graphical programming framework
01.12.2022, Studentische Hilfskräfte, Praktikantenstellen, Studienarbeiten
Overview:
Gene expression data at the single-cell level (scRNA-seq) has become into a fundamental tool in biological and biomedical research given their high- resolution power to dissect heterogenic signatures in complex scenarios, e.g., analysis of tumor microenvironment in cancer.
Scanpy is one of the most complete toolboxes for scRNA-seq analysis, allowing a wide range of analyses, including differential expression, pseudo-time, time series, and spatial transcriptomics analysis. However, Scanpy is a python library and requires programming skills to exploit all its functionalities, which is challenging for biological and biomedical researchers without enough programming experience.
On the other hand, Galaxy project is one of the most used web-based user- friendly initiatives focused on the usability of previously published bioinformatics tools for researchers to avoid the coding step-up. Furthermore, another valuable feature of Galaxy is the possibility to create customized pipelines to automatize analysis requiring intermediate steps. Unfortunately, for scRNA-seq, there are no complete unities from Scanpy available, and some biomedical projects require internal management because of patient data protection statements.
Therefore, all unities conversion from Scanpy into a universal pipeline file format ready to use in in-house pipeline cluster systems or initiatives such as Galaxy seems necessary for the good of the scientific community.
Project description:
The project consists of the conversion from python functions (Scanpy) into pipeline systems file format (CTD) via a previous python function developed to facilitate this operation (CTDconversion). Furthermore, the evaluation of the new Scanpy-Nodes utilities (scNodes) through graphical workflow design software (KNIME) and biological/biomedical workflow web tool (GALAXY). Once the functionality of scNodes is assured, the design and implementation of single-cell best practices as workflows for the most common scRNA-seq analysis purposes.
Aims:
Phases of the project:
Kontakt: juan.henao@helmholtz-muenchen.de, benjamin.schubert@helmholtz- muenchen.de