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Setup CI/CD Pipeline for MSStats #143
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PR Reviewer Guide 🔍Here are some key observations to aid the review process:
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PR Code Suggestions ✨Explore these optional code suggestions:
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mkdir -p ~/.ssh | ||
echo "${{ secrets.SSH_PRIVATE_KEY }}" > ~/.ssh/id_rsa | ||
chmod 600 ~/.ssh/id_rsa |
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I would follow ChatGPT's suggestion here.
#SBATCH --time=01:00:00 # Set the maximum run time | ||
#SBATCH --ntasks=1 # Number of tasks (one process) | ||
#SBATCH --cpus-per-task=8 # Use 8 CPU cores for the task | ||
#SBATCH --mem=128G # Request 256GB of memory |
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Comment says 256, but says 128 here.
mkdir -p ~/.ssh | ||
echo "${{ secrets.SSH_PRIVATE_KEY }}" > ~/.ssh/id_rsa | ||
chmod 600 ~/.ssh/id_rsa | ||
ssh-keyscan -H login-00.discovery.neu.edu >> ~/.ssh/known_hosts |
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I think we should follow chatGPT's suggestion here (the error handling one)
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- name: Fetch Output | ||
run: | | ||
scp raina.ans@login-00.discovery.neu.edu:/home/raina.ans/R/job_output.txt job_output.txt |
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There seems to be a lot of dependency on using your /home/raina.ans
folder. Could we instead use a folder in the /work/VitekLab
directory? I think there's already a benchmarking folder in there.
# boxplot(human_comparisonResult$log2FC, | ||
# main = "Boxplot of log2FC for Human", | ||
# ylab = "log2FC", | ||
# col = "lightblue") |
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If you're not using the code, could you remove the comments?
fragpipe_raw$Condition = unlist(lapply(fragpipe_raw$Run, function(x){ | ||
paste(str_split(x, "\\_")[[1]][4:5], collapse="_") | ||
})) | ||
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fragpipe_raw$BioReplicate = unlist(lapply(fragpipe_raw$Run, function(x){ | ||
paste(str_split(x, "\\_")[[1]][4:7], collapse="_") | ||
})) |
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I thought the Fragpipe files already have BioReplicate and Condition information
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Could you use the dataset stored in the /work/VitekLab/Data/MS/Benchmarking
directory? It should have the name MSstats.csv
label = "Data process without Normalization", | ||
result = function() dataProcess(msstats_format, normalization = "FALSE", n_top_feature = 20) | ||
), | ||
list( | ||
label = "Data process without Normalization with MBImpute False", | ||
result = function() dataProcess(msstats_format, normalization = "FALSE", n_top_feature = 20, MBimpute = FALSE) | ||
) |
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Does n_top_feature
parameter need to be initialized to anything here? i thought it's only needed if featureSubset = "topN"
- name: Fetch Output | ||
run: | | ||
scp raina.ans@login-00.discovery.neu.edu:/home/raina.ans/R/job_output.txt job_output.txt | ||
scp raina.ans@login-00.discovery.neu.edu:/home/raina.ans/R/job_error.txt job_error.txt |
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I'm wondering if it makes sense to use a login info for someone like Olga. I'm not sure if she has an OOD account though. Or maybe use my login.
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How difficult would it be to use someone else's login. What would we need to adjust?
User description
Motivation and Context
Part of Dataset Benchmarking Task
Changes
Please provide a detailed bullet point list of your changes.
Testing
Please describe any unit tests you added or modified to verify your changes.
Checklist Before Requesting a Review
PR Type
enhancement, tests
Description
Changes walkthrough 📝
slurm_poc.yml
Add GitHub Actions workflow for HPC integration using Slurm
.github/workflows/slurm_poc.yml
benchmark.R
Add benchmarking script with data processing and analysis
benchmark/benchmark.R
config.slurm
Create Slurm configuration script for benchmarking job
benchmark/config.slurm