Wayne:High Throughput Sequencing Resources: Difference between revisions

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== High throughput (HT) datatypes and workflow ==
== High throughput (HT) platform and read types ==
 
<u>Platform and read type</u><br>
<ul>
<ul>
<li> Illumina single-end vs. paired-end
<li> Illumina single-end vs. paired-end
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</ul>
</ul>


<u> File formats and conversions </u><br>
== File formats and conversions ==
<ul>
<ul>
<li> bcl
<li> bcl
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<br>
<br>


<u> Deplexing using barcoded sequence tags </u><br>
 
== Deplexing using barcoded sequence tags ==
<ul>
<ul>
<li> Editing (or hamming) distance
<li> Editing (or hamming) distance
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<br>
<br>


<u> Quality control </u><br>
 
== Quality control ==
<ul>
<ul>
<li> Fastx tools
<li> Fastx tools
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<br>
<br>


<u> Trimming and clipping </u><br>
 
== Trimming and clipping ==
<ul>
<ul>
<li> Trim based on low quality scored per nucleotide position within a read
<li> Trim based on low quality scored per nucleotide position within a read
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<br>
<br>


<u>DNA sequence analysis </u><br>
 
== DNA sequence analysis ==
<br>
<br>


<u>RNA-seq analysis</u><br>
 
== RNA-seq analysis ==
<ul>
<ul>
<li> Quantifying and annotating aligned reads
<li> Quantifying and annotating aligned reads

Revision as of 16:53, 15 February 2013

High throughput (HT) platform and read types

  • Illumina single-end vs. paired-end
  • 454 Roche
  • SOLiD
  • MiSeq
  • Ion Torrent

File formats and conversions

  • bcl
  • qseq
  • fastq



Deplexing using barcoded sequence tags

  • Editing (or hamming) distance



Quality control

  • Fastx tools
  • Using mapping as the quality control for reads



Trimming and clipping

  • Trim based on low quality scored per nucleotide position within a read
  • Clip sequence artefacts (e.g. adapters, primers)



DNA sequence analysis



RNA-seq analysis

  • Quantifying and annotating aligned reads
  • DESeq
  • edgeR

A variety of additional R packages are available for normalizing RNA-Seq read count data and identifying differentially expressed genes (DEG):

  • easyRNASeq (simplifies read counting per genome feature)
  • DEXSeq (Inference of differential exon usage)
  • DEGseq
  • baySeq (also see: segmentSeq)
  • Genominator (Bullard et al. 2010)

R basics

HT sequence analysis using R (and Bioconductor)