High Throughput Sequence (HTS) data analysis. Lei Zhou
|
|
|
- Erika Davis
- 5 years ago
- Views:
Transcription
1 High Throughput Sequence (HTS) data analysis Lei Zhou High Throughput Sequence (HTS) data analysis 1. Representation of HTS data. 2. Visualization of HTS data. 3. Discovering genomic pattern from HTS data. 4. Integrated data analysis and hypothesis formulation. 1
2 Recoding sequence information sequence file format FASTA format suitable for single gene or genomic region, pre-genomic era. > Gene_name or accession, (other info) ACTGGGTTTATGACGTGTCATGCATGCA ATGTAGCTAGATGCTAGCTAGATGCTAG CTAGATGCTA. Defined format is necessary for computers to identify and process the information. Example of FASTA format file from NCBI 2
3 Representation of (HTS) data BED (Browser Extensible Data) file Chrom. Start End name Scor Strand chr U0 0 + chr U1 0 - chr U2 0 + chr U1 0 - chr U2 0 + With the completion of the genome, there is no need to record the base pair identity (if it is the same as the reference genome). Detailed description of genomic data formats: Representation of HTS data The importance of a reference genome All coordinates are only meaningful for a given genome assembly. One assembly may have multiple releases (annotations). You need to know which reference genome was used to generate the BED file. 3
4 How to gain knowledge from HTS data Visualization of HTS data. Discovering genomic patterns. Identifying novel mechanism hypothesis generation. Visualization of HTS data. Simple visualization - distribution of tags (or normalized values). Barski et al. (2007) Cell Chr. ChrStart ChrEnd Value (2007) Cell chr chr chr chr chr BedGraph file (Wig) 4
5 Visualization of HTS data. Shifting sequence tag position may be necessary to reflect nucleosome positions. In this example the mapping positions were shifted +73bp for forward strain and -73bp for reverse strain to reflect the midpoint of the nucleosome. Jiang & Pugh, Nat. Rev. Genet., 2009 Visualization of HTS data. Advanced visualization depending on purpose of comparison. Example - Circos plot depicts genomic location, chromosomal copy number (red, copy gain; blue, copy loss). Interchromosomal translocations (purple) and intra-chromosomal (green) rearrangements observed in primary prostate cancers Berger et al. (2011) Nature 5
6 Discovering genomic patterns Barski et al. (2007) Cell Usually requires some programming (scripting). As a biologist, you need to clearly define your question, and the logic to obtain the data summary. Discovering genomic patterns Q: Is H3K4me3 associated with TSS? Is such an association related to gene expression status? Logic: 1. Group genes based on expression levels obtained with a microarray study (Su et al, 2004). 2. For each gene, obtain the normalized H3K4me3 ChIP-Seq counts within [-2k, +2k] of the TSS. 3. For each of the expression group, plot the average value along the [-2k, +2k] interval. 6
7 Integrated data analysis and hypothesis formulation An example: Chromatin barrier Gaszner & Felsenfeld, Nat. Rev. Genet., 2006 Chromatin barriers demarcate the boundaries between heterochromatin and euchromatin regions. It is usually bound by insulator proteins such as CTCF, Su(Hw) etc. An example of genomic analysis and hypothesis generation The problem: binding of insulator proteins does not always correlate with chromatin boundary. H3K27me3 ChIP-Seq Insulator protein ChIP- Seq binding sites from those that are in heterochromatic (H3K27me3-enriched) region? 7
8 An example of genomic analysis and hypothesis generation binding sites from those that are in H3K27me3-enriched region? 1. Genome-wide Identification of H3K27me3 boundaries using ChIP-Seq data. Verifying the predications using RNA-Seq data for the same cell type. An example of genomic analysis and hypothesis generation binding sites from those that are in heterochromatic region? 1. Genome-wide Identification of H3K27me3 boundaries using ChIP-Seq data. 2. Compare the binding levels of CTCF and co- factors. Figures reflect the average binding intensity for hundreds of sites at the boundary (solid line) or within heterochromatic regions (dotted line). 8
9 An example of genomic analysis and hypothesis generation binding sites from those that are in H3K27me3-enriched region? 1. Genome-wide Identification of H3K27me3 boundaries using ChIP-Seq data. 2. Compare the binding levels of CTCF and co-factors. 3. Is the difference significant? U (rank sum) test. P>0.01 P<0.001 An example of genomic analysis and hypothesis generation binding sites from those that are in H3K27me3-enriched region? 1. Genome-wide Identification of H3K27me3 boundaries using ChIP-Seq data. 2. Compare the binding levels of CTCF and co-factors. 3. Is the difference significant? 4. What might be the cause of this difference? comparing underlying DNA sequences. The 400 bp regions surrounding the CTCF binding sites at the boundary were compared against those in H3K27me3- enriched region to identify discriminative motifs. ( ro.html) 9
10 An example of genomic analysis and hypothesis generation binding sites from those that are in H3K27me3-enriched region? Compared to CTCF binding site in H3K27me3-enriched region, CTCF binding sites at the boundary are associated with multi-da motif, have less nucleosome density, and have higher level of co-factor binding. Hypothesis: the presence of multi-da motif facilitates the binding of co-factor by destabilizing nucleosome formation. Useful resources for HTS analysis Galaxy tools ( psu ) UCSC Genome Browser ( ) Sequence motif identification (MEME: ) 10
Computational Analysis of UHT Sequences Histone modifications, CAGE, RNA-Seq
Computational Analysis of UHT Sequences Histone modifications, CAGE, RNA-Seq Philipp Bucher Wednesday January 21, 2009 SIB graduate school course EPFL, Lausanne ChIP-seq against histone variants: Biological
Nature Structural & Molecular Biology: doi: /nsmb.2419
Supplementary Figure 1 Mapped sequence reads and nucleosome occupancies. (a) Distribution of sequencing reads on the mouse reference genome for chromosome 14 as an example. The number of reads in a 1 Mb
Genome-wide Association Studies (GWAS) Pasieka, Science Photo Library
Lecture 5 Genome-wide Association Studies (GWAS) Pasieka, Science Photo Library Chi-squared test to evaluate whether the odds ratio is different from 1. Corrected for multiple testing Source: wikipedia.org
Supplemental Figure S1. Tertiles of FKBP5 promoter methylation and internal regulatory region
Supplemental Figure S1. Tertiles of FKBP5 promoter methylation and internal regulatory region methylation in relation to PSS and fetal coupling. A, PSS values for participants whose placentas showed low,
Accessing and Using ENCODE Data Dr. Peggy J. Farnham
1 William M Keck Professor of Biochemistry Keck School of Medicine University of Southern California How many human genes are encoded in our 3x10 9 bp? C. elegans (worm) 959 cells and 1x10 8 bp 20,000
Comparison of open chromatin regions between dentate granule cells and other tissues and neural cell types.
Supplementary Figure 1 Comparison of open chromatin regions between dentate granule cells and other tissues and neural cell types. (a) Pearson correlation heatmap among open chromatin profiles of different
The Epigenome Tools 2: ChIP-Seq and Data Analysis
The Epigenome Tools 2: ChIP-Seq and Data Analysis Chongzhi Zang zang@virginia.edu http://zanglab.com PHS5705: Public Health Genomics March 20, 2017 1 Outline Epigenome: basics review ChIP-seq overview
The Insulator Binding Protein CTCF Positions 20 Nucleosomes around Its Binding Sites across the Human Genome
The Insulator Binding Protein CTCF Positions 20 Nucleosomes around Its Binding Sites across the Human Genome Yutao Fu 1, Manisha Sinha 2,3, Craig L. Peterson 3, Zhiping Weng 1,4,5 * 1 Bioinformatics Program,
Peak-calling for ChIP-seq and ATAC-seq
Peak-calling for ChIP-seq and ATAC-seq Shamith Samarajiwa CRUK Autumn School in Bioinformatics 2017 University of Cambridge Overview Peak-calling: identify enriched (signal) regions in ChIP-seq or ATAC-seq
MIR retrotransposon sequences provide insulators to the human genome
Supplementary Information: MIR retrotransposon sequences provide insulators to the human genome Jianrong Wang, Cristina Vicente-García, Davide Seruggia, Eduardo Moltó, Ana Fernandez- Miñán, Ana Neto, Elbert
a) List of KMTs targeted in the shrna screen. The official symbol, KMT designation,
Supplementary Information Supplementary Figures Supplementary Figure 1. a) List of KMTs targeted in the shrna screen. The official symbol, KMT designation, gene ID and specifities are provided. Those highlighted
Chip Seq Peak Calling in Galaxy
Chip Seq Peak Calling in Galaxy Chris Seward PowerPoint by Pei-Chen Peng Chip-Seq Peak Calling in Galaxy Chris Seward 2018 1 Introduction This goals of the lab are as follows: 1. Gain experience using
ChromHMM Tutorial. Jason Ernst Assistant Professor University of California, Los Angeles
ChromHMM Tutorial Jason Ernst Assistant Professor University of California, Los Angeles Talk Outline Chromatin states analysis and ChromHMM Accessing chromatin state annotations for ENCODE2 and Roadmap
ChIP-seq data analysis
ChIP-seq data analysis Harri Lähdesmäki Department of Computer Science Aalto University November 24, 2017 Contents Background ChIP-seq protocol ChIP-seq data analysis Transcriptional regulation Transcriptional
Supplementary Figure S1. Gene expression analysis of epidermal marker genes and TP63.
Supplementary Figure Legends Supplementary Figure S1. Gene expression analysis of epidermal marker genes and TP63. A. Screenshot of the UCSC genome browser from normalized RNAPII and RNA-seq ChIP-seq data
Assignment 5: Integrative epigenomics analysis
Assignment 5: Integrative epigenomics analysis Due date: Friday, 2/24 10am. Note: no late assignments will be accepted. Introduction CpG islands (CGIs) are important regulatory regions in the genome. What
Session 6: Integration of epigenetic data. Peter J Park Department of Biomedical Informatics Harvard Medical School July 18-19, 2016
Session 6: Integration of epigenetic data Peter J Park Department of Biomedical Informatics Harvard Medical School July 18-19, 2016 Utilizing complimentary datasets Frequent mutations in chromatin regulators
RASA: Robust Alternative Splicing Analysis for Human Transcriptome Arrays
Supplementary Materials RASA: Robust Alternative Splicing Analysis for Human Transcriptome Arrays Junhee Seok 1*, Weihong Xu 2, Ronald W. Davis 2, Wenzhong Xiao 2,3* 1 School of Electrical Engineering,
EPIGENOMICS PROFILING SERVICES
EPIGENOMICS PROFILING SERVICES Chromatin analysis DNA methylation analysis RNA-seq analysis Diagenode helps you uncover the mysteries of epigenetics PAGE 3 Integrative epigenomics analysis DNA methylation
Package NarrowPeaks. August 3, Version Date Type Package
Package NarrowPeaks August 3, 2013 Version 1.5.0 Date 2013-02-13 Type Package Title Analysis of Variation in ChIP-seq using Functional PCA Statistics Author Pedro Madrigal , with contributions
7SK ChIRP-seq is specifically RNA dependent and conserved between mice and humans.
Supplementary Figure 1 7SK ChIRP-seq is specifically RNA dependent and conserved between mice and humans. Regions targeted by the Even and Odd ChIRP probes mapped to a secondary structure model 56 of the
DNA-seq Bioinformatics Analysis: Copy Number Variation
DNA-seq Bioinformatics Analysis: Copy Number Variation Elodie Girard elodie.girard@curie.fr U900 institut Curie, INSERM, Mines ParisTech, PSL Research University Paris, France NGS Applications 5C HiC DNA-seq
Introduction. Introduction
Introduction We are leveraging genome sequencing data from The Cancer Genome Atlas (TCGA) to more accurately define mutated and stable genes and dysregulated metabolic pathways in solid tumors. These efforts
CTCF-Mediated Functional Chromatin Interactome in Pluripotent Cells
SUPPLEMENTARY INFORMATION CTCF-Mediated Functional Chromatin Interactome in Pluripotent Cells Lusy Handoko 1,*, Han Xu 1,*, Guoliang Li 1,*, Chew Yee Ngan 1, Elaine Chew 1, Marie Schnapp 1, Charlie Wah
Part-II: Statistical analysis of ChIP-seq data
Part-II: Statistical analysis of ChIP-seq data Outline ChIP-seq data, features, detailed modeling aspects (today). Other ChIP-seq related problems - overview (next lecture). IDR (next lecture) Stat 877
Heintzman, ND, Stuart, RK, Hon, G, Fu, Y, Ching, CW, Hawkins, RD, Barrera, LO, Van Calcar, S, Qu, C, Ching, KA, Wang, W, Weng, Z, Green, RD,
Heintzman, ND, Stuart, RK, Hon, G, Fu, Y, Ching, CW, Hawkins, RD, Barrera, LO, Van Calcar, S, Qu, C, Ching, KA, Wang, W, Weng, Z, Green, RD, Crawford, GE, Ren, B (2007) Distinct and predictive chromatin
An epigenetic approach to understanding (and predicting?) environmental effects on gene expression
www.collaslab.com An epigenetic approach to understanding (and predicting?) environmental effects on gene expression Philippe Collas University of Oslo Institute of Basic Medical Sciences Stem Cell Epigenetics
STAT1 regulates microrna transcription in interferon γ stimulated HeLa cells
CAMDA 2009 October 5, 2009 STAT1 regulates microrna transcription in interferon γ stimulated HeLa cells Guohua Wang 1, Yadong Wang 1, Denan Zhang 1, Mingxiang Teng 1,2, Lang Li 2, and Yunlong Liu 2 Harbin
Data mining with Ensembl Biomart. Stéphanie Le Gras
Data mining with Ensembl Biomart Stéphanie Le Gras (slegras@igbmc.fr) Guidelines Genome data Genome browsers Getting access to genomic data: Ensembl/BioMart 2 Genome Sequencing Example: Human genome 2000:
EXPression ANalyzer and DisplayER
EXPression ANalyzer and DisplayER Tom Hait Aviv Steiner Igor Ulitsky Chaim Linhart Amos Tanay Seagull Shavit Rani Elkon Adi Maron-Katz Dorit Sagir Eyal David Roded Sharan Israel Steinfeld Yossi Shiloh
Nature Genetics: doi: /ng Supplementary Figure 1. Immunofluorescence (IF) confirms absence of H3K9me in met-2 set-25 worms.
Supplementary Figure 1 Immunofluorescence (IF) confirms absence of H3K9me in met-2 set-25 worms. IF images of wild-type (wt) and met-2 set-25 worms showing the loss of H3K9me2/me3 at the indicated developmental
A Practical Guide to Integrative Genomics by RNA-seq and ChIP-seq Analysis
A Practical Guide to Integrative Genomics by RNA-seq and ChIP-seq Analysis Jian Xu, Ph.D. Children s Research Institute, UTSW Introduction Outline Overview of genomic and next-gen sequencing technologies
Supplementary Figure 1 IL-27 IL
Tim-3 Supplementary Figure 1 Tc0 49.5 0.6 Tc1 63.5 0.84 Un 49.8 0.16 35.5 0.16 10 4 61.2 5.53 10 3 64.5 5.66 10 2 10 1 10 0 31 2.22 10 0 10 1 10 2 10 3 10 4 IL-10 28.2 1.69 IL-27 Supplementary Figure 1.
Nature Structural & Molecular Biology: doi: /nsmb Supplementary Figure 1
Supplementary Figure 1 Effect of HSP90 inhibition on expression of endogenous retroviruses. (a) Inducible shrna-mediated Hsp90 silencing in mouse ESCs. Immunoblots of total cell extract expressing the
ChIP-seq hands-on. Iros Barozzi, Campus IFOM-IEO (Milan) Saverio Minucci, Gioacchino Natoli Labs
ChIP-seq hands-on Iros Barozzi, Campus IFOM-IEO (Milan) Saverio Minucci, Gioacchino Natoli Labs Main goals Becoming familiar with essential tools and formats Visualizing and contextualizing raw data Understand
ChIP-seq analysis. J. van Helden, M. Defrance, C. Herrmann, D. Puthier, N. Servant, M. Thomas-Chollier, O.Sand
ChIP-seq analysis J. van Helden, M. Defrance, C. Herrmann, D. Puthier, N. Servant, M. Thomas-Chollier, O.Sand Tuesday : quick introduction to ChIP-seq and peak-calling (Presentation + Practical session)
Computational aspects of ChIP-seq. John Marioni Research Group Leader European Bioinformatics Institute European Molecular Biology Laboratory
Computational aspects of ChIP-seq John Marioni Research Group Leader European Bioinformatics Institute European Molecular Biology Laboratory ChIP-seq Using highthroughput sequencing to investigate DNA
MODULE 4: SPLICING. Removal of introns from messenger RNA by splicing
Last update: 05/10/2017 MODULE 4: SPLICING Lesson Plan: Title MEG LAAKSO Removal of introns from messenger RNA by splicing Objectives Identify splice donor and acceptor sites that are best supported by
Nature Immunology: doi: /ni Supplementary Figure 1. DNA-methylation machinery is essential for silencing of Cd4 in cytotoxic T cells.
Supplementary Figure 1 DNA-methylation machinery is essential for silencing of Cd4 in cytotoxic T cells. (a) Scheme for the retroviral shrna screen. (b) Histogram showing CD4 expression (MFI) in WT cytotoxic
Discovery of Novel Human Gene Regulatory Modules from Gene Co-expression and
Discovery of Novel Human Gene Regulatory Modules from Gene Co-expression and Promoter Motif Analysis Shisong Ma 1,2*, Michael Snyder 3, and Savithramma P Dinesh-Kumar 2* 1 School of Life Sciences, University
Supplementary Figure 1. Efficiency of Mll4 deletion and its effect on T cell populations in the periphery. Nature Immunology: doi: /ni.
Supplementary Figure 1 Efficiency of Mll4 deletion and its effect on T cell populations in the periphery. Expression of Mll4 floxed alleles (16-19) in naive CD4 + T cells isolated from lymph nodes and
Comprehensive nucleosome mapping of the human genome in cancer progression
/, Vol. 7, No. 12 Comprehensive nucleosome mapping of the human genome in cancer progression Brooke R. Druliner 1,5, Daniel Vera 1,6, Ruth Johnson 2, Xiaoyang Ruan 3, Lynn M. Apone 4, Eileen T. Dimalanta
Functional annotation of farm animal genomes: ChIP-seq.
Functional annotation of farm animal genomes: ChIP-seq Richard Crooijmans 2018, PAGXXVI Richard.Crooijmans@wur.nl Why FAANG is important Understanding the genotype to phenotype link This needs: - genomic
Analysis of Massively Parallel Sequencing Data Application of Illumina Sequencing to the Genetics of Human Cancers
Analysis of Massively Parallel Sequencing Data Application of Illumina Sequencing to the Genetics of Human Cancers Gordon Blackshields Senior Bioinformatician Source BioScience 1 To Cancer Genetics Studies
MODULE 3: TRANSCRIPTION PART II
MODULE 3: TRANSCRIPTION PART II Lesson Plan: Title S. CATHERINE SILVER KEY, CHIYEDZA SMALL Transcription Part II: What happens to the initial (premrna) transcript made by RNA pol II? Objectives Explain
Supplementary note: Comparison of deletion variants identified in this study and four earlier studies
Supplementary note: Comparison of deletion variants identified in this study and four earlier studies Here we compare the results of this study to potentially overlapping results from four earlier studies
RNA-seq Introduction
RNA-seq Introduction DNA is the same in all cells but which RNAs that is present is different in all cells There is a wide variety of different functional RNAs Which RNAs (and sometimes then translated
SUPPLEMENTARY INFORMATION
doi: 1.138/nature8645 Physical coverage (x haploid genomes) 11 6.4 4.9 6.9 6.7 4.4 5.9 9.1 7.6 125 Neither end mapped One end mapped Chimaeras Correct Reads (million ns) 1 75 5 25 HCC1187 HCC1395 HCC1599
Hands-On Ten The BRCA1 Gene and Protein
Hands-On Ten The BRCA1 Gene and Protein Objective: To review transcription, translation, reading frames, mutations, and reading files from GenBank, and to review some of the bioinformatics tools, such
Genomic structural variation
Genomic structural variation Mario Cáceres The new genomic variation DNA sequence differs across individuals much more than researchers had suspected through structural changes A huge amount of structural
Breast cancer. Risk factors you cannot change include: Treatment Plan Selection. Inferring Transcriptional Module from Breast Cancer Profile Data
Breast cancer Inferring Transcriptional Module from Breast Cancer Profile Data Breast Cancer and Targeted Therapy Microarray Profile Data Inferring Transcriptional Module Methods CSC 177 Data Warehousing
Large conserved domains of low DNA methylation maintained by Dnmt3a
Supplementary information Large conserved domains of low DNA methylation maintained by Dnmt3a Mira Jeong# 1, Deqiang Sun # 2, Min Luo# 1, Yun Huang 3, Grant A. Challen %1, Benjamin Rodriguez 2, Xiaotian
Raymond Auerbach PhD Candidate, Yale University Gerstein and Snyder Labs August 30, 2012
Elucidating Transcriptional Regulation at Multiple Scales Using High-Throughput Sequencing, Data Integration, and Computational Methods Raymond Auerbach PhD Candidate, Yale University Gerstein and Snyder
Supplemental Information For: The genetics of splicing in neuroblastoma
Supplemental Information For: The genetics of splicing in neuroblastoma Justin Chen, Christopher S. Hackett, Shile Zhang, Young K. Song, Robert J.A. Bell, Annette M. Molinaro, David A. Quigley, Allan Balmain,
Broad H3K4me3 is associated with increased transcription elongation and enhancer activity at tumor suppressor genes
Broad H3K4me3 is associated with increased transcription elongation and enhancer activity at tumor suppressor genes Kaifu Chen 1,2,3,4,5,10, Zhong Chen 6,10, Dayong Wu 6, Lili Zhang 7, Xueqiu Lin 1,2,8,
Supplemental Figure 1. Genes showing ectopic H3K9 dimethylation in this study are DNA hypermethylated in Lister et al. study.
mc mc mc mc SUP mc mc Supplemental Figure. Genes showing ectopic HK9 dimethylation in this study are DNA hypermethylated in Lister et al. study. Representative views of genes that gain HK9m marks in their
Epigenetic interplay between mouse endogenous retroviruses and host genes
RESEARCH Open Access Epigenetic interplay between mouse endogenous retroviruses and host genes Rita Rebollo 1,2, Katharine Miceli-Royer 1,2, Ying Zhang 1,2, Sharareh Farivar 1,2, Liane Gagnier 1,2 and
Patterns of Histone Methylation and Chromatin Organization in Grapevine Leaf. Rachel Schwope EPIGEN May 24-27, 2016
Patterns of Histone Methylation and Chromatin Organization in Grapevine Leaf Rachel Schwope EPIGEN May 24-27, 2016 What does H3K4 methylation do? Plant of interest: Vitis vinifera Culturally important
Yingying Wei George Wu Hongkai Ji
Stat Biosci (2013) 5:156 178 DOI 10.1007/s12561-012-9066-5 Global Mapping of Transcription Factor Binding Sites by Sequencing Chromatin Surrogates: a Perspective on Experimental Design, Data Analysis,
Processing, integrating and analysing chromatin immunoprecipitation followed by sequencing (ChIP-seq) data
Processing, integrating and analysing chromatin immunoprecipitation followed by sequencing (ChIP-seq) data Bioinformatics methods, models and applications to disease Alex Essebier ChIP-seq experiment To
Figure S2. Distribution of acgh probes on all ten chromosomes of the RIL M0022
96 APPENDIX B. Supporting Information for chapter 4 "changes in genome content generated via segregation of non-allelic homologs" Figure S1. Potential de novo CNV probes and sizes of apparently de novo
Nature Immunology: doi: /ni Supplementary Figure 1 33,312. Aire rep 1. Aire rep 2 # 44,325 # 44,055. Aire rep 1. Aire rep 2.
a 33,312 b rep 1 rep 1 # 44,325 rep 2 # 44,055 [0-84] rep 2 [0-84] 1810043G02Rik Pfkl Dnmt3l Icosl rep 1 [0-165] rep 2 [0-165] Rps14 Cd74 Mir5107 Tcof1 rep 1 [0-69] rep 2 [0-68] Id3 E2f2 Asap3 rep 1 [0-141]
Table S1. Total and mapped reads produced for each ChIP-seq sample
Tale S1. Total and mapped reads produced for each ChIP-seq sample Sample Total Reads Mapped Reads Col- H3K27me3 rep1 125662 1334323 (85.76%) Col- H3K27me3 rep2 9176437 7986731 (87.4%) atmi1a//c H3K27m3
Nature Immunology: doi: /ni Supplementary Figure 1. Transcriptional program of the TE and MP CD8 + T cell subsets.
Supplementary Figure 1 Transcriptional program of the TE and MP CD8 + T cell subsets. (a) Comparison of gene expression of TE and MP CD8 + T cell subsets by microarray. Genes that are 1.5-fold upregulated
Nature Genetics: doi: /ng Supplementary Figure 1. Assessment of sample purity and quality.
Supplementary Figure 1 Assessment of sample purity and quality. (a) Hematoxylin and eosin staining of formaldehyde-fixed, paraffin-embedded sections from a human testis biopsy collected concurrently with
Supplementary Figures
Supplementary Figures Supplementary Figure 1. Pan-cancer analysis of global and local DNA methylation variation a) Variations in global DNA methylation are shown as measured by averaging the genome-wide
the reaction was stopped by adding glycine to final concentration 0.2M for 10 minutes at
Supplemental Material Material and Methods. ChIP. Cells were crosslinked with formaldehyde 0.4% for 10 min at room temperature and the reaction was stopped by adding glycine to final concentration 0.2M
Plasticity in patterns of histone modifications and chromosomal proteins in Drosophila heterochromatin
Research Plasticity in patterns of histone modifications and chromosomal proteins in Drosophila heterochromatin Nicole C. Riddle, 1,9 Aki Minoda, 2,9 Peter V. Kharchenko, 3,9 Artyom A. Alekseyenko, 4 Yuri
Metadata of the chapter that will be visualized online
Metadata of the chapter that will be visualized online ChapterTitle Chapter Sub-Title Advanced Analysis of Human Plasma Circulating DNA Sequences Produced by Parallel Tagged Sequencing on the 454 Platform
Nature Immunology: doi: /ni Supplementary Figure 1. Characteristics of SEs in T reg and T conv cells.
Supplementary Figure 1 Characteristics of SEs in T reg and T conv cells. (a) Patterns of indicated transcription factor-binding at SEs and surrounding regions in T reg and T conv cells. Average normalized
Open Access RESEARCH. Background Malaria is a major public health problem in many developing countries, with the parasite Plasmodium
Karmodiya et al. Epigenetics & Chromatin (215) 8:32 DOI 1.1186/s1372-15-29-1 RESEARCH Open Access A comprehensive epigenome map of Plasmodium falciparum reveals unique mechanisms of transcriptional regulation
RNA SEQUENCING AND DATA ANALYSIS
RNA SEQUENCING AND DATA ANALYSIS Length of mrna transcripts in the human genome 5,000 5,000 4,000 3,000 2,000 4,000 1,000 0 0 200 400 600 800 3,000 2,000 1,000 0 0 2,000 4,000 6,000 8,000 10,000 Length
Global Epigenetic and Transcriptional Trends among Two Rice Subspecies and Their Reciprocal Hybrids W
The Plant Cell, Vol. 22: 17 33, January 2010, www.plantcell.org ã 2010 American Society of Plant Biologists RESEARCH ARTICLES Global Epigenetic and Transcriptional Trends among Two Rice Subspecies and
Supplementary Information. Supplementary Figures
Supplementary Information Supplementary Figures.8 57 essential gene density 2 1.5 LTR insert frequency diversity DEL.5 DUP.5 INV.5 TRA 1 2 3 4 5 1 2 3 4 1 2 Supplementary Figure 1. Locations and minor
Supplementary Information
Supplementary Information for Ho et al., modencode and ENCODE resources for analysis of metazoan chromatin organization Supplementary Content Supplementary Methods ---------------------------------------------------------
Exploring chromatin regulation by ChIP-Sequencing
Exploring chromatin regulation by ChIP-Sequencing From datasets quality assessment, enrichment patterns identification and multi-profiles integration to the reconstitution of gene regulatory wires describing
ESCs were lysed with Trizol reagent (Life technologies) and RNA was extracted according to
Supplemental Methods RNA-seq ESCs were lysed with Trizol reagent (Life technologies) and RNA was extracted according to the manufacturer's instructions. RNAse free DNaseI (Sigma) was used to eliminate
Nature Biotechnology: doi: /nbt.1904
Supplementary Information Comparison between assembly-based SV calls and array CGH results Genome-wide array assessment of copy number changes, such as array comparative genomic hybridization (acgh), is
Generating Spontaneous Copy Number Variants (CNVs) Jennifer Freeman Assistant Professor of Toxicology School of Health Sciences Purdue University
Role of Chemical lexposure in Generating Spontaneous Copy Number Variants (CNVs) Jennifer Freeman Assistant Professor of Toxicology School of Health Sciences Purdue University CNV Discovery Reference Genetic
Analysis of the peroxisome proliferator-activated receptor-β/δ (PPARβ/δ) cistrome reveals novel co-regulatory role of ATF4
Khozoie et al. BMC Genomics 2012, 13:665 RESEARCH ARTICLE Open Access Analysis of the peroxisome proliferator-activated receptor-β/δ (PPARβ/δ) cistrome reveals novel co-regulatory role of ATF4 Combiz Khozoie
PDF hosted at the Radboud Repository of the Radboud University Nijmegen
PDF hosted at the Radboud Repository of the Radboud University Nijmegen The following full text is a publisher's version. For additional information about this publication click this link. http://hdl.handle.net/2066/156973
Histone Modifications Are Associated with Transcript Isoform Diversity in Normal and Cancer Cells
Histone Modifications Are Associated with Transcript Isoform Diversity in Normal and Cancer Cells Ondrej Podlaha 1, Subhajyoti De 2,3,4, Mithat Gonen 5, Franziska Michor 1 * 1 Department of Biostatistics
Statistical analysis of ChIP-seq data
Statistical analysis of ChIP-seq data Sündüz Keleş Department of Statistics Department of Biostatistics and Medical Informatics University of Wisconsin, Madison Feb 9, 2012 BMI 776 (Spring 12) 02/09/2012
Introduction to Systems Biology of Cancer Lecture 2
Introduction to Systems Biology of Cancer Lecture 2 Gustavo Stolovitzky IBM Research Icahn School of Medicine at Mt Sinai DREAM Challenges High throughput measurements: The age of omics Systems Biology
Tutorial. ChIP Sequencing. Sample to Insight. September 15, 2016
ChIP Sequencing September 15, 2016 Sample to Insight CLC bio, a QIAGEN Company Silkeborgvej 2 Prismet 8000 Aarhus C Denmark Telephone: +45 70 22 32 44 www.clcbio.com support-clcbio@qiagen.com ChIP Sequencing
A Quick-Start Guide for rseqdiff
A Quick-Start Guide for rseqdiff Yang Shi (email: shyboy@umich.edu) and Hui Jiang (email: jianghui@umich.edu) 09/05/2013 Introduction rseqdiff is an R package that can detect differential gene and isoform
Not IN Our Genes - A Different Kind of Inheritance.! Christopher Phiel, Ph.D. University of Colorado Denver Mini-STEM School February 4, 2014
Not IN Our Genes - A Different Kind of Inheritance! Christopher Phiel, Ph.D. University of Colorado Denver Mini-STEM School February 4, 2014 Epigenetics in Mainstream Media Epigenetics *Current definition:
ONLINE. Online supplementary information S1 (Box) Method. Supplementary data. Online links
ONLINE Online supplementary information S1 (Box) Method The of the human or mouse genomes were downloaded from the UCSC Genome Browser using the Tables feature. The d component of each genome was comprehensively
Supplementary Figure S1: Defective heterochromatin repair in HGPS progeroid cells
Supplementary Figure S1: Defective heterochromatin repair in HGPS progeroid cells Immunofluorescence staining of H3K9me3 and 53BP1 in PH and HGADFN003 (HG003) cells at 24 h after γ-irradiation. Scale bar,
Eukaryotic Gene Regulation
Eukaryotic Gene Regulation Chapter 19: Control of Eukaryotic Genome The BIG Questions How are genes turned on & off in eukaryotes? How do cells with the same genes differentiate to perform completely different,
Case Studies on High Throughput Gene Expression Data Kun Huang, PhD Raghu Machiraju, PhD
Case Studies on High Throughput Gene Expression Data Kun Huang, PhD Raghu Machiraju, PhD Department of Biomedical Informatics Department of Computer Science and Engineering The Ohio State University Review
Mechanisms of alternative splicing regulation
Mechanisms of alternative splicing regulation The number of mechanisms that are known to be involved in splicing regulation approximates the number of splicing decisions that have been analyzed in detail.
38 Int'l Conf. Bioinformatics and Computational Biology BIOCOMP'16
38 Int'l Conf. Bioinformatics and Computational Biology BIOCOMP'16 PGAR: ASD Candidate Gene Prioritization System Using Expression Patterns Steven Cogill and Liangjiang Wang Department of Genetics and
V24 Regular vs. alternative splicing
Regular splicing V24 Regular vs. alternative splicing mechanistic steps recognition of splice sites Alternative splicing different mechanisms how frequent is alternative splicing? Effect of alternative
SUPPLEMENTAL FILE. mir-22 and mir-29a are members of the androgen receptor cistrome modulating. LAMC1 and Mcl-1 in prostate cancer
1 SUPPLEMENTAL FILE 2 3 mir-22 and mir-29a are members of the androgen receptor cistrome modulating LAMC1 and Mcl-1 in prostate cancer 4 5 6 Lorenza Pasqualini 1, Huajie Bu 1,2, Martin Puhr 1, Narisu Narisu
levels of genes were separated by their expression levels; 2,000 high, medium, and low
Figure S1. Histone modification profiles near transcription start sites. The overall histone modification around transcription start sites (TSSs) was calculated. Histone modification levels of genes were
Annotation of Chimp Chunk 2-10 Jerome M Molleston 5/4/2009
Annotation of Chimp Chunk 2-10 Jerome M Molleston 5/4/2009 1 Abstract A stretch of chimpanzee DNA was annotated using tools including BLAST, BLAT, and Genscan. Analysis of Genscan predicted genes revealed
Dominic J Smiraglia, PhD Department of Cancer Genetics. DNA methylation in prostate cancer
Dominic J Smiraglia, PhD Department of Cancer Genetics DNA methylation in prostate cancer Overarching theme Epigenetic regulation allows the genome to be responsive to the environment Sets the tone for
Supplementary Materials
1 Supplementary Materials Rotger et al. Table S1A: Demographic characteristics of study participants. VNP RP EC CP (n=6) (n=66) (n=9) (n=5) Male gender, n(%) 5 (83) 54 (82) 5 (56) 3 (60) White ethnicity,
Lung Met 1 Lung Met 2 Lung Met Lung Met H3K4me1. Lung Met H3K27ac Primary H3K4me1
a Gained Met-VELs 1.5 1.5 -.5 Lung Met 1 Lung Met Lung Met 3 1. Lung Met H3K4me1 Lung Met H3K4me1 1 Lung Met H3K4me1 Lung Met H3K7ac 1.5 Lung Met H3K7ac Lung Met H3K7ac.8 Primary H3K4me1 Primary H3K7ac