SMA Finder

1.4.4 · active · verified Fri Apr 17

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.

Common errors

```
sma_finder: command not found
```
cause The `sma_finder` executable script is not in your system's PATH, or the package was not installed with entry points correctly registered.

fix After `pip install sma-finder`, ensure your Python environment is active. If the command still fails, try executing with `python -m sma_finder` instead. You might need to add your Python's `Scripts` or `bin` directory to your system's PATH.
```
FileNotFoundError: [Errno 2] No such file or directory: '/path/to/your_input.bam'
```
cause The specified input BAM/CRAM file, reference FASTA file, or other required file does not exist at the given path, or the path is incorrect.

fix Double-check the exact path and filename for all input files (`--input_bam_files`, `--reference_fasta`). Verify that the files exist and are readable by the user running SMA Finder.
```
Error: Samtools not found or not in PATH.
```
cause SMA Finder requires `samtools` (and potentially other bioinformatics tools) to process sequencing data, but it cannot find the `samtools` executable.

fix Install `samtools` on your system. For example, using `conda install samtools` or your system's package manager (e.g., `apt install samtools`). After installation, ensure its executable is included in your system's PATH environment variable.

Warnings

gotcha SMA 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.
gotcha Processing 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.
gotcha When 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.

Install

pip install sma-finder Install via pip

Imports

cli
wrong:
```
import sma_finder
```
correct:
```
from sma_finder import cli
```
SMA Finder is primarily a command-line interface (CLI) tool. While `sma_finder.cli` contains the main entry point, direct programmatic import and execution are not the primary use case; it's typically run from the shell.

Quickstart

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

view raw JSON →