A reference-based, UMI-aware, 5ʹ-trimming-aware PCR duplicate removal pipeline.
Dupligänger is a reference-based, UMI-aware, 5’-trimming-aware PCR duplicate removal pipeline.
Usage: dupliganger [options] <command> [<args>…]
Dupligänger is a pipeline. Each stage of the pipeline is run by passing a ‘command’ to Dupligänger. The commands / pipeline-steps (in order) are as follows:
remove-umi 1. Annotate read names with UMIs (clip inline UMIs if needed). remove-adapter 2. Remove adapters ('Cutadapt' wrapper). qtrim 3. Quality trim ('Trimmomatic' wrapper). annotate-qtrim 4. Annotates quality trimmed file(s). align 5. Align reads to a reference genome assembly (performed manually by user). dedup 6. Use the alignment to remove PCR duplicates.
While generally used only by the developers of Dupligänger, the ‘dedup’ command is comprised of the following Dupligänger commands run in the following order:
build-read-db 1. Build a database of aligned reads. build-location-db 2. Build a database of locations of aligned reads. build-dup-db 3. Build a database of PCR duplicates.
-o OUT_DIR Place results in directory OUT_DIR. --compress Compress output.
- Dupligänger supports (and autodetects) input FASTQ files that are gzipped.
See ‘dupliganger help <command>’ for more information on a specific command.
For further information on Dupligänger, please see the full documentation at https://github.com/uoregon-postlethwait/dupliganger
Dupligänger has been funded by the following grants:
- NIH R01 OD011116 - Resources for Teleost Gene Duplicates and Human Disease
- NIH R24 OD011199 - Advancing the Scientific Potential of Transcriptomics in Aquatic Models
- NIH R24 OD018555 - Development of Aquatic Model Resources for Therapeutic Screens
- NSF PLR-1543383 - Antarctic Fish and MicroRNA Control of Development and Physiology
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size dupliganger-0.98.tar.gz (108.2 kB)||File type Source||Python version None||Upload date||Hashes View hashes|