alevin-fry
mixcr
| alevin-fry | mixcr | |
|---|---|---|
| 3 | 1 | |
| 152 | 310 | |
| 4.6% | 2.6% | |
| 7.2 | 9.7 | |
| 2 months ago | 4 days ago | |
| Rust | Kotlin | |
| BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
alevin-fry
-
RNA VELOCITY
You can also get this information easily from the raw data using our alevin-fry tool. It produces a count matrix with spliced/unspliced/ambiguous counts that can easily be imported into python or R for velocity analysis. You can read more about alevin-fry here and check it out on github here. It's also easily installable via bioconda, and there's even a tool to simplify execution, called simpleaf. I'm happy to answer any questions you might have about using it!
-
"Surpassing" Go & the near-future of Rust: in what domains will Rust succeed?
I think it depends on where in the space one is working. Our most recent tool, for example, is alevin-fry, which is for efficient preprocessing of single cell RNA seq data. Rust is the natural replacement for tools in the space that otherwise would have been in C++ (aligners, assemblers, large scale indexing, and things like RNA seq quantification and preprocessing). I view julia as more appropriate to replace tools currently existing in Python or R. There, I believe it can offer some substantial benefits. For our applications however, garbage collection is usually a non-starter.
-
Our lab did a thing in rust (single-cell bioinformatics)
My lab has been trying to move most of our development over to rust (from C++). Our most recent paper presents a tool for single-cell and single-nucleus RNA-seq processing in rust https://rdcu.be/cIL35. The repo is https://github.com/COMBINE-lab/alevin-fry. It's one of our first "big" rust packages; so hopefully our design practices and rust skills will continue to improve.
mixcr
-
Is it possible to get tcra data from single cell raw reads? The paper only provides tcrb data.
If you have access to the fqs then there's a chance you can extract some sequences out using Mixcr or similar, but there probably won't be many. You will need the reads because not all of the TCR is germline encoded.
What are some alternatives?
pagoda2 - R package for analyzing and interactively exploring large-scale single-cell RNA-seq datasets
hgvs - Python library to parse, format, validate, normalize, and map sequence variants. `pip install hgvs`
rust - Empowering everyone to build reliable and efficient software.
salmon - 🐟 🍣 🍱 Highly-accurate & wicked fast transcript-level quantification from RNA-seq reads using selective alignment
deno - A modern runtime for JavaScript and TypeScript.
galaxy - Data intensive science for everyone.
AreWeRustYet - Awesome list of "Are We *thing* Yet" for Rust
rnaseq - RNA-seq analyses.
alacritty - A cross-platform, OpenGL terminal emulator.
fastp - An ultra-fast all-in-one FASTQ preprocessor (QC/adapters/trimming/filtering/splitting/merging...)
mirdeep2 - Discovering known and novel miRNAs from small RNA sequencing data
deepvariant - DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.