PIPseeker Release Notes & Archives
Release Notes
V2.1.4
- Minor patch to Docker image for running with limited user permissions
V2.1.3
- Automatic check for PIPseeker updates
- Build cell type annotation references from PIPseeker results
- Generate barcode whitelist from FASTQ files for custom analysis
V2.0.0
- Support for multi-omics workflows:
- Quantification of cell surface protein using Antibody Derived Tags (ADT)
- Sample demultiplexing using Hash-Tag oligonucleotides (HTO)
- Feature plots: show individual gene expression across cells in UMAP space
- Clustering: better control of clustering parameters and sensitivity for improved rare cell type identification
- SVG format option for saved images
- Improvements to the summary report
- Performance improvements: faster analysis and better resource utilization
V1.1.7
- Operating systems
- Additional Linux support:
- Centos8
- Centos7
- Ubuntu 22.10 – Kinetic
- Ubuntu 22.04 – Focal
- Ubuntu 22.04 – Jammy
- Ubuntu 18.04 – Bionic
- Ubuntu 16.04 – Xenial
- Native macOS support (no Docker installation required)
- Additional Linux support:
- Performance improvements
- Parallel processing
- Parallelization was added to each major step of the pipeline to optimize system resource usage and reduce runtime.
- RAM and disk space optimization
- Recovery mode
- Resume previous failed runs from the last completed step.
- Parallel processing
- Command line interface
- “pipseeker count” and “pipseeker reanalyze” renamed to “pipseeker full” and “pipseeker cells”.
- Cell type annotation
- Identify cell types in the processed sample.
- Preflight checks
- Verifies that the system has sufficient resources before starting the analysis.