YOU ARE HERE PUBLICSCIENTIST WEBSITE

Bioinformatics

Quality Control, trimming and alignment of Bisulfite-Seq data (Prot 57)

Felix Krueger, Simon R Andrews

Introduction

Dramatic improvements and falling costs of high throughput sequencing have made bisulfite sequencing (BS-Seq) a viable option for the global analysis of DNA methylation (Bock et al, 2011; Li et al, 2010; Lister et al, 2009; Lister et al, 2011; Meissner et al, 2008; Stadler et al, 2011; Xie et al, 2012). The analysis of methylation obtained from BS-Seq is relatively straight forward, but care should be taken for initial quality control, trimming and suitable alignment of BS-Seq libraries since these are susceptible to a variety of errors or biases that one could probably get away with in other sequencing applications (discussed in (Krueger et al, 2012)). [...]

PDF version

Felix Krueger, Simon R Andrews

Bioinformatics Group, The Babraham Institute, Cambridge, CB22 3AT, United Kingdom

Corresponding author: Felix Krueger & Simon R Andrews
Email feedback to: This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Felix Krueger, Simon R Andrews
 

A pipeline for ChIP-seq data analysis (Prot 56)

Ruhi Ali1, Florence M.G. Cavalli1, Juan M. Vaquerizas1, Nicholas M. Luscombe2,3

Introduction

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is becoming the standard experimental procedure to investigate transcriptional regulation and epigenetic mechanisms on a genome-wide scale (reviewed in (Park, 2009)). The technique involves covalent cross-linking of proteins to the DNA, followed by fragmentation and immunoprecipitation (IP) of the chromatin by using an antibody against the protein or histone modification of interest. The result of this experiment is a set of short DNA fragments of about 200 bp in length that represent regions of the genome where the protein is bound, or where specific histone modifications occurred. The segments are then sequenced using one of the various next generation sequencing procedures now available. The resulting reads (usually 36 to 100bp) are then mapped back to the reference genome of interest in order to identify regions with significant binding [...]

PDF version

Ruhi Ali1, Florence M.G. Cavalli1, Juan M. Vaquerizas1, Nicholas M. Luscombe2,3

1 European Bioinformatics Institute. Wellcome Trust Genome Campus, Cambridge CB10 1SD, UK.
2 Okinawa Institute of Science & Technology, 1919-1 Tancha, Onna-son, Kunigami- gun, Okinawa 904-0495, Japan.
3 University College London Genetics Institute, Gower Street, London WC1E 6BT, UK

Corresponding author: Nicholas M. Luscombe
Email feedback to: This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Ruhi Ali, Florence M.G. Cavalli, Juan M. Vaquerizas, Nicholas M. Luscombe
 

A Guideline for ChIP - Chip Data Quality Control and Normalization (Prot 47)

Matthias Siebert, Michael Lidschreiber, Holger Hartmann, and Johannes Söding

Introduction

Chromatin immunoprecipitation coupled to tiling microarray analysis (ChIP-on-chip) is used to measure genome-wide the DNA binding sites of a protein of interest. In ChIP-on-chip, proteins are covalently cross-linked to the DNA by formaldehyde, cells are lysed, the chromatin is immunoprecipitated with an antibody to the protein of interest and the fragmented DNA that is directly or indirectly bound to the protein is analyzed with tiling arrays. For this purpose, the fragmented DNA is fluorescently labeled and hybridized to the tiling array, which consists of millions of short (25 to 60 nucleotides long) probes that cover the genome at a constant spacing (4 to 100s of nucleotides), like tiles covering a roof. The data generated by one experiment consists of an intensity value for each DNA probe. These values measure the relative quantity of DNA at the probe's genomic position in the immunoprecipitated material. [...]

PDF version

Matthias Siebert, Michael Lidschreiber, Holger Hartmann, and Johannes Söding

Gene Center Munich - Ludwig-Maximilians-Universität - Feodor-Lynen-Str. 25 - 81377 Munich, Germany

Matthias Siebert, Michael Lidschreiber, Holger Hartmann, and Johannes Söding
 

Basic Analysis of NimbleGen ChIP-on-chip Data using Bioconductor/R (Prot 43)

Tobias Straub

Introduction

Hybridization of chromatin immuno-precipitation (ChIP) material to tiling arrays at NimbleGen service facilities usually leaves the customer with a set of data files that are of limited use. Most information about the experiment is gained by either displaying immuno-precipitate(IP)/input ratio tracks (the GFF files provided) of individual hybridisation experiments with NimbleGen’s SignalMap software or by scanning the list of peaks identified by the automated data analysis. Summary profiles from replicate experiments cannot be investigated; further calculations are left to the customers. Apart from the fact that data quality cannot be directly evaluated, raw data is not corrected for systematic signal distortions in the generation of ratio GFF files. Furthermore, the robustness of the provided peak finding procedures is questionable, as the algorithm will frequently identify many "significant" peaks in noise-only experiments [...]

PDF version

Tobias Straub

Adolf Butenandt Institute - Molecular Biology - Ludwig-Maximilians University, Germany

Tobias Straub