due dates

courses/cg/index.html

@@ -22,11 +22,11 @@ <h3>Schedule</h3>
       <li><a href="https://gear-genomics.embl.de/data/.slides/Lecture3_StructuralVariants.pdf">Lecture3 - Structural Variants</a></li>
       <li><a href="https://gear-genomics.embl.de/data/.slides/Lecture4_Epigenetics.pdf">Lecture4 - Cancer Epigenetics</a></li>
       <li>Wednesday 24th April, 9am-4pm: Biocev day (Lectures and Practicals)</li>
-      <li>Thursday 2th May, 12pm-2pm: Single-cell lecture (Zoom)</li>
-      <li>Thursday 9th May: Exercises and Questionnaires are due</li>
+      <li>Thursday 2th May, 12pm-2pm: RNA-Seq and scRNA-Seq lectures (Zoom)</li>
+      <li>Thursday 16th May: Exercises and Questionnaires are due</li>
     </ul>
 
-    <h3>Exercise 1: Variant Calling (due date 24th April 2024)</h3>
+    <h3>Exercise 1: Variant Calling (due date 2nd May 2024)</h3>
 
     Please create a GitHub account or login to your existing account and create a new repository to analyse sequencing data. The goal of this exercise is to create a simple variant calling workflow for human sequencing data. Please describe the steps of your workflow using markdown (<a href="https://docs.github.com/en/get-started/writing-on-github">GitHub Markdown</a>). The workflow should contain steps to align the FASTQ files to the human reference genome (<a href="https://github.com/lh3/bwa">bwa</a>), call variants (<a href="https://samtools.github.io/bcftools/howtos/variant-calling.html">bcftools</a>) and annotate all single-nucleotide variants with (<a href="https://www.ensembl.org/Tools/VEP">VEP</a>). For this excercise you can ignore all InDels. Once you have finished the exercise, send me the repository URL of your GitHub repository and the likely causative variant via email.
 
@@ -36,7 +36,7 @@ <h3>Exercise 1: Variant Calling (due date 24th April 2024)</h3>
       <li>FASTQ of read2, <a href="https://gear-genomics.embl.de/data/.slides/R2.fastq.gz">Read2</a></li>
     </ul>
 
-    <h3>Exercise 2: Cancer Genomics Data Analysis (due date 24th April 2024)</h3>
+    <h3>Exercise 2: Cancer Genomics Data Analysis (due date 2nd May 2024)</h3>
     In this exercise we want to analyze a cancer genomics sample, namely a paired tumor-normal sample pair.
     You can download the data set <a href="https://gear-genomics.embl.de/data/.exercise/">here</a>.
     The main objective of this exercise is to align the data to the human reference genome (<a href="https://hgdownload.soe.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz">https://hgdownload.soe.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz</a>), to sort and index the alignments and to generate a read-depth plot, as discussed in the lectures. Please note that I downsampled the dataset and I also just kept the data for chromosome X from 20Mbp to 40Mbp (GRCh37/hg19 coordinates) because otherwise all analysis take a lot of time for a human genome. Once you have generated the alignment in BAM format you can subset the BAM to the region of interest using `samtools view -b input.bam chrX:20000000-40000000 > output.bam`.
@@ -49,15 +49,15 @@ <h3>Exercise 2: Cancer Genomics Data Analysis (due date 24th April 2024)</h3>
     **Optional**: Once you have successfully computed a read-depth plot you may also want to call structural variants and overlay these with the read-depth plot as arcs or points that indicate SV breakpoints.
 
 
-    <h3>Exercise 3: Working with count matrices (due date 9th May 2024)</h3>
+    <h3>Exercise 3: Working with count matrices (due date 16th May 2024)</h3>
     In this exercise we want to run a differential gene expression analysis using an RNA-Seq count matrix (<a href="https://gear-genomics.embl.de/data/.slides/sample.counts">sample.counts</a>).
     The sample metadata is available here: <a href="https://gear-genomics.embl.de/data/.slides/sample.info">sample.info</a>.
     Starting from an <a href="https://gear-genomics.embl.de/data/.slides/template.R">Rscript template</a> please run a differential expression analysis, generate PCA, Heatmap and MA-plots and export the results into a CSV file.
     Once you are done please upload your Rscript to your GitHub repository and email me again the repository link, thanks!
     <br>
     **Optional**: You may also want to run a gene set enrichment analysis on the differentially expressed genes.
 
-    <h3>Exercise 4: Fill out the questionnaires (Google Forms, due date 9th May 2024)</h3>
+    <h3>Exercise 4: Fill out the questionnaires (Google Forms, due date 16th May 2024)</h3>
 
     To be sent via email on the 25th or 26th April.