zamprof123/rp1b_task1
Nov 2024 – Apr 2025
3 Months active
Languages Used
PythonTextShelltext
Technical Skills
Basic ProgrammingConditional StatementsFile I/OList SlicingLoopsProblem Solving
Ery21
PROFILE
Ery21
Ekem Ekemezie developed bioinformatics workflows and data analysis tools in the zamprof123/rp1b_task1 repository, focusing on genomic data processing and visualization. Over three months, Ekem implemented a reproducible variant analysis pipeline using Python and Shell scripting, integrating conda environment setup, read mapping, SNP and indel calling, and depth file generation for multiple samples. Ekem also enhanced cell cycle analysis by introducing rolling average smoothing and per-track time-series visualization, improving interpretability of biological data. Comprehensive documentation accompanied each feature, supporting onboarding and reproducibility. The work demonstrated solid application of data analysis, scientific computing, and file I/O skills to real-world genomics problems.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
13Total
Bugs
0
Commits
13
Features
6
Lines of code
255
Activity Months3
Your Network
20 people
Work History
April 2025
2 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for zamprof123/rp1b_task1. Delivered data visualization improvements for cell cycle analysis and formal Python script documentation. These changes deliver clearer insights into cell cycle progression and improve repository maintainability.
2 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for zamprof123/rp1b_task1. Delivered data visualization improvements for cell cycle analysis and formal Python script documentation. These changes deliver clearer insights into cell cycle progression and improve repository maintainability.
April 2025
December 2024
3 Commits • 1 Features
Dec 1, 2024Month 2024-12: Delivered an end-to-end Variant Analysis Workflow and accompanying documentation for zamprof123/rp1b_task1. The feature provides a reproducible pipeline (conda environment setup, bios/tools installation, read mapping, SNP/indel calling, generation of depth files for three samples, BAM indexing, and alignment visualization) and comprehensive Q&A documentation detailing SNP/indel analysis, sample comparisons, and environmental factors affecting INDELs. This work enhances data quality, reproducibility, and decision-support for downstream analyses, with clear traceability to commits.
December 2024
3 Commits • 1 Features
Dec 1, 2024Month 2024-12: Delivered an end-to-end Variant Analysis Workflow and accompanying documentation for zamprof123/rp1b_task1. The feature provides a reproducible pipeline (conda environment setup, bios/tools installation, read mapping, SNP/indel calling, generation of depth files for three samples, BAM indexing, and alignment visualization) and comprehensive Q&A documentation detailing SNP/indel analysis, sample comparisons, and environmental factors affecting INDELs. This work enhances data quality, reproducibility, and decision-support for downstream analyses, with clear traceability to commits.
November 2024
8 Commits • 3 Features
Nov 1, 2024Concise monthly summary for 2024-11: Delivered Rosalind-related artefacts and established a clean baseline for future exercises in zamprof123/rp1b_task1. Key outputs include an output file for Rosalind INI4-2, scaffolding and cleanup for Rosalind Task-1, and a comprehensive Task-1 Rosalind solutions file. These deliverables enable faster validation, easier onboarding for new contributors, and a foundation for repeatable assessments and automation.
8 Commits • 3 Features
Nov 1, 2024Concise monthly summary for 2024-11: Delivered Rosalind-related artefacts and established a clean baseline for future exercises in zamprof123/rp1b_task1. Key outputs include an output file for Rosalind INI4-2, scaffolding and cleanup for Rosalind Task-1, and a comprehensive Task-1 Rosalind solutions file. These deliverables enable faster validation, easier onboarding for new contributors, and a foundation for repeatable assessments and automation.
November 2024
Activity
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Quality Metrics
Correctness84.6%
Maintainability84.6%
Architecture84.6%
Performance83.0%
AI Usage23.0%
Skills & Technologies
Programming Languages
PythonShellTexttext
Technical Skills
Basic ProgrammingBioinformaticsConditional StatementsData AnalysisData VisualizationFile I/OGenomic AnalysisGenomicsList SlicingLoopsProblem SolvingScientific ComputingShell ScriptingString ManipulationVariant Calling
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