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TxNova

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TxNova — short for Transcript Nova — recovers unannotated spliced residual loci from existing bulk RNA-seq BAMs. Cohort-recurrent residual splices become locus models. Class, counts, junctions, and bridges are recomputed from the BAM and the annotation. A control-versus-treat filter is optional.

Step What it does
Harvest Cohort-recurrent CIGAR N junctions missing from the annotation → residual loci
Universe Annotation + residual models, counted together
Gates Structure always; treat-detected / control-silent only if both groups are present
Tables Residual catalog; optional contrast finals; both-group structure-pass when a contrast exists

Docs: Read the Docs.

What you need

  • Python 3.10+
  • Coordinate-sorted, indexed BAMs from STAR or HISAT2 (≥2 samples; control/treat optional)
  • Genome FASTA + .fai, and a comprehensive gene GTF (mouse GENCODE M39 / GRCm39, or human GENCODE / GRCh38). species: auto infers mouse or human; you can set species: mouse or human. Only those two are supported.
  • A YAML config and a sample sheet (txnova init writes starters)

Install

pip install txnova
# or: conda install -c conda-forge -c bioconda txnova

Wheels cover Linux and macOS. On Windows use WSL2. Building from source needs a Rust toolchain; see Installation.

First run

txnova init -c config.yaml --samples samples.tsv
# edit paths, strandedness (rf / fr / unstranded), and sample rows
txnova preflight -c config.yaml
txnova run -c config.yaml

What to expect under output_dir:

  • candidates/candidates.tsv — structure-pass residuals; treat-detected / control-silent when a contrast exists
  • candidates/candidates.unnamed.tsv — structure-pass, also in control by TPM
  • candidates/candidates.shared.tsv — structure-pass, splice in both groups
  • report/report.html — start here
  • quantify/ — full-universe counts, TPM, and DE

The three candidate tables share the structural gates. They answer different questions (induction vs unannotated structure in both groups). They are not a declaration of new genes.

Next: Preparing input BAMs · Quickstart · Output reference · FAQ

Status

0.1.x. Pin txnova==0.1.12 in Methods. Changelog.

Citation

If you use TxNova in published work, please cite the preprint:

Zhao Li, Aaron James, Shengxuan Li. TxNova: recovery of recurrent unannotated intergenic splice loci from existing bulk RNA-seq alignments. bioRxiv (2026). doi:10.64898/2026.08.24.746847

@article{li2026txnova,
  title   = {TxNova: recovery of recurrent unannotated intergenic splice loci from existing bulk RNA-seq alignments},
  author  = {Li, Zhao and James, Aaron and Li, Shengxuan},
  journal = {bioRxiv},
  year    = {2026},
  doi     = {10.64898/2026.08.24.746847},
  url     = {https://www.biorxiv.org/content/10.64898/2026.08.24.746847v1},
}

For the software record, cite the Zenodo DOI above. Pin the installed version in Methods (this tree is txnova==0.1.12). See CITATION.cff.

Li, Z. TxNova. Zenodo. doi:10.5281/zenodo.21970482

PyPI: https://pypi.org/project/txnova/.

License

Software: Apache License 2.0. The packaged hexamer tables come from CPAT (Wang et al. 2013); see docs/license.

Author

Zhao Li (李钊)
Email: leelieber@gmail.com

Metadata

Release files for txnova 0.1.12

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txnova-0.1.12-cp310-abi3-manylinux_2_28_x86_64.whl CPython 3.10 abi3 Linux glibc 2.28+ x86-64 Details
txnova-0.1.12-cp310-abi3-manylinux_2_28_aarch64.whl CPython 3.10 abi3 Linux glibc 2.28+ ARM64 Details
txnova-0.1.12-cp310-abi3-macosx_11_0_arm64.whl CPython 3.10 abi3 macOS 11.0+ ARM64 Details
txnova-0.1.12-cp310-abi3-macosx_10_12_x86_64.whl CPython 3.10 abi3 macOS 10.12+ x86-64 Details

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