Fachprojekt:

Reproduzierbare Datenanalyse mit Snakemake am Beispiel der Bioinformatik

Johannes Köster

 

University of Duisburg-Essen

Data Analysis

Data analysis

dataset

results

Steps:

  • aggregation
  • transformation
  • filtration
  • visualization

Via:

  • command line tools
  • small scripts

Data analysis

dataset

results

dataset

dataset

dataset

dataset

dataset

Data analysis

dataset

results

dataset

dataset

dataset

dataset

dataset

From raw data to final figures:

  • document parameters, tools, versions
  • execute without manual intervention

automation

Data analysis

dataset

results

dataset

dataset

dataset

dataset

dataset

scalability

Handle parallelization:

execute for tens to thousands of datasets

Avoid redundancy:

  • when adding datasets
  • when resuming from failures

automation

dataset

results

dataset

dataset

dataset

dataset

dataset

Handle deployment:

be able to easily execute analyses on a different system/platform/infrastructure

portability

scalability

automation

Reproducible data analysis

Bioinformatics

www.copdri.com 2016

Cells

www.austincc.edu 2016

Chromosomes

www.medicalxpress.com 2016

Genes

biosocialmethods.isr.umich.edu 2016

From genes to proteins

Transcript activity/expression:

the more RNA, the more protein

transcript

DNA:

  • made of 4 nucleotides: Adenine, Guanine, Cytosine, Thymine
  • a text over the alphabet \(\{A, C, G, T \}\)

Questions

  • Which mutations does the genome of a patient contain?
  • Which transcripts are particularly active/inactive with a certain disease?
  • Which bacteria appear in a sample?
  • Who is the murder?

Methods

  • statistical modelling
  • algorithm and data structure engineering
  • machine learning
  • data analysis

Here: Analysis of RNA-sequencing data

Illumina Inc. 2018

Illumina sequencing

en.wikipedia.org 2018

Illumina sequencing

en.wikipedia.org 2018

Illumina sequencing

en.wikipedia.org 2018

Result:

short, (paired-end) Reads

Transcript quantification with RNA-sequencing

en.wikipedia.org 2018

  • obtain many short reads from RNA (50-100 million)
  • map them against a reference genome
  • quantify transcript expression by counting reads on each transcript

...ACGCTAGCAGCGTAGCGGAGCTATTGCGGAGCTGAGCGTATCGGAGAGATCGGATCTGGATCGAGATCTGAGCTGAGCTAGCTGGCTAGCGATCGGAGGAGCTAGCGATATTCGAGGAGGCGTATCGTAGC...

Gene and transcript sequence

CGGAGCTATTGCGG

GGAGCTATTGCGGA

GGATCGAGATCT

GGATCGAGATCT

CGGAGGAGCTAG

CGGAGGAGCTAG

TCGGAGGAGCTA

Semesterplan

Phase 1

Phase 2

Phase 3

 

11.10.2018 Einführung, Snakemake-Tutorial
18.10.2018 Snakemake-Tutorial
25.10.2018 Snakemake-Tutorial
01.11.2018 Vorbereitung der Vorträge
08.11.2018 Vorbereitung der Vorträge
15.11.2018 Vorträge (je 30min)
22.11.2018 Implementierung des Workflows
29.11.2018 Implementierung des Workflows
06.12.2018 Implementierung des Workflows
13.12.2018 Implementierung des Workflows
20.12.2018 Implementierung des Workflows
10.01.2019 Implementierung des Workflows
17.01.2019 Implementierung des Workflows
24.01.2019 Vorbereitung der Abschlusspräsentationen
31.01.2019 Abschlusspräsentationen

Phase 4

Fachprojekt: Reproduzierbare Datenanalyse mit Snakemake

By Johannes Köster

Fachprojekt: Reproduzierbare Datenanalyse mit Snakemake

  • 377
Loading comments...

More from Johannes Köster