sma-finder

library1.4.4pypypiunverified

SMA Finder is a Python-based command-line tool designed for diagnosing spinal muscular atrophy (SMA) using exome or genome sequencing data. It automates the analysis of sequencing files to identify genetic markers associated with SMA. The current version is 1.4.4, with releases occurring as significant new features or improvements are added, rather than on a strict cadence.

data devops

pip install sma-finder

github ↗package ↗

INSTALL

IMPORT

SIG · SMA-FINDER

sma-finder

datapythonv1.4.4

Install

16.0s avg

Import

—

Disk

476MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v1.4.4 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.910 runs

installs and imports cleanly · install 0.0s · import 0.000s · 453.6MB

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 16.0s · import 0.000s · 451MB

476MB installed

● package 476MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

SMAFinder

✓ from sma_finder import SMAFinder

✗ import sma_finder

Run SMA Finder from the command line, providing input BAM/CRAM files, a reference genome FASTA, and an output directory. The `--reference_name` flag helps label outputs and, for v1.2+, informs the tool if it needs to try multiple reference fastas.

sma_finder --input_bam_files /path/to/your_sample.bam \ --reference_fasta /path/to/your_reference.fa \ --output_dir ./results \ --reference_name hg38

sma-finder --version

Debug

Known issues

gotchaSMA Finder relies on external bioinformatics tools, most notably `samtools`. These tools must be installed on your system and accessible via your system's PATH for SMA Finder to function correctly.

fix

Ensure `samtools` (and any other necessary bioinformatics tools) are installed and their executables are in your system's PATH. Using a tool like `conda` (e.g., `conda install samtools`) or a containerized environment (Docker, Singularity) can help manage these dependencies.

affects: All versions

gotchaProcessing large sequencing files (especially whole-genome sequencing or WGS) can be computationally intensive and demand significant RAM and disk space. Running out of memory or disk space is a common issue for large datasets.

fix

Allocate sufficient computing resources (RAM, CPU cores, disk space) for your analysis. For WGS data, consider running on a high-performance computing (HPC) cluster or cloud environment with adequate resources.

affects: All versions

gotchaWhen providing multiple reference FASTA files (a feature added in v1.2), the tool will attempt to use each until a match is found. However, explicitly ensuring your input BAM/CRAM files are aligned against one of the provided reference FASTA builds (e.g., hg19 or hg38) is crucial for accurate results.

fix

Verify the genome build of your input BAM/CRAM files. Provide a reference FASTA file that precisely matches this build. While the tool is flexible, explicit matching prevents unnecessary trial-and-error.

affects: All versions (v1.2+ provides some mitigation)

Upgrade

Version history

1.4.4latest on PyPI · released Jan 31, 2024

Audit

Dependencies

No dependency data recorded yet.

Agent activity

14 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/broadinstitute/sma_finder ↗

packagehttps://pypi.org/project/sma-finder/ ↗