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Reading the repo
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How to install on Linux
Fast single-cell and spatial transcriptomics in Rust. 24x faster than Scanpy on compute-bound steps.
Saved setup from 23 min ago
Will it work on Linux?
Then run bash setup.sh. It stops at the first error and is safe to run again. Servers and tests aren't started; it lists them at the end. Read it first.
git clone https://github.com/jwg054000/RustPipe-SC.git cd RustPipe-SC
Rust stable
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
cargo build
cargo run
cargo test
# H5AD input (Scanpy/nf-core output)
rustpipe-sc pipeline \
--input sample.h5ad \
--output results/ \
--n-hvg 2000 --n-pcs 50 --knn-k 15
# 10x CellRanger H5 input
rustpipe-sc pipeline \
--input filtered_feature_bc_matrix.h5 \
--output results/ \
--max-pct-mt 20.0
# CSV input
rustpipe-sc pipeline \
--input expression.csv \
--output results/
# Optional library QC from a Cell Ranger BAM (PATH rustqc; not the cell matrix)
rustpipe-sc pipeline \
--input filtered_feature_bc_matrix.h5 \
--output results/ \
--qc-bam possorted_genome_bam.bam \
--qc-gtf genes.gtf
# QC metrics + cell filtering
rustpipe-sc qc --input raw.h5ad --output qc/ --min-genes 200 --max-pct-mt 5.0
# Normalize + log1p
rustpipe-sc normalize --input qc/filtered.csv --output norm/
# HVG selection (Seurat v3 method)
rustpipe-sc hvg --input norm/normalized.csv --output hvg/ --n-top-genes 2000
# PCA
rustpipe-sc pca --input hvg/expression_hvg.csv --output pca/ --n-components 50
# kNN graph
rustpipe-sc knn --input pca/pca_scores.csv --output knn/ --k 15
# Leiden clustering
rustpipe-sc leiden --input knn/knn.csv --output clusters/ --resolution 1.0
# Spatial autocorrelation (Moran's I)
rustpipe-sc morans-i \
--input expression.csv \
--coords spatial_coords.csv \
--output spatial/
--threads N Number of threads (0 = all cores, default: 0)
--seed N Random seed for reproducibility (default: 42)
-v/-vv/-vvv Verbosity level
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