UNIT 2 Flashcards

1
Q

Mapping of Sequence Reads to Reference Genomes

A
  • Mapping of Sequence Reads
    • Fundamental technique in genomics and bioinformatics
    • Aligning reads to a reference genome
    • Underpins many downstream analyses
  • Key Concepts
    • Sequence reads
    • Reference genome
    • Alignment
    • Alignment algorithms and tools
  • The Mapping Process
    • Preprocessing of reads
    • Indexing the reference genome
    • Alignment
    • Post-alignment processing
  • Key Concepts
    • Mapping quality (MAPQ)
    • Unique vs. multi-mapping reads
    • Paired-end vs. single-end reads
    • Gapped vs. ungapped alignment
  • Importance of Read Mapping
    • Variant detection
    • Gene expression analysis
    • Genome assembly and structural variation
    • Comparative genomics
    • Clinical diagnostics
  • Challenges in Read Mapping
    • Repetitive regions
    • Structural variations
    • Sequencing errors
    • Computational demands
    • Genomic diversity
  • Tools and Algorithms
    • BWA, Bowtie, STAR, HISAT2, Minimap2, GMAP/GSNAP
    • Hash-based indexing, Burrows-Wheeler Transform, suffix arrays, seed-and-extend
  • Recent Advances
    • Long-read mapping
    • Graph-based references
    • Machine learning approaches
    • Cloud computing and parallelization
    • Real-time mapping
  • Practical Considerations
    • Choice of reference genome
    • Aligner selection
    • Parameter optimization
    • Quality control and validation
    • Handling multi-mapping reads
  • Conclusion
    • Essential technique in genomics
    • Enables accurate interpretation of sequencing data
    • Continuous advancements in tools and algorithms
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2
Q

Sequence Mapping and Read Mapping

A
  • Sequence Mapping
    • Computational process of aligning reads to a reference genome
    • Essential for understanding sequencing data
  • Key Concepts
    • Sequence reads
    • Reference genome
    • Alignment
    • Hashing-based methods (Bowtie, MAQ)
    • BWT-based methods (BWA, Bowtie2)
    • Seed-and-extend algorithms
    • Splice-aware mapping (STAR, HISAT2)
  • Challenges
    • Sequencing errors
    • Repetitive regions
    • Insertion/deletion (indel) handling
    • Large structural variations
    • Computational demands
    • Genetic diversity
  • Importance
    • Variant calling
    • RNA-Seq analysis
    • Functional genomics
    • Personalized medicine
    • Comparative genomics
  • Practical Considerations
    • Choice of reference genome
    • Aligner selection
    • Parameter optimization
    • Quality control
    • Handling multi-mapping reads
  • Conclusion
    • Fundamental technique in genomics
    • Essential for interpreting sequencing data
    • Continuous advancements in tools and algorithms
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3
Q

Read Sequence Alignment and Aligners

A
  • Read Sequence Alignment
    • Fundamental step in bioinformatics
    • Aligning reads to a reference genome
    • Essential for downstream analysis
  • Process
    • Preprocessing
    • Mapping
    • Scoring
    • Storing results (SAM/BAM)
  • SAM and BAM Formats
    • SAM: Text-based, human-readable
    • BAM: Binary, compressed, efficient
    • Mandatory and optional fields in SAM
  • Popular Alignment Tools
    • BWA (Burrows-Wheeler Aligner)
    • Bowtie/Bowtie2
    • STAR (Spliced Transcripts Alignment to a Reference)
    • HISAT2
    • Minimap2
  • Key Concepts
    • Mapping quality
    • Gapped vs. ungapped alignment
    • Paired-end vs. single-end reads
    • Structural variations
  • Challenges
    • Sequencing errors
    • Repetitive regions
    • Insertion/deletion (indel) handling
    • Large structural variations
    • Computational demands
    • Genetic diversity
  • Applications
    • Variant calling
    • Gene expression analysis
    • Genome assembly
    • Comparative genomics
    • Clinical diagnostics
  • Conclusion
    • Essential for understanding sequencing data
    • Variety of tools and algorithms available
    • Continuous advancements in the field
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4
Q

Manipulating Alignments in SAM/BAM Files

A
  • SAM/BAM Manipulation
    • Essential for preparing aligned reads for analysis
  • Common Operations
    • Conversion between SAM and BAM
    • Sorting alignments
    • Indexing BAM files
    • Filtering alignments
    • Marking and removing duplicates
    • Adding or modifying read groups
    • Merging and splitting BAM files
    • Realignment around indels and BQSR
  • Tools
    • SAMtools
    • Picard Tools
    • BEDTools
    • Sambamba
    • GATK
  • Best Practices
    • Start with high-quality alignments
    • Sort and index BAM files
    • Handle duplicates
    • Maintain read groups
    • Filter carefully
    • Document steps and parameters
    • Optimize computational resources
    • Validate manipulated files
  • Advanced Topics
    • Graph-based references
    • Handling multi-mapping reads
    • Integration with workflow managers
  • Conclusion
    • Critical for genomic data analysis
    • Mastery of tools and techniques essential
    • Adhere to best practices for data integrity and reproducibility
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