RADCamp Latin America 2026 Part II (Bioinformatics)
Day 2 (AM)
Overview of the activities:
- Exercise 1: Demultiplex your raw data
- Look at the real data
- Exercise 2: RADseq data quality control (QC)
- Coffee break
- Assemble real data
Demultiplex Empirical Data
Lead: Isaac (Could take all morning)
The first step in a RADSeq assembly is to evaluate the quality
of the raw data. It is typically more useful to do quality control
on a per-sample basis rather than on the full undemultiplexed raw
data file, so before we run fastqc we need to run ipyrad2 step 1
to demux raw data to samples.
- TODO: Where does the empirical data live?
- TODO: When are the barcodes files prepared?
Make a new directory and a new ipyrad2 params file for your empirical assembly
cd ~
mkdir <your_assembly_name>
cd <your_assembly_name>
ipyrad2-classic -n <your_assembly_name>
Edit params file to point to raw fastq data and barcodes file
Edit your new params file and set raw_fastq_path and
barcodes_path to the full path where these files are found.
Run step 1 to demultiplex your data
ipyrad2-classic -p params-<your_assembly_name> -s 1 -c 16
Quick check of demux process
Demux fastq files are stored in the *_fastqs directory, so take a look
in this directory to get a quick feel for how the data is distributed
among samples:
# `-l` gives a detailed (long) list
# `-h` shows file sizes in human readable format
ls -lh <your_assmbly_name>_fastqs
Question: Do most of your R1/R2 files for each sample show about the same size? Or are some much bigger or much smaller than average?
TODO FINISH
Empirical Data QC
Lead: Isaac (45’)
Now we will run fastqc on a couple of samples from the empirical data. To do
this we will first change directory (cd) to where the demultiplexed samples live,
inside ~/empirical/*_fastqs. Consult the fastqc exercise from yesterday
for how to run and interpret results.
In the remaining time choose 1-2 samples to run fastqc on both R1 and R2. After the runs finish, inspect the results and try to come to a conclusion about what the results indicate.
Be prepared to answer the following questions:
- Were there any significant quality issues with any of the samples?
- Was there noticeable adapter contamination?
Coffee break
Briefly report back on fastqc results
- Were there any significant problems with any of the samples?
- Was there noticeable adapter contamination?
- Other things you noticed? Any other questions?
Empirical assembly
You already started your empirical assembly when you ran Step 1 to demux your raw data to samples, so now you can continue with steps 2-5 to complete the assembly.
- Open a terminal window on your compute node and
cd ~/<your_empirical_assembly> - Run ipyrad2-classic step 2
ipyrad -p params-wat.txt -s 2 -c 16to trim and filter - While step 2 is running make an imap file for the samples you will want to use
to for construction of the pseudo-reference in step 3.
- Aim for broad and even taxonomic coverage
- More samples means longer runtimes. The default will choose 10 random samples, but 10 may be more than enough if all samples are from a single panmictic population.
- Make sure in your params file within the
[denovo]block to set theimapvalue to point to this file.
- Launch ipyrad2-classic steps 3-5
ipyrad -p params-wat.txt -s 345 -c 16 - After you verify that the assembly is running you may close your browser tab