FASTQ Processing, Quality Control & Read Trimming
From Bulk & scRNA-seq to Spatial Transcriptomics for Fighting Cancer 2026
Presented by Quynh Hoang
Date: Oct 18, 2026
Session ID: BU1.2
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TABLE OF CONTENTS
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What would you should after this lecture?
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Bulk RNA-seq: Upstream Analysis Workflow
INTRODUCTIONS
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Quality problems
RAW DATA PROCESSING
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Quality problems
RAW DATA PROCESSING
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Quality problems
RAW DATA PROCESSING
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Quality problems
RAW DATA PROCESSING
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1. FASTQ FILE STRUCTURE
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FASTQ Raw File Structure
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FASTQ Raw File Structure
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Illumina Header
Sequencer ID: A = NovaSeq, M = MiSeq, NB = NextSeq
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Illumina Header
No. of run on that instrument
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Illumina Header
Flowcell ID
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Illumina Header
Lane on that flowcell
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Illumina Header
Imaging tile within the lane
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Illumina Header
Cluster coordinates on that tile
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Illumina Header
Read: 1 (R1 = Forward), 2 (R2 = Reverse)
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Illumina Header
Filtered:
N = Passed, Y = Failed filter
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Illumina Header
0: Not a control read
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Illumina Header
Index: Sample barcode
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Illumina Header
Sequencer ID: A = NovaSeq, M = MiSeq, NB = NextSeq
No. of run on that instrument
Flowcell ID
Lane on that flowcell
Imaging tile within the lane
Cluster coordinates on that tile
Read: 1 (R1 = Forward), 2 (R2 = Reverse)
Filtered:
N = Passed,
Y = Failed filter
0: Not a control read
Index: Sample barcode
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2. SINGLE-END AND PAIRED-END SEQUENCING
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In single-end sequencing, a single set of a flow complementary sequence, index sequence and adaptor sequence has been used.
Only generate one read => A single FASTQ file.
SINGLE-END
Read 1
5'
3'
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Application:
SINGLE-END
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PAIRED-END
Read 1
Read 2
5'
3'
3'
5'
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Two reads are generated, known as forward and reverse reads (R1 and R2).
=> More no. of read => more accuracy of sequencing
Bridge amplification.
PAIRED-END
Index 1
P5
Adaptor
P7
Index 2
Adaptor
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PAIRED-END
PE provides high-quality alignment and sequencing of repetitive regions
Suitable for de novo sequencing; genetic splice variations, mutations
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Which is better ??
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3. PRED QUALITY SCORE
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Q = − 10 log10 P
Phred Quality Score | Probability of Incorrect Base Call | Base Call Accuracy |
10 | 1 in 10 | 90% |
20 | 1 in 100 | 99% |
30 | 1 in 1,000 | 99.9% |
40 | 1 in 10,000 | 99.99% |
PHRED-SCORE
Q scores are defined as a property that is logarithmically related to the base calling error probabilities (P).
Q score high => increase accuracy
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Q-SCORE
How confident the sequencer is that a base call is correct ?
Q = ASCII - 33
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ASCII TABLE
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A FASTQ quality character has an ASCII decimal value of 53 under Phred+33 encoding. What is the corresponding Phred quality score?
PRACTICE
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A FASTQ quality character has an ASCII decimal value of 53 under Phred+33 encoding. What is the corresponding Phred quality score?
Key: 53 − 33 = 20, so the corresponding Phred quality score is Q20
PRACTICE
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A base has a Phred quality score of Q30. What is its approximate sequencing error probability?
PRACTICE
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A base has a Phred quality score of Q30. What is its approximate sequencing error probability?
Key: Q30 corresponds to an error probability of 10⁻³, which is 0.1%
PRACTICE
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Under Phred+33 encoding, which quality character corresponds to Q35?
PRACTICE
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Under Phred+33 encoding, which quality character corresponds to Q35?
Key: ASCII 68 ⟶ character is D
PRACTICE
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Consider this FASTQ read under Phred+33 encoding:
ACGTA
+
5?I+D
What is the complete sequence of Phred quality scores for the five bases, in order? Use Q = ASCII − 33.
PRACTICE
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Consider this FASTQ read under Phred+33 encoding:
ACGTA
+
5?I+D
What is the complete sequence of Phred quality scores for the five bases, in order? Use Q = ASCII − 33.
Key: Q20, Q30, Q40, Q10, Q35
The quality characters 5, ?, I, +, and D have ASCII values 53, 63, 73, 43, and 68, which give Q20, Q30, Q40, Q10, and Q35.
PRACTICE
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4. QUALITY ASSESSMENT WITH FASTQC
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FASTQC
A Quality Control application for FastQ files
FastQC is a program designed to spot problems in high throughput sequencing datasets.
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FASTQC
It runs a set of analyses on one or more raw sequence files in fastq or bam format.
It will generate an HTML report for each file you process
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PER BASE SEQUENCE QUALITY
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PER TILE SEQUENCE QUALITY
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Does sequencing quality differ between different tiles on flow cell?
PER SEQUENCE QUALITY SCORE
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PER BASE SEQUENCE CONTENT
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PER SEQUENCE GC CONTENT
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PER BASE N CONTENT
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SEQUENCE LENGTH DISTRIBUTION
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SEQUENCE DUPLICATION LEVELS
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ADAPTER CONTENT
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5. MULTIQC REPORT AGGREGATION
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MULTIQC
MultiQC is a tool to create a single report with interactive plots for multiple bioinformatics analyses across many samples.
A single HTML report is generated summarising the statistics for all logs found.
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6. ADAPTER/QUALITY TRIMMING
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How to remove adapter sequences from sequencing read ??
Index 1
P5
Adaptor
P7
Index 2
Adaptor
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Quality trimming: remove low-quality bases
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TRIMMING TOOLS
A bioinformatics program that processes sequencing reads by removing unwanted parts: adapter sequences, low-quality bases.
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Trimming tools:
TRIMMING TOOLS
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FASTP
provide ultrafast all-in-one preprocessing and quality control for FastQ data
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TRIMMOMATIC
Palindrome mode => uses the read pair to detect even very short adapter read-through
Need adapter fasta file
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CUTADAP
Specific sequence need to be cut
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7. CREATING ENVIRONMENT AND INSTALLING TOOLS
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BIOCONDA
Install miniforge
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BIOCONDA
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Add channels into miniforge
BIOCONDA
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Create and Activate Environemnt
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Install Tools: A Brief Guide
List tools installed
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DOCUMENTS
Course Github repository: [Click here].
Practice examples: [Click here].
Data used for practice: Bioproject accession code PRJNA605185
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THANK YOU FOR YOUR ATTENTION!
From Bulk & scRNA-seq to Spatial Transcriptomics for Fighting Cancer 2026
Date: Oct 04, 2026
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