populationgenomics/production-pipelines
Nov 2025 – Nov 2025
1 Month active
Languages Used
Python
Technical Skills
Python scriptingbioinformaticscloud computingcommand line toolsdata processingfile handling
Michael Harper
PROFILE
Michael Harper
Michael Harper developed an end-to-end UBAM processing and kinetics removal pipeline for the populationgenomics/production-pipelines repository. Using Python scripting and command line tools such as samtools, he enabled automated handling of PacBio ubam files from Google Cloud Storage, removal of kinetic data, and output of cleaned BAM files to a specified directory. He standardized output naming conventions and path handling, converting extensions and introducing consistent suffixes to improve downstream usability and reduce manual intervention. This work enhanced data quality and reproducibility, demonstrating depth in bioinformatics data processing and cloud integration while simplifying automation and supporting robust downstream analytics workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
1
Lines of code
72
Activity Months1
Your Network
19 peopleSame Organization
@populationgenomics.org.au12
Shared Repositories
7
Work History
November 2025
5 Commits • 1 Features
Nov 1, 2025Month 2025-11 — Major feature delivered for populationgenomics/production-pipelines. Implemented the UBAM processing and kinetics removal pipeline enabling end-to-end handling of PacBio ubam files from Google Cloud Storage, removal of kinetic data via samtools, and saving cleaned BAMs to a defined output directory. Standardized output naming and path handling to improve downstream usability and clarity (changing extensions to .bam and naming conventions like '_no_kinetics_bam'). This work enhances data quality, reproducibility, and pipeline stability, reducing manual intervention and enabling smoother integration with downstream analytics.
5 Commits • 1 Features
Nov 1, 2025Month 2025-11 — Major feature delivered for populationgenomics/production-pipelines. Implemented the UBAM processing and kinetics removal pipeline enabling end-to-end handling of PacBio ubam files from Google Cloud Storage, removal of kinetic data via samtools, and saving cleaned BAMs to a defined output directory. Standardized output naming and path handling to improve downstream usability and clarity (changing extensions to .bam and naming conventions like '_no_kinetics_bam'). This work enhances data quality, reproducibility, and pipeline stability, reducing manual intervention and enabling smoother integration with downstream analytics.
November 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability96.0%
Architecture96.0%
Performance96.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Python scriptingbioinformaticscloud computingcommand line toolsdata processingfile handlingscripting
Repositories Contributed To
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