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update course for 2023-2024
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lievenclement committed Sep 19, 2023
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4 changes: 2 additions & 2 deletions README.md
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# Statistical Genomics Analysis, 2021-2022
# Statistical Genomics Analysis, 2023-2024

Course website at https://statomics.github.io/SGA21/.
Course website at https://statomics.github.io/SGA/.
48 changes: 2 additions & 46 deletions _site.yml
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Expand Up @@ -15,54 +15,10 @@ navbar:
- text: 1.2 Recap linear model
href: recapGeneralLinearModel.html
- text: ---- MODULE I PROTEOMICS ----
- text: 1. Proteomics Bioinformatics
href: docs/martens_proteomics_bioinformatics.pdf
- text: 2.1 Identification - FDR - QC
href: TargetDecoy.html
- text: 2.2.1. Quantification - Preprocessing
href: pda_quantification_preprocessing.html
- text: 2.2.2. Wrap-up Preprocessing - Peptide-Level-Models
href: pda_robustSummarisation_peptideModels.html
- text: 2.3.1. Quantification - Differential Abundance Analysis
href: pda_quantification_inference.html
- text: 2.3.2. Wrap-up DA - Blocking
href: pda_blocking_wrapup.html
- text: 2.3.3 Technical Details
href: technicalDetailsProteomics.html
- text: ---- MODULE I PROTEOMICS ----
- text: 1. Introduction to RNA-seq
href: sequencing_intro.html
- text: 2. Working with count data and GLMs
href: sequencing_countData.html


- text: "tutorials"
icon: fa-laptop
menu:
- text: ---- INTRODUCTION ----
- text: 1 Intro KPNA2
href: multipleRegression_KPNA2.html
- text: ---- MODULE I PROTEOMICS ----
- text: 1. Bioinformatics for Proteomics
href: https://www.compomics.com/bioinformatics-for-proteomics/
- text: 2.1. Target Decoy QC
href: TargetDecoyTutorial.html
- text: 2.2. Quantification - Preprocessing
href: pda_tutorialPreprocessing.html
- text: 2.3. Quantification - Design
href: pda_tutorialDesign.html
- text: ---- MODULE II RNA-seq ----
- text: 1. Read mapping
href: sequencingTutorial1_mapping.html
- text: 2. Working with Count Data
href: sequencingTutorial2_DE.html
- text: 3. Single Cell RNA-seq Data Analysis
href: scRNA-seq-Tutorial.html



right:
- icon: fab fa-github
href: https://github.com/statOmics/SGA21
href: https://github.com/statOmics/SGA
- text: "statOmics"
href: http://statomics.github.io/
output:
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7 changes: 5 additions & 2 deletions index.Rmd
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Expand Up @@ -25,7 +25,7 @@ This course is oriented towards biologists and bioinformaticians with a particul
# Prerequisites

The prerequisites for the Statistical Genomics Analysis course are the successful completion of a basic course of statistics that covers topics on data exploration and descriptive statistics, statistical modeling, and inference: linear models, confidence intervals, t-tests, F-tests, anova, chi-squared test.
The basis concepts may be revisited in the online course at https://statomics.github.io/PSLS/ (English) and in https://statomics.github.io/sbc21/ (Dutch).
The basis concepts may be revisited in the online course at https://statomics.github.io/PSLS/ (English) and in https://statomics.github.io/sbc/ (Dutch).

In addition, knowledge of programming in `R` is preferred. A primer to `R` and Data visualization in `R` can be found at:

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- Lecture: [HTML](./recapGeneralLinearModel.html), [PDF](./recapGeneralLinearModel.pdf)
- Tutorial KPNA2: [HTML](./multipleRegression_KPNA2.html), [PDF](./multipleRegression_KPNA2.pdf)
- link to a compressed figures directory: [download figures]("https://raw.githubusercontent.com/statOmics/SGA/master/figures.tar.gz")


<!--
## Module I: Proteomics Data Analysis (Week 1-5)
### 1. Bioinformatics for proteomics
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- Lecture Intro to scRNA-seq: [html](./sequencing_singleCell.html), [pdf](./sequencing_singleCell.pdf)
- Tutorial on scRNA-seq: [handout](./scRNA-seq-Tutorial.html)
-->
1,096 changes: 670 additions & 426 deletions intro.Rmd

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