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Module 8 — Text Editing & File Compression

Time: 75–90 min Goal: Master basic text editing with nano, work efficiently with compressed files, and verify file integrity with checksums. Exit ticket (email me): Your completed configuration file, checksum verification output, and analysis script.

What You'll Learn

By the end of this module, you will understand:

  • How to edit text files with nano
  • Essential nano keyboard shortcuts
  • How to safely edit configuration and script files
  • Why bioinformatics files are compressed
  • How to compress and decompress files with gzip
  • How to work with compressed files without decompressing them
  • How to verify file integrity with checksums (md5sum, sha256sum)
  • Best practices for handling large genomic datasets

Part 1: Text Editing with Nano

Why Learn a Terminal Text Editor?

In bioinformatics, you'll frequently need to: - Edit configuration files on remote servers - Fix script errors - Create analysis parameter files - Add comments to data files

You need a text editor that works in the terminal (no GUI required).

Popular terminal editors: - nano: Beginner-friendly, simple - vim/vi: Powerful but steep learning curve - emacs: Very powerful but complex

We'll learn nano because it's: - Pre-installed on most systems - Easy to use immediately - Has helpful hints displayed at the bottom - Perfect for quick edits

Starting Nano

nano filename.txt

If the file doesn't exist, nano creates it. If it exists, nano opens it for editing.

Practice: 

cd ~/bioinfo-course
mkdir -p module08
cd module08

nano my_notes.txt

You'll see the nano editor interface:

  GNU nano 5.4                my_notes.txt

[Blank editing area]


















^G Get Help  ^O Write Out  ^W Where Is   ^K Cut Text   ^J Justify
^X Exit      ^R Read File  ^\ Replace    ^U Paste Text ^T To Spell

The ^ symbol means Ctrl. So ^X means Ctrl+X.

Basic Nano Operations

Typing Text

Just start typing! Nano works like a simple text editor.

This is my first note.
I can type multiple lines.
It's very straightforward!

Moving Around

Key Action
Arrow keys Move cursor
Ctrl+A Jump to beginning of line
Ctrl+E Jump to end of line
Ctrl+Y Page up
Ctrl+V Page down
Ctrl+_ (underscore) Go to line number

Saving (Writing Out)

  1. Press Ctrl+O (Write Out)
  2. Nano asks: File Name to Write: my_notes.txt
  3. Press Enter to confirm

You'll see: [ Wrote 3 lines ]

Exiting

Press Ctrl+X

If you have unsaved changes, nano asks: 

Save modified buffer?
 Y Yes
 N No           ^C Cancel

  • Y: Save and exit
  • N: Exit without saving
  • Ctrl+C: Cancel and return to editing

Practice: Your First Edit

nano practice.txt
  1. Type several lines of text
  2. Press Ctrl+O to save
  3. Press Enter to confirm filename
  4. Press Ctrl+X to exit

Verify your file: 

cat practice.txt

Essential Nano Shortcuts

Cutting, Copying, and Pasting

Shortcut Action How It Works
Ctrl+K Cut line Cuts current line to clipboard
Alt+6 Copy line Copies current line without deleting
Ctrl+U Paste Pastes clipboard content

Practice: 

nano cut_paste_practice.txt

Type: 

Line 1
Line 2
Line 3
Line 4

  1. Move cursor to Line 2
  2. Press Ctrl+K (cuts the line)
  3. Move cursor to end of file
  4. Press Ctrl+U (pastes it)

Result: 

Line 1
Line 3
Line 4
Line 2

To cut multiple lines: 1. Press Ctrl+K multiple times 2. All cut lines are in the clipboard 3. Press Ctrl+U to paste them all

Searching

Shortcut Action
Ctrl+W Search ("Where Is")
Alt+W Find next occurrence
Ctrl+\ Search and replace

Practice: 

nano search_practice.txt

Type: 

The quick brown fox
jumps over the lazy dog.
The dog is sleeping.
The fox is running.

Save it (Ctrl+O, Enter).

Now: 1. Press Ctrl+W 2. Type dog 3. Press Enter

Cursor jumps to the first "dog".

Press Alt+W to find the next occurrence.

Search and Replace

  1. Press Ctrl+\ (backslash)
  2. Search: Type what to find (e.g., dog)
  3. Press Enter
  4. Replace with: Type replacement (e.g., cat)
  5. Press Enter
  6. Nano asks: Replace this instance?
  7. Y: Replace this one
  8. N: Skip this one
  9. A: Replace all
  10. Ctrl+C: Cancel

Practice: Replace all "dog" with "cat" in your file.

Undoing and Redoing

Shortcut Action
Alt+U Undo
Alt+E Redo

Note: On some systems, these might not work. Nano's undo is limited compared to GUI editors, so save frequently!

Getting Help

Press Ctrl+G to see the full help system. Press Ctrl+X to exit help.

Complete Nano Keyboard Shortcut Table

Shortcut Action
Ctrl+O Write Out (save)
Ctrl+X Exit
Ctrl+G Get Help
Ctrl+K Cut line
Ctrl+U Paste (Uncut)
Alt+6 Copy line
Ctrl+W Search (Where Is)
Alt+W Find next
Ctrl+\ Search and replace
Ctrl+A Beginning of line
Ctrl+E End of line
Ctrl+Y Page up
Ctrl+V Page down
Ctrl+_ Go to line number
Alt+U Undo
Alt+E Redo
Ctrl+C Show cursor position / Cancel
Ctrl+R Read (insert) another file

Real Bioinformatics Use Cases

Use Case 1: Editing a Configuration File

nano analysis_config.txt

Type: 

# Analysis Configuration
reference_genome=/data/refs/hg38.fa
input_fastq=/data/samples/patient001_R1.fastq.gz
output_dir=/results/patient001
threads=8
min_quality=20

Save and exit.

Use Case 2: Creating a Sample Manifest

nano samples.tsv

Type: 

SampleID    Condition   Batch   Replicate
S001    control Batch1  Rep1
S002    control Batch1  Rep2
S003    treated Batch1  Rep1
S004    treated Batch1  Rep2

(Use Tab key between columns for proper TSV format)

Use Case 3: Quick Script Fix

You have a script with an error: 

nano analysis.sh

Original: 

#!/bin/bash
fastqc input.fastq -o results/
# Oops, typo below:
multiqc resutls/ -o report/

Fix: 1. Press Ctrl+W, search for resutls 2. Press Ctrl+\, replace resutls with results 3. Save and exit

Part 2: File Compression

Why Compress Files in Bioinformatics?

Genomic data files are huge: - A single human genome FASTQ: ~200 GB uncompressed - Compressed with gzip: ~60 GB (70% reduction!) - A single RNA-seq sample: 5-20 GB compressed

Compression saves: - Disk space - Transfer time - Storage costs

Common compressed formats: - .gz — gzip compression (most common) - .bz2 — bzip2 compression (better compression, slower) - .zip — ZIP archive (common on Windows) - .tar.gz or .tgz — Compressed archive (multiple files)

In bioinformatics, gzip (.gz) is the standard.

Compressing Files with gzip

gzip compresses files and adds a .gz extension.

gzip filename

Important: This deletes the original file!

Practice: 

cd ~/bioinfo-course/module08

# Create a test file
echo "This is a test file with some repeated text text text text" > test.txt

# Check size
ls -lh test.txt

# Compress it
gzip test.txt

# Check size and name
ls -lh test.txt.gz

The original test.txt is gone, replaced by test.txt.gz.

Keep the Original: gzip -c

To keep the original, use -c (write to stdout) and redirect:

gzip -c test.txt > test.txt.gz

Now both test.txt and test.txt.gz exist.

Decompress with gunzip

gunzip test.txt.gz

This deletes test.txt.gz and creates test.txt.

Or keep the compressed file: 

gunzip -c test.txt.gz > test.txt

Useful gzip Options

Option What It Does Example
-c Write to stdout (keep original) gzip -c file > file.gz
-d Decompress (same as gunzip) gzip -d file.gz
-k Keep original file gzip -k file
-1 to -9 Compression level (1=fast/big, 9=slow/small) gzip -9 file
-l List compressed file info gzip -l file.gz
-r Recursively compress directory gzip -r directory/
-t Test integrity gzip -t file.gz

Check Compression Ratio

gzip -l test.txt.gz

Output: 

         compressed        uncompressed  ratio uncompressed_name
                 42                  61  50.8% test.txt

Working with Compressed Files WITHOUT Decompressing

This is crucial for bioinformatics! You don't want to decompress a 60 GB FASTQ file just to look at it!

View with zcat (Compressed cat)

zcat file.gz

Example: 

cd ~/bioinfo-course/module08

# Create and compress a test file
cat > sequences.txt << 'EOF'
>Seq1
ATGCGCTAG
>Seq2
GCTAGCTAC
>Seq3
TACGATCGA
EOF

gzip sequences.txt

# View without decompressing
zcat sequences.txt.gz

Output: 

>Seq1
ATGCGCTAG
>Seq2
GCTAGCTAC
>Seq3
TACGATCGA

The file stays compressed!

View with zless (Compressed less)

zless file.gz

Same navigation as less (Space, b, q, /search, etc.).

Perfect for previewing large compressed FASTQ files: 

zless sample001_R1.fastq.gz

Search with zgrep (Compressed grep)

zgrep 'pattern' file.gz

Example: 

# Count sequences in a compressed FASTA
zgrep -c '^>' sequences.txt.gz

Output: 3

Process with Pipes

# Count lines in compressed file
zcat file.gz | wc -l

# Extract sequences from compressed FASTA
zcat sequences.txt.gz | grep -v '^>'

# Get first 1000 reads from compressed FASTQ
zcat sample_R1.fastq.gz | head -n 4000 | less

OS-Specific Note for macOS

Use: zcat, zless, zgrep

Use: gzcat, zless, zgrep

Or create aliases: 

alias zcat='gzcat'

Practical Example: FASTQ File Inspection

cd ~/bioinfo-course/module08

# Create a mock FASTQ file
cat > sample.fastq << 'EOF'
@Read1
ATGCGCTAG
+
IIIIIIIII
@Read2
GCTAGCTAC
+
IIIIIIIII
@Read3
TACGATCGA
+
IIIIIIIII
EOF

# Compress it
gzip sample.fastq

# Preview first read (4 lines)
zcat sample.fastq.gz | head -n 4

# Count total reads (number of lines / 4)
echo "$(( $(zcat sample.fastq.gz | wc -l) / 4 )) reads"

# Count reads with quality score 'I' (high quality)
zgrep -c 'IIIIIIIII' sample.fastq.gz

# Extract just the sequences (every 2nd line starting from line 2)
zcat sample.fastq.gz | awk 'NR % 4 == 2'

Part 3: Checksums — Verify File Integrity

What is a Checksum?

A checksum is a unique "fingerprint" of a file's contents. Even changing a single byte produces a completely different checksum.

Uses: - Verify file wasn't corrupted during download/transfer - Confirm file hasn't been modified - Compare files quickly without reading entire contents

Common algorithms: - MD5: 128-bit hash (fast, but cryptographically weak) - SHA-256: 256-bit hash (secure, standard for verification)

Generating Checksums

MD5 Checksum

md5sum filename

md5 filename

Example: 

cd ~/bioinfo-course/module08

echo "Important data" > data.txt

# Generate MD5 checksum (Linux/WSL)
md5sum data.txt

Output: 

3c5d4c68d9fc9a1b8e8c8a5c3f7e5f9a  data.txt

The first part is the checksum (32 hexadecimal characters).

sha256sum filename

shasum -a 256 filename

Example: 

sha256sum data.txt

Output: 

a7e2c4f5d8b9e1c3a6f4d2b8e5c9f1a3d7b2e8c4f6a1d9b5c2e8f4a7d3b6e1c5  data.txt

(64 hex characters)

Saving and Verifying Checksums

Save Checksum to File

sha256sum data.txt > data.txt.sha256
cat data.txt.sha256

Output: 

a7e2c4f5d8b9e1c3a6f4d2b8e5c9f1a3d7b2e8c4f6a1d9b5c2e8f4a7d3b6e1c5  data.txt

Verify Checksum Later

sha256sum -c data.txt.sha256

shasum -a 256 -c data.txt.sha256

Output: 

data.txt: OK

This confirms the file hasn't changed.

Test: Modify the File

# Change the file slightly
echo "Modified data" > data.txt

# Verify again
sha256sum -c data.txt.sha256

Output: 

data.txt: FAILED
sha256sum: WARNING: 1 computed checksum did NOT match

The checksum detected the change!

Real Bioinformatics Use Case: Download Verification

When downloading genomic data, you should always verify checksums.

Example workflow:

# Download FASTQ file (simulated)
curl -O ftp://data.server.edu/sample001_R1.fastq.gz

# Download checksum file
curl -O ftp://data.server.edu/sample001_R1.fastq.gz.md5

# Verify
md5sum -c sample001_R1.fastq.gz.md5

If it says "OK", your download is complete and uncorrupted!

Generate Checksums for Multiple Files

# Generate checksums for all FASTQ files
sha256sum *.fastq.gz > all_samples.sha256

# Verify all at once later
sha256sum -c all_samples.sha256

Output: 

sample001_R1.fastq.gz: OK
sample001_R2.fastq.gz: OK
sample002_R1.fastq.gz: OK
sample002_R2.fastq.gz: OK

Practice Exercises

Exercise 1: Create and Edit a Script

cd ~/bioinfo-course/module08
nano qc_script.sh

Type: 

#!/bin/bash
# Quality control script for RNA-seq samples

SAMPLE_ID="sample001"
INPUT_DIR="/data/raw_fastq"
OUTPUT_DIR="/results/qc"

echo "Starting QC for $SAMPLE_ID"
mkdir -p $OUTPUT_DIR

# Placeholder for FastQC
echo "Running FastQC..."
# fastqc ${INPUT_DIR}/${SAMPLE_ID}_R1.fastq.gz -o $OUTPUT_DIR

echo "QC complete!"

Save (Ctrl+O, Enter), then exit (Ctrl+X).

Verify: 

cat qc_script.sh

Exercise 2: Compress and Verify

# Create a data file
cat > experiment_results.txt << 'EOF'
Sample,ReadCount,MappingRate
S001,25000000,95.2
S002,26000000,94.8
S003,24500000,93.1
EOF

# Generate checksum BEFORE compression
sha256sum experiment_results.txt > experiment_results.txt.sha256

# Compress
gzip -k experiment_results.txt

# Verify original (should work)
sha256sum -c experiment_results.txt.sha256

# Try to view compressed without decompressing
zcat experiment_results.txt.gz | head

Exercise 3: FASTQ Simulation

# Create a larger mock FASTQ
cat > reads.fastq << 'EOF'
@Read1
ATGCGCTAGCTAGCTAGCTAGCTAGCT
+
IIIIIIIIIIIIIIIIIIIIIIIIIII
@Read2
GCTAGCTACGATCGATCGATCGATCG
+
IIIIIIIIIIIIIIIIIIIIIIIIIII
@Read3
TACGATCGAGCTAGCTAGCTAGCTAG
+
IIIIIIIIIIIIIIIIIIIIIIIIIII
@Read4
ATCGATCGATCGATCGATCGATCGAT
+
IIIIIIIIIIIIIIIIIIIIIIIIIII
@Read5
GCTAGCTAGCTAGCTAGCTAGCTAGC
+
IIIIIIIIIIIIIIIIIIIIIIIIIII
EOF

# Compress
gzip reads.fastq

# Count reads
echo "$(( $(zcat reads.fastq.gz | wc -l) / 4 )) reads total"

# Extract just sequence IDs
zcat reads.fastq.gz | grep '^@' | cut -c 2-

# Extract just sequences
zcat reads.fastq.gz | awk 'NR % 4 == 2'

# Find reads containing "GCTAGC" motif
zgrep 'GCTAGC' reads.fastq.gz

The Exit Ticket Challenge: Complete Workflow

Scenario

You're setting up a bioinformatics analysis. Create configuration files, compress data, and verify integrity.

Tasks

Task 1: Create an analysis configuration file

nano analysis_config.txt

Include: - Reference genome path - Input FASTQ paths (sample001_R1.fastq.gz, sample001_R2.fastq.gz) - Output directory - Number of threads (8) - Minimum quality score (20)

Task 2: Create a sample manifest in TSV format

nano sample_manifest.tsv

Include 5 samples with columns: - SampleID - Condition (control or treated) - Batch - ReadCount - QC_Status (pass/fail)

Task 3: Create a mock FASTQ file with 10 reads

nano reads.fastq

Use proper FASTQ format (4 lines per read).

Task 4: Compress the FASTQ file, keeping the original

Task 5: Generate SHA-256 checksums for: - The uncompressed FASTQ - The compressed FASTQ - The manifest file

Save all checksums to checksums.sha256

Task 6: Verify all checksums

Task 7: Without decompressing, count the number of reads in the compressed FASTQ

Task 8: Create a simple analysis script (run_analysis.sh) that: - Prints "Analysis started" - Prints the sample ID and paths from your config file (just echo statements) - Prints "Analysis complete"

Make the script executable and test it: 

chmod +x run_analysis.sh
./run_analysis.sh

Quick Reference

Nano Shortcuts

Shortcut Action
Ctrl+O Save (Write Out)
Ctrl+X Exit
Ctrl+K Cut line
Ctrl+U Paste (Uncut)
Ctrl+W Search
Ctrl+\ Replace
Ctrl+A Start of line
Ctrl+E End of line
Alt+U Undo
Ctrl+G Help

Compression

Command What It Does
gzip file Compress (deletes original)
gzip -k file Compress (keeps original)
gzip -c file > file.gz Compress to stdout
gunzip file.gz Decompress (deletes .gz)
zcat file.gz View compressed file
zless file.gz Page through compressed file
zgrep pattern file.gz Search compressed file
gzip -l file.gz Show compression info

Checksums

Command What It Does
md5sum file Generate MD5 checksum (Linux)
sha256sum file Generate SHA-256 checksum (Linux)
shasum -a 256 file Generate SHA-256 checksum (macOS)
sha256sum -c file.sha256 Verify checksum (Linux)
shasum -a 256 -c file.sha256 Verify checksum (macOS)

Exit Ticket

To complete this module, send me an email with:

Subject: Bioinfo M8 Exit Ticket – [Your Name]

Content:

  1. Contents of your analysis_config.txt
  2. Contents of your sample_manifest.tsv
  3. Output of checksum verification (sha256sum -c checksums.sha256)
  4. The command you used to count reads in the compressed FASTQ
  5. Contents of your run_analysis.sh script
  6. One paragraph (3-4 sentences) explaining why compression and checksums are important in bioinformatics

Summary

Congratulations! You now understand:

✓ How to edit text files with nano ✓ Essential nano keyboard shortcuts for efficient editing ✓ How to safely edit configuration files and scripts ✓ Why compression is critical for genomic data ✓ How to compress and decompress files with gzip ✓ How to work with compressed files without decompressing (zcat, zless, zgrep) ✓ How to verify file integrity with checksums (md5sum, sha256sum) ✓ Best practices for handling large genomic datasets

These skills are foundational! You'll use them constantly when: - Editing configuration files for bioinformatics tools - Working with compressed FASTQ/BAM files - Verifying downloaded datasets - Creating and modifying analysis scripts - Managing disk space efficiently

In the next module, we'll dive into advanced text processing with awk—a powerful tool for manipulating tabular data.

Next: Module 9 — Advanced Text Processing with awk