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+# ML-Final-Project
+
+## Introduction
+
+The inspiration for this project comes from the publication: Novel Biomarker Prediction for Lung Cancer Using Random Forest Classifiers
+(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10126698/)
+
+The data used for this analysis is Illumina Hiseq2500 RNA-seq data found at NCBI SRA under the project ID SRP117020. Samples were obtained from 130 patients diagnosed with non-small cell lung cancer (NSCLC).
+The data contains sequences with distribution of poor to well differentiated adenocarcinomas and squamous cell cancers
+
+The reference genome used for alignment can be found here: https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.26/.
+
+### Project Overview 
+
+```mermaid
+graph TD;
+    RNA_seq_FASTQs-->Reference_Genome_Alignment_HISAT2;
+    RNA_seq_FASTQs-->FastQC;
+    Reference_Genome_Alignment_HISAT2-->Transcript_Quantification/Merging_StringTie;
+    Transcript_Quantification/Merging_StringTie-->Differential_Expression_DESeq2;
+    Differential_Expression_DESeq2-->Pathway_Analysis_KOBAS;
+    Differential_Expression_DESeq2-->SCLC/NSCLC_Gene_Classification;
+    Pathway_Analysis_KOBAS-->SCLC/NSCLC_Gene_Classification;
+    Differential_Expression_DESeq2-->Dataset_Annotation;
+    Pathway_Analysis_KOBAS-->Dataset_Annotation;
+    Dataset_Annotation-->Data_Preprocessing;
+    Data_Preprocessing-->Maching_Learning_Models;
+    Maching_Learning_Models-->Logistic_Regression;
+    Maching_Learning_Models-->Random_Forest;
+    Maching_Learning_Models-->Gradient_Boost;
+    Maching_Learning_Models-->AdaBoost;
+    Maching_Learning_Models-->KNN;
+```
+
+#### Data Preparation (Part I)
+
+Preparation of the data for the ML algorithms includes a pipeline containing various bioinformatics tools:
+```mermaid
+graph TD;
+    SRA_accessions.txt-->SRA-Toolkits/prefetch;
+    SRA-Toolkits/prefetch-->.sra_files;
+    .sra_files-->fastq-dump;
+    fastq-dump-->untrimmed_fastqs;
+    untrimmed_fastqs-->FastQC;
+    FastQC-->MultiQC
+    MultiQC-->untrimmed_quality_report
+    untrimmed_fastqs-->fastp;
+    fastp-->trimmed_fastq_files;
+    trimmed_fastq_files-->FastQC2;
+    FastQC2-->MultiQC2;
+    MultiQC2-->trimmed_quality_report
+    trimmed_fastq_files-->HISAT2;
+```
+
+* To use SRA-Toolkits prefetch to retrieve all samples:
+``` 
+while read accession; do
+  prefetch "$accession"
+done < SRA_accessions.txt`
+```
+
+* To convert all paired sample .sra files to fastq files:
+```
+for dir in SRR*/; do
+    echo "Processing $dir"
+    fastq-dump --split-files --gzip "$dir/${dir%/}.sra"
+done
+```
+
+
+* To trim all fastq samples:
+```
+for file in *_1.fastq; do
+    base=$(basename "$file" "_1.fastq")
+    fastp -i "${base}_1.fastq" -I "${base}_2.fastq" -o "../FASTQ_SAMPLES_TRIMMED/${base}_1_trimmed.fq" -O "../FASTQ_SAMPLES_TRIMMED/${base}_2_trimmed.fq"
+done
+```
+
+* Align reads to the reference genome using `alignments.sh` script:
+```
+chmod +x alignment.sh
+./alignment.sh
+```
+