Fietsgemiddelde kwaliteit plotten

Daar ben je! Klaar voor een kleine uitdaging? Test wat je hebt geleerd door drie snelle plots te maken. Je zult zien: het betaalt zich nu terug!

Jij bent aan zet om het nieuwe pakket Rqc te gebruiken en meerdere bestanden tegelijk te controleren.

Deze oefening maakt deel uit van de cursus

Introductie tot Bioconductor in R

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Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# Load package Rqc
library(Rqc)

# Average per cycle quality plot
___

Code bewerken en uitvoeren

Deze oefening maakt deel uit van de cursus

Introductie tot Bioconductor in R

SkillTag.level.intermediateSkillTag.label

4.8+

Begin de cursus gratis

In this chapter, you will get hands-on with Bioconductor. Bioconductor is the specialized repository for bioinformatics software, developed and maintained by the R community. You will learn how to install and use bioconductor packages. You'll be introduced to S4 objects and functions, because most packages within Bioconductor inherit from S4. Additionally, you will use a real genomic dataset of a fungus to explore the BSgenome package.

Exercise 1: Introduction to the Bioconductor Project Exercise 2: Bioconductor version Exercise 3: BiocManager to install packages Exercise 4: The role of S4 in Bioconductor Exercise 5: S4 class definition Exercise 6: Interaction with classes Exercise 7: Introducing biology of genomic datasets Exercise 8: Discovering the yeast genome Exercise 9: Partitioning the yeast genome Exercise 10: Available genomes

Biostrings are memory efficient string containers. Biostring has matching algorithms, and other utilities, for fast manipulation of large biological sequences or sets of sequences. How efficient you can become by using the right containers for your sequences? You will learn about alphabets, and sequence manipulation by using the tiny genome of a virus.

Exercise 1: Introduction to Biostrings Exercise 2: Exploring the Zika virus sequence Exercise 3: Biostrings containers Exercise 4: Manipulating Biostrings Exercise 5: Sequence handling Exercise 6: From a set to a single sequence Exercise 7: Subsetting a set Exercise 8: Common sequence manipulation functions Exercise 9: Why are we interested in patterns?Exercise 10: Searching for a pattern Exercise 11: Finding Palindromes Exercise 12: Finding a conserved region within six frames Exercise 13: Looking for a match

The IRanges and GenomicRanges packages are also containers for storing and manipulating genomic intervals and variables defined along a genome. These packages provide infrastructure and support to many other Bioconductor packages because of their enriching features. You will learn how to use these containers and their associated metadata, for manipulation of your sequences. The dataset you will be looking at is a special gene of interest in the human genome.

Exercise 1: IRanges and Genomic Structures Exercise 2: IRanges Exercise 3: Constructing IRanges Exercise 4: Interacting with IRanges Exercise 5: Gene of interest Exercise 6: From tabular data to Genomic Ranges Exercise 7: GenomicRanges accessors Exercise 8: ABCD1 mutation Exercise 9: Human genome chromosome X Exercise 10: Manipulating collections of GRanges Exercise 11: A sequence window Exercise 12: Is it there?Exercise 13: More about ABCD1 Exercise 14: How many transcripts?Exercise 15: From GRangesList object into a GRanges object

ShortRead is the package for input, manipulation and assessment of fasta and fastq files. You can subset, trim and filter the sequences of interest, and even do a report of quality. An extra bonus towards the last exercises will give you the tools for parallel quality assessment, wink, wink Rqc. Exciting enough, for this you will use plant genome sequences!

Exercise 1: Sequentie-bestanden Exercise 2: Waarom fastq?Exercise 3: Bestanden inlezen Exercise 4: Een fastq-bestand verkennen Exercise 5: Neem een steekproef uit een fastq-bestand Exercise 6: Sequentiekwaliteit Exercise 7: De kwaliteit van sequenties verkennen Exercise 8: Plot van basekwaliteit Exercise 9: Maak je eigen nucleotidenfrequentie-plot Exercise 10: Matchen en filteren Exercise 11: On-the-fly reads filteren!Exercise 12: Duplicaten verwijderen Exercise 13: Meer filteren!Exercise 14: Meervoudige beoordeling Exercise 15: Fietsgemiddelde kwaliteit plotten

Huidige oefening

Exercise 16: Introductie tot Bioconductor