1st lesson free
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Shah
- Rate R407
- Response 1h
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Students3
Number of students Shah has accompanied since joining Superprof
Number of students Shah has accompanied since joining Superprof
R407/h
Contact
1st lesson free
- Statistics
- School science
- Biochemistry
- Science Exam Preparation
- Quantitative methods
Metagenomics & microbiome data analysis — MetaPhlAn, HUMAnN, LEfSe, taught by a PhD researcher
- Statistics
- School science
- Biochemistry
- Science Exam Preparation
- Quantitative methods
Lesson location
About Shah
I'm a PhD researcher at SEMM working under Prof. Nicola Segata, whose group develops MetaPhlAn, HUMAnN, ChocoPhlAn and LEfSe — the standard toolkit for shotgun metagenomic profiling. I use these tools daily on real data, not from documentation.
My work covers taxonomic and functional profiling, strain-level analysis, and machine learning applied to microbiome datasets. I've also taught biology for 7 years, so I can explain why a method works, not just which command to type.
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About the lesson
- Primary
- Secondary
- Matric/GCSE
- +7
levels :
Primary
Secondary
Matric/GCSE
AS Level
A Level
BTech
Adult education
Masters
Doctorate
MBA
- English
Languages in which the lesson is available :
English
Metagenomics has a steep entry cost: the biology, the command line, and the statistics all have to click at once. I teach them together, using real data.
From sample to results — study design, 16S vs shotgun (and when each is the wrong choice), read QC, host decontamination, and what your sequencing depth actually supports.
Taxonomic and functional profiling — MetaPhlAn and HUMAnN end to end: running them, reading the output tables, and interpreting what a relative abundance profile does and doesn't tell you. Strain-level analysis and assembly-based approaches for those who need them.
Statistics and interpretation — alpha and beta diversity, compositional data and why standard methods mislead on it, differential abundance with LEfSe and alternatives, and multivariate testing. This is where most microbiome papers go wrong, so I spend real time here.
Machine learning on microbiome data — feature selection, cross-validation done correctly, and avoiding the overfitting that is endemic in this literature.
Your own dataset — bring your samples, your failing pipeline, or your thesis chapter. I'm happy to work through your actual analysis rather than a tutorial dataset.
For PhD and master's students, postdocs, and wet-lab researchers moving into computational microbiome work. Comfort with the command line helps but isn't required — we can start from bash basics. Online, in English, first lesson free to scope out what you need.
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Rates
Rate
- R407
Package rates
- 5h: R2035
- 10h: R4070
free lesson
The free first lesson with Shah allows you to get to know the tutor and discuss your needs and expectations.
- 1h
online
- R407/h
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