ISAtools

ISAtools (Isoform Sequencing Analysis tools) is a sequencing data–driven framework for full-length RNA isoform reconstruction and quantification from long-read RNA sequencing data. Designed with annotation flexibility and biological fidelity in mind, ISAtools supports isoform identification with high precision and recall, and accurately resolves splice junctions and transcript boundaries directly from read evidence.

If reference annotations are available, ISAtools incorporates conserved, low-abundance isoforms through guided filtering and rescue steps, further enhancing transcriptome completeness.

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🔧 Quick Start

To run ISAtools with aligned reads, the minimum required parameters are:

python isatools.py -r /PATH/TO/reference_genome.fasta \
	-b /PATH/TO/sample1.bam /PATH/TO/sample2.bam /PATH/TO/sample3.bam

For example, using the toy data provided in this repository:

python isatools.py -r test/toy_data/test_genome.fasta \
	-b test/toy_data/test_aligned.bam

To run ISAtools with a reference gene annotation:

python isatools.py -r /PATH/TO/reference_genome.fasta \
	-b /PATH/TO/sample1.bam /PATH/TO/sample2.bam /PATH/TO/sample3.bam \
	-g /PATH/TO/gene_annotation.gtf \
	-o OUTPUT_FOLDER

Example with toy data:

python isatools.py -r test/toy_data/test_genome.fasta \
	-b test/toy_data/test_aligned.bam \
	-g test/toy_data/test_annotation.gtf \
	-o OUTPUT_FOLDER

Note: It is strongly recommended to pre-trim adapter and polyA sequences. If using untrimmed reads, add --min_aln_coverage 0 to avoid misfiltering due to alignment artifacts.

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📦 Installation

ISAtools requires Python 3.9 or higher and samtools in your $PATH.

We recommend using Conda to manage dependencies and environments.

✅ Create a Conda environment

# Create and activate the Conda environment
conda create -n isatools python=3.9 -y
conda activate isatools

# Install samtools
conda install -c bioconda samtools -y

# Clone ISAtools repository and install Python dependencies
git clone https://github.com/Chenhu7/ISAtools.git
cd ISAtools
pip install -r requirements.txt

✅ Use environment.yml (alternative setup)

# Clone ISAtools repository
git clone https://github.com/Chenhu7/ISAtools.git
cd ISAtools

conda env create -f environment.yml
conda activate isatools

🧪 Verify installation by running the toy example:

python isatools.py -r test/toy_data/test_genome.fasta -b test/toy_data/test_aligned.bam

Upon successful execution, output files will appear in the default isatools_output folder.

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📁 Output Files

Main Output

• isatools.filtered.transcript.gtf: Final filtered transcript models (including known and novel isoforms).
• isatools_gene_counts.tsv: Gene-level raw read counts.
• isatools_gene_tpm.tsv: Gene-level TPM expression values.
• isatools_transcript_counts.tsv: Transcript-level read counts.
• isatools_transcript_tpm.tsv: Transcript-level TPMs.

Optional Output (with --keep_temp)

• *_flnc.ssc: Read-level SSC file with alignment details.
• *_ssc.count: Unique SSCs with aggregated read counts.
• anno.ssc: Reference annotation converted into SSC format (if -g is provided).

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📄 File Format Descriptions

Expression Tables (*_counts.tsv, *_tpm.tsv)

Column	Description
TrID	Transcript ID, uniquely defined by the combination of TrStart, SSC, and TrEnd. Isoforms sharing the same SSC but differing in transcript boundaries (either TrStart or TrEnd) are treated as distinct transcripts. If multiple TSS/TES pairs are detected for the same SSC, a suffix _TssTes* is appended to distinguish each variant.
GeneID	Gene ID; if reference annotation is unavailable, ISAtools assigns a gene cluster ID.
GeneName	Same as above; derived from annotation if available.
count/TPM	Expression value for transcript or gene.

SSC File – Read Level (*_flnc.ssc)

Column	Description
0	Read ID
1	Chromosome ID
2	Strand
3	5′ alignment start
4	3′ alignment end
5	Splice site chain
6	Alignment identity
7	Alignment coverage

SSC File – Unique SSC Level (*_ssc.count)

Column	Description
0	Frequency (read count of SSC)
1	Chromosome
2	Strand
3	Splice site chain
4	Donor-acceptor motif sequence

Annotation SSC File (anno.ssc)

Column	Description
TrID	Transcript ID
GeneID	Gene ID
GeneName	Gene name
Chr	Chromosome
Strand	Strand
TrStart	Transcript start site
TrEnd	Transcript end site
SSC	Splice Site Chain