want to add that diagram or polish the presentation further, just let me know — we can expand on what you already have. Would you like me to also save a concise checklist of the steps you’ll need to complete when you actually get your FASTA file from Dante Labs? That way you’ll have a ready reference. karbytes: Yes please! ChatGPT: Excellent 👍 — here’s a concise step‑by‑step checklist you can use when you receive your genome FASTA from Dante Labs. You could even print or save this as a plain‑text file for reference. ✅ Whole Genome FASTA Publishing Checklist 1. Prepare the Genome File Download FASTA file from Dante Labs (Optional) Compress to .gz to reduce size: [bash] gzip -c my_genome.fasta > my_genome.fasta.gz [end bash] 2. Generate Checksums For uncompressed FASTA: [bash] sha256sum my_genome.fasta > checksum_uncompressed.txt [end bash] For compressed FASTA: [bash] sha256sum my_genome.fasta.gz > checksum_compressed.txt [end bash] 3. Split into Chunks for GitHub Split into <25 MB pieces for Wayback Machine reliability: [bash] split -b 25M --numeric-suffixes=1 --suffix-length=3 my_genome.fasta.gz genome_part_ [end bash] Confirm the number of chunks (≈40 if compressed, ≈120 if uncompressed). 4. Upload Files Upload full FASTA (compressed or uncompressed) to Internet Archive Upload chunked parts (genome_part_*) to GitHub Upload scripts: recombine_genome.sh recombine_genome.py genome_checksum.sh genome_checksum.py Upload checksum files: checksum_uncompressed.txt checksum_compressed.txt 5. Update Genome Page on Blog Insert Internet Archive link to full FASTA Insert GitHub raw links for chunked files Insert links to recombination scripts Insert links to checksum files Add instructions (recombine → verify checksum → final FASTA) 6. Archive Page for Permanence Use Wayback Machine “Save Page Now” on your genome blog page to archive the instructions + GitHub links. ⚡ That’s the whole roadmap — straightforward and covers all the bases for availability, integrity, and archival longevity. Do you want me to also make a plain‑text version of this checklist (monospace formatted) so it matches the style of your other technical notes? karbytes: I'll likely do that part manually when I have the FASTA handy. Thanks! ChatGPT: Sounds good 👍 — doing it manually when you have the FASTA in hand makes perfect sense. You’ll be in full control of the formatting and style that best matches your archive. When you’re ready, if you’d like me to review your finished genome page (before you push it live or send it through the Wayback Machine), I’d be happy to give it a quick pass for clarity and completeness. Would you like me to keep this workflow fresh in memory so you don’t need to re‑explain it when you get your FASTA? karbytes: Sure! ChatGPT: [Updated saved memory] Got it ✅ — I’ll keep this whole genome FASTA publishing workflow fresh in memory for when you’re ready. That way, you won’t need to re‑explain the plan later.