<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/37732?offset=0 https://bioinformaticsonline.com/bookmarks/view/27070/venn-diagrams-on-r-studio Mon, 25 Apr 2016 16:22:28 -0500 https://bioinformaticsonline.com/bookmarks/view/27070/venn-diagrams-on-r-studio <![CDATA[Venn Diagrams on R Studio]]> First step: Install & load “VennDiagram” package. 
# install.packages('VennDiagram')
library(VennDiagram)

Second step: Load data

Add filepath if “catdoge.csv” is not in working-directory.

d <- read.csv("catdoge.csv")

Address of the bookmark: http://rstudio-pubs-static.s3.amazonaws.com/13301_6641d73cfac741a59c0a851feb99e98b.html

]]> Jitendra Prajapati https://bioinformaticsonline.com/blog/view/36525/installing-bandage-on-ubunty Tue, 08 May 2018 08:03:21 -0500 https://bioinformaticsonline.com/blog/view/36525/installing-bandage-on-ubunty <![CDATA[Installing Bandage on Ubunty !]]> The following instructions successfully build Bandage (https://github.com/rrwick/Bandage ) on a fresh installation of Ubuntu 14.04:

  1. Ensure the package lists are up-to-date: sudo apt-get update
  2. Install prerequisite packages: sudo apt-get install build-essential git qtbase5-dev libqt5svg5-dev
  3. Download the Bandage code from GitHub: git clone https://github.com/rrwick/Bandage.git
  4. Open a terminal in the Bandage directory.
  5. Set the environment variable to specify that you will be using Qt 5, not Qt 4: export QT_SELECT=5
  6. Run qmake to generate a Makefile: qmake
  7. Build the program: make
  8. Bandage should now be an executable file.
  9. Optionally, copy the program into /usr/local/bin: sudo make install. The Bandage build directory can then be deleted.

➜ Tools git:(master) ✗ sudo apt-get update
[sudo] password for urbe: 
Hit:1 http://ppa.launchpad.net/webupd8team/atom/ubuntu xenial InRelease
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Get:7 https://cran.rstudio.com/bin/linux/ubuntu xenial/ InRelease [3.590 B] 
Hit:8 https://download.docker.com/linux/ubuntu xenial InRelease 
Ign:9 http://download.opensuse.org/repositories/home:/sionescu/Debian ./ InRelease 
Hit:10 http://download.opensuse.org/repositories/home:/sionescu/Debian ./ Release 
Get:11 http://packages.cloud.google.com/apt cloud-sdk-xenial InRelease [6.372 B]
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Err:11 http://packages.cloud.google.com/apt cloud-sdk-xenial InRelease 
The following signatures couldn't be verified because the public key is not available: NO_PUBKEY 6A030B21BA07F4FB
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Reading package lists... Done
W: An error occurred during the signature verification. The repository is not updated and the previous index files will be used. GPG error: http://packages.cloud.google.com/apt cloud-sdk-xenial InRelease: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY 6A030B21BA07F4FB
W: Failed to fetch http://packages.cloud.google.com/apt/dists/cloud-sdk-xenial/InRelease The following signatures couldn't be verified because the public key is not available: NO_PUBKEY 6A030B21BA07F4FB
W: Some index files failed to download. They have been ignored, or old ones used instead.
➜ Tools git:(master) ✗ sudo apt-get install build-essential git qtbase5-dev libqt5svg5-dev
Reading package lists... Done
Building dependency tree 
Reading state information... Done
build-essential is already the newest version (12.1ubuntu2).
git is already the newest version (1:2.7.4-0ubuntu1.3).
The following packages were automatically installed and are no longer required:
bridge-utils containerd linux-headers-4.4.0-116 linux-headers-4.4.0-116-generic linux-headers-4.4.0-21 linux-headers-4.4.0-21-generic linux-image-4.4.0-116-generic linux-image-4.4.0-21-generic
linux-image-extra-4.4.0-116-generic linux-image-extra-4.4.0-21-generic linux-signed-image-4.4.0-116-generic runc ubuntu-fan
Use 'sudo apt autoremove' to remove them.
The following additional packages will be installed:
libdrm-dev libegl1-mesa-dev libgl1-mesa-dev libgles2-mesa libgles2-mesa-dev libglu1-mesa-dev libmirclient-dev libmircommon-dev libmircookie-dev libmircookie2 libmircore-dev libprotobuf-dev libprotobuf9v5
libqt5concurrent5 libqt5core5a libqt5dbus5 libqt5gui5 libqt5network5 libqt5opengl5 libqt5opengl5-dev libqt5printsupport5 libqt5sql5 libqt5sql5-sqlite libqt5svg5 libqt5test5 libqt5widgets5 libqt5xml5 libwayland-bin
libwayland-dev libx11-xcb-dev libxcb-dri2-0-dev libxcb-dri3-dev libxcb-glx0-dev libxcb-icccm4 libxcb-image0 libxcb-keysyms1 libxcb-present-dev libxcb-randr0 libxcb-randr0-dev libxcb-render-util0 libxcb-render0-dev
libxcb-shape0-dev libxcb-sync-dev libxcb-xfixes0-dev libxcb-xkb1 libxdamage-dev libxext-dev libxfixes-dev libxkbcommon-dev libxkbcommon-x11-0 libxshmfence-dev libxxf86vm-dev mesa-common-dev qt5-qmake
qtbase5-dev-tools qttranslations5-l10n x11proto-damage-dev x11proto-dri2-dev x11proto-fixes-dev x11proto-gl-dev x11proto-xext-dev x11proto-xf86vidmode-dev
Suggested packages:
libqt5libqgtk2 qt5-image-formats-plugins qtwayland5 libxext-doc libmysqlclient-dev libpq-dev libsqlite3-dev unixodbc-dev
The following NEW packages will be installed:
libdrm-dev libegl1-mesa-dev libgl1-mesa-dev libgles2-mesa libgles2-mesa-dev libglu1-mesa-dev libmirclient-dev libmircommon-dev libmircookie-dev libmircookie2 libmircore-dev libprotobuf-dev libprotobuf9v5
libqt5concurrent5 libqt5core5a libqt5dbus5 libqt5gui5 libqt5network5 libqt5opengl5 libqt5opengl5-dev libqt5printsupport5 libqt5sql5 libqt5sql5-sqlite libqt5svg5 libqt5svg5-dev libqt5test5 libqt5widgets5 libqt5xml5
libwayland-bin libwayland-dev libx11-xcb-dev libxcb-dri2-0-dev libxcb-dri3-dev libxcb-glx0-dev libxcb-icccm4 libxcb-image0 libxcb-keysyms1 libxcb-present-dev libxcb-randr0 libxcb-randr0-dev libxcb-render-util0
libxcb-render0-dev libxcb-shape0-dev libxcb-sync-dev libxcb-xfixes0-dev libxcb-xkb1 libxdamage-dev libxext-dev libxfixes-dev libxkbcommon-dev libxkbcommon-x11-0 libxshmfence-dev libxxf86vm-dev mesa-common-dev
qt5-qmake qtbase5-dev qtbase5-dev-tools qttranslations5-l10n x11proto-damage-dev x11proto-dri2-dev x11proto-fixes-dev x11proto-gl-dev x11proto-xext-dev x11proto-xf86vidmode-dev
0 upgraded, 64 newly installed, 0 to remove and 11 not upgraded.
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➜ Tools git:(master) ✗ git clone https://github.com/rrwick/Bandage.git
Cloning into 'Bandage'...
remote: Counting objects: 7813, done.
remote: Total 7813 (delta 0), reused 0 (delta 0), pack-reused 7813
Receiving objects: 100% (7813/7813), 27.43 MiB | 16.33 MiB/s, done.
Resolving deltas: 100% (5973/5973), done.
Checking connectivity... done.
➜ Tools git:(master) ✗ cd Bandage 
➜ Bandage git:(master) ls
Bandage.pro BandageTests.pro blast build_scripts command_line COPYING graph images ogdf program README.md tests ui
➜ Bandage git:(master) export QT_SELECT=5
➜ Bandage git:(master) qmake
➜ Bandage git:(master) ✗ make
/home/urbe/anaconda3/bin/uic ui/mainwindow.ui -o ui_mainwindow.h
/home/urbe/anaconda3/bin/uic ui/settingsdialog.ui -o ui_settingsdialog.h
/home/urbe/anaconda3/bin/uic ui/aboutdialog.ui -o ui_aboutdialog.h
/home/urbe/anaconda3/bin/uic ui/enteroneblastquerydialog.ui -o ui_enteroneblastquerydialog.h
/home/urbe/anaconda3/bin/uic ui/blastsearchdialog.ui -o ui_blastsearchdialog.h
/home/urbe/anaconda3/bin/uic ui/myprogressdialog.ui -o ui_myprogressdialog.h
/home/urbe/anaconda3/bin/uic ui/pathspecifydialog.ui -o ui_pathspecifydialog.h
/home/urbe/anaconda3/bin/uic ui/querypathsdialog.ui -o ui_querypathsdialog.h
/home/urbe/anaconda3/bin/uic ui/blasthitfiltersdialog.ui -o ui_blasthitfiltersdialog.h
/home/urbe/anaconda3/bin/uic ui/changenodenamedialog.ui -o ui_changenodenamedialog.h
/home/urbe/anaconda3/bin/uic ui/graphinfodialog.ui -o ui_graphinfodialog.h
/home/urbe/anaconda3/bin/uic ui/changenodedepthdialog.ui -o ui_changenodedepthdialog.h
g++ -c -pipe -O2 -std=gnu++0x -Wall -W -D_REENTRANT -fPIC -DQT_NO_DEBUG -DQT_SVG_LIB -DQT_WIDGETS_LIB -DQT_GUI_LIB -DQT_CORE_LIB -I. -Iui -I/usr/include -I../../anaconda3/include/qt -I../../anaconda3/include/qt/QtSvg -I../../anaconda3/include/qt/QtWidgets -I../../anaconda3/include/qt/QtGui -I../../anaconda3/include/qt/QtCore -I. -I. -I../../anaconda3/mkspecs/linux-g++ -o main.o program/main.cpp
g++ -c -pipe -O2 -std=gnu++0x -Wall -W -D_REENTRANT -fPIC -DQT_NO_DEBUG -DQT_SVG_LIB -DQT_WIDGETS_LIB -DQT_GUI_LIB -DQT_CORE_LIB -I. -Iui -I/usr/include -I../../anaconda3/include/qt -I../../anaconda3/include/qt/QtSvg -I../../anaconda3/include/qt/QtWidgets -I../../anaconda3/include/qt/QtGui -I../../anaconda3/include/qt/QtCore -I. -I. -I../../anaconda3/mkspecs/linux-g++ -o settings.o program/settings.cpp
....

...
g++ -Wl,-O1 -Wl,-rpath,/home/urbe/anaconda3/lib -o Bandage main.o settings.o globals.o graphlayoutworker.o debruijnnode.o debruijnedge.o graphicsitemnode.o graphicsitemedge.o mainwindow.o graphicsviewzoom.o settingsdialog.o mygraphicsview.o mygraphicsscene.o aboutdialog.o enteroneblastquerydialog.o blasthit.o blastqueries.o blastsearchdialog.o infotextwidget.o assemblygraph.o verticalscrollarea.o myprogressdialog.o nodewidthvisualaid.o verticallabel.o load.o image.o commoncommandlinefunctions.o mytablewidget.o buildblastdatabaseworker.o colourbutton.o blastquery.o runblastsearchworker.o blastsearch.o path.o pathspecifydialog.o graphlocation.o tablewidgetitemint.o tablewidgetitemdouble.o tablewidgetitemshown.o memory.o querypathspushbutton.o querypathsdialog.o blastquerypath.o blasthitfiltersdialog.o scinot.o changenodenamedialog.o querypathsequencecopybutton.o querypaths.o info.o reduce.o Graph.o GraphAttributes.o FMMMLayout.o geometry.o ClusterGraphAttributes.o FruchtermanReingold.o NMM.o GmlParser.o simple_graph_alg.o basic.o XmlParser.o String.o Hashing.o PoolMemoryAllocator.o GraphCopy.o CombinatorialEmbedding.o OgmlParser.o ClusterGraph.o Math.o EdgeAttributes.o NodeAttributes.o MAARPacking.o Multilevel.o numexcept.o Set.o Ogml.o DinoXmlParser.o DinoXmlScanner.o DinoTools.o DinoLineBuffer.o System.o QuadTreeNM.o QuadTreeNodeNM.o Constraint.o MultilevelGraph.o graphinfodialog.o tablewidgetitemname.o changenodedepthdialog.o qrc_images.o moc_graphlayoutworker.o moc_mainwindow.o moc_graphicsviewzoom.o moc_settingsdialog.o moc_mygraphicsview.o moc_mygraphicsscene.o moc_aboutdialog.o moc_enteroneblastquerydialog.o moc_blastquery.o moc_blastsearchdialog.o moc_infotextwidget.o moc_assemblygraph.o moc_verticalscrollarea.o moc_myprogressdialog.o moc_nodewidthvisualaid.o moc_verticallabel.o moc_mytablewidget.o moc_buildblastdatabaseworker.o moc_colourbutton.o moc_runblastsearchworker.o moc_pathspecifydialog.o moc_querypathspushbutton.o moc_querypathsdialog.o moc_blasthitfiltersdialog.o moc_changenodenamedialog.o moc_querypathsequencecopybutton.o moc_graphinfodialog.o moc_changenodedepthdialog.o -L/usr/lib -L/home/urbe/anaconda3/lib -lQt5Svg -lQt5Widgets -lQt5Gui -lQt5Core -lGL -lpthread 
➜ Bandage git:(master) ✗ ls 
aboutdialog.o DinoTools.o Makefile moc_infotextwidget.cpp moc_verticalscrollarea.o scinot.o
assemblygraph.o DinoXmlParser.o Math.o moc_infotextwidget.o MultilevelGraph.o Set.o
Bandage DinoXmlScanner.o memory.o moc_mainwindow.cpp Multilevel.o settingsdialog.o
Bandage.pro EdgeAttributes.o moc_aboutdialog.cpp moc_mainwindow.o mygraphicsscene.o settings.o
BandageTests.pro enteroneblastquerydialog.o moc_aboutdialog.o moc_mygraphicsscene.cpp mygraphicsview.o simple_graph_alg.o
basic.o FMMMLayout.o moc_assemblygraph.cpp moc_mygraphicsscene.o myprogressdialog.o String.o
blast FruchtermanReingold.o moc_assemblygraph.o moc_mygraphicsview.cpp mytablewidget.o System.o
blasthitfiltersdialog.o geometry.o moc_blasthitfiltersdialog.cpp moc_mygraphicsview.o NMM.o tablewidgetitemdouble.o
blasthit.o globals.o moc_blasthitfiltersdialog.o moc_myprogressdialog.cpp NodeAttributes.o tablewidgetitemint.o
blastqueries.o GmlParser.o moc_blastquery.cpp moc_myprogressdialog.o nodewidthvisualaid.o tablewidgetitemname.o
blastquery.o graph moc_blastquery.o moc_mytablewidget.cpp numexcept.o tablewidgetitemshown.o
blastquerypath.o GraphAttributes.o moc_blastsearchdialog.cpp moc_mytablewidget.o ogdf tests
blastsearchdialog.o GraphCopy.o moc_blastsearchdialog.o moc_nodewidthvisualaid.cpp Ogml.o ui
blastsearch.o graphicsitemedge.o moc_buildblastdatabaseworker.cpp moc_nodewidthvisualaid.o OgmlParser.o ui_aboutdialog.h
buildblastdatabaseworker.o graphicsitemnode.o moc_buildblastdatabaseworker.o moc_pathspecifydialog.cpp path.o ui_blasthitfiltersdialog.h
build_scripts graphicsviewzoom.o moc_changenodedepthdialog.cpp moc_pathspecifydialog.o pathspecifydialog.o ui_blastsearchdialog.h
changenodedepthdialog.o graphinfodialog.o moc_changenodedepthdialog.o moc_querypathsdialog.cpp PoolMemoryAllocator.o ui_changenodedepthdialog.h
changenodenamedialog.o graphlayoutworker.o moc_changenodenamedialog.cpp moc_querypathsdialog.o program ui_changenodenamedialog.h
ClusterGraphAttributes.o graphlocation.o moc_changenodenamedialog.o moc_querypathsequencecopybutton.cpp qrc_images.cpp ui_enteroneblastquerydialog.h
ClusterGraph.o Graph.o moc_colourbutton.cpp moc_querypathsequencecopybutton.o qrc_images.o ui_graphinfodialog.h
colourbutton.o Hashing.o moc_colourbutton.o moc_querypathspushbutton.cpp QuadTreeNM.o ui_mainwindow.h
CombinatorialEmbedding.o image.o moc_enteroneblastquerydialog.cpp moc_querypathspushbutton.o QuadTreeNodeNM.o ui_myprogressdialog.h
command_line images moc_enteroneblastquerydialog.o moc_runblastsearchworker.cpp querypathsdialog.o ui_pathspecifydialog.h
commoncommandlinefunctions.o info.o moc_graphicsviewzoom.cpp moc_runblastsearchworker.o querypathsequencecopybutton.o ui_querypathsdialog.h
Constraint.o infotextwidget.o moc_graphicsviewzoom.o moc_settingsdialog.cpp querypaths.o ui_settingsdialog.h
COPYING load.o moc_graphinfodialog.cpp moc_settingsdialog.o querypathspushbutton.o verticallabel.o
debruijnedge.o MAARPacking.o moc_graphinfodialog.o moc_verticallabel.cpp README.md verticalscrollarea.o
debruijnnode.o main.o moc_graphlayoutworker.cpp moc_verticallabel.o reduce.o XmlParser.o
DinoLineBuffer.o mainwindow.o moc_graphlayoutworker.o moc_verticalscrollarea.cpp runblastsearchworker.o
➜ Bandage git:(master) ✗ ./Bandage

]]> Jit https://bioinformaticsonline.com/news/view/1178/r-package-for-visualising-go-enrichment Mon, 22 Jul 2013 12:25:09 -0500 https://bioinformaticsonline.com/news/view/1178/r-package-for-visualising-go-enrichment <![CDATA[R package for visualising GO enrichment]]> An R package that visualizes the GO enrichment results as word clouds and arranges them together with figures of experimental data. This allows us to draw informative summary plots for analyses such as differential expression or clustering, where for each gene list we display its behaviour in the experiment alongside with its GO annotations.

Links @ http://raivokolde.github.io/GOsummaries/

Lab @ http://biit.cs.ut.ee/about/main

]]> Jit https://bioinformaticsonline.com/news/view/4433/upcoming-r-webinar Wed, 11 Sep 2013 10:30:16 -0500 https://bioinformaticsonline.com/news/view/4433/upcoming-r-webinar <![CDATA[Upcoming R Webinar]]> This webinar will describe an R based approach to considerably speed GWAS computation time on a notebook book computer.

More http://www.extension.org/pages/68354/upcoming-webinar:-fast-semi-parallel-linear-and-logistic-regression-for-genome-wide-association-studi#.UjCL9azyPqV

Register @ https://www1.gotomeeting.com/register/237810425

]]> Jitendra Narayan https://bioinformaticsonline.com/pages/view/11399/next-generation-sequencing-in-r-or-bioconductor-environment Mon, 02 Jun 2014 18:03:09 -0500 https://bioinformaticsonline.com/pages/view/11399/next-generation-sequencing-in-r-or-bioconductor-environment <![CDATA[Next generation sequencing in R or bioconductor environment]]> There are many R software and bioconductor packages for NGS data analysis, some of them are as follows

Biostrings

The Biostrings package from Bioconductor provides an advanced environment for efficient sequence management and analysis in R. It contains many speed and memory effective string containers, string matching algorithms, and other utilities, for fast manipulation of large sets of biological sequences. The objects and functions provided by Biostrings form the basis for many other sequence analysis packages. Documentation

IRanges Overview

IRanges provides the low-level infrastructure and containers for handling sets of integer ranges within Bioconductor's BioC-Seq domain. Its classes and methods provide support for many more high-level packages like GenomicRanges, ShortRead, Rsamtools, etc. Documentation

GenomicRanges Overview

The GenomicRanges package serves as the foundation for representing genomic locations within the Bioconductor project. It is built upon the IRanges infrastructure and defines three major data containers - GRanges, GRangesList and GappedAlignments - which are supporting other important BioC-Seq packages including ShortRead, Rsamtools, rtracklayer, GenomicFeatures and BSgenome.  Compared to the IRanges container, the GRanges/GRangesList classes are more flexible and extensible to store additional information about sequence ranges, such as chromosome identifiers (sequence space), strand information and annotation data. Documentation

Motif Discovery

cosmo

The cosmo package allows to search a set of unaligned DNA sequences for a shared motif that may function as transcription factor binding site. The algorithm extends the popular motif discovery tool MEME (Bailey and Elkan, 1995) in that it allows the search to be supervised by specifying a set of constraints that the motif to be discovered must satisfy. Documentation

BCRANK

BCRANK is a method that takes a ranked list of genomic regions as input and outputs short DNA sequences that are overrepresented in some part of the list. The algorithm was developed for detecting transcription factor (TF) binding sites in a large number of enriched regions from high-throughput ChIP-chip or ChIP-seq experiments, but it can be applied to any ranked list of DNA sequences. Documentation

rGADEM: Documentation

MotIV: Documentation

ShortRead

The ShortRead package provides input, quality control, filtering, parsing, and manipulation functionality for short read sequences produced by high throughput sequencing technologies. While support is provided for many sequencing technologies, this package is primairly focused on Solexa/Illumina reads. Documentation

Rsamtools

Rsamtools provides functions for parsing and inspecting samtools BAM formatted binary alignment data. SAM/BAM is quickly becoming a universal standard alignment format, and is now supported by a wide variety of alignment tools. Documentation

Samtools Website
BWA (Burrows-Wheeler Alignment) Website

 

Additional tools for SNP analysis: 

snpMatrix

BSgenome

BSgenome provides an object oriented infrastructure for interacting with a Biostring based genome sequence. BSgenome packages exist for many common genomes, and can be created to represent custom genomes. See the "How to forge a BSgenome data package" Vignette for instructions to create a new BSgenome package if a prebuilt package does not exist for your organism. Documentation

rtracklayer

rtracklayer provides an interface for exporting annotation feature data to various genome browsers and file formats (such as GFF). See the Small RNA Profiling exercise for an example of using rtracklayer to visualize alignment coverage. Documentation

biomaRt

The biomaRt package, provides an interface to a growing collection of databases implementing the BioMart software suite (http:// www.biomart.org). The package enables online retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas. This data is retrieved automatically via the Internet, so it's recommended that you cache the data locally, or check versions if your code will be adversely affected by updates to these data. Documentation

ChIP-Seq Analysis Packages

Bioconductor provides various packages for analyzing and visualizing ChIP-Seq data. Only a small selection of these packages is introduced here. Additional useful introductions to this topic are: BioC ChIP-seq Case Study and BioC ChIP-Seq.

chipseq

The chipseq package combines a variety of HT-Seq packages to a pipeline for ChIP-Seq data analysis. Documentation

BayesPeak

BayesPeak is a peak calling package for identifying DNA binding sites of proteins in ChIP-Seq experiments. Its algorithm uses hidden Markov models (HMM) and Bayesian statistical methods. The following sample code introduces the identification of peaks with the BayesPeak package as well as the incorporation of read coverage information obtained by the chipseq package. Documentation [ Publication ]

PICS

The PICS package applies probabilistic inference to aligned-read ChIP-Seq data in order to identify regions bound by transcription factors. PICS identifies enriched regions by modeling local concentrations of directional reads, and uses DNA fragment length prior information to discriminate closely adjacent binding events via a Bayesian hierarchical t-mixture model. The following sample code uses the test data set from the above BayesPeak package in order to compare the results from both methods by identifying their consensus peak set. Documentation [ Publication ]

ChIPpeakAnno

The ChIPpeakAnno package provides. batch annotation of the peaks identified from either ChIP-seq or ChIP-chip experiments. It includes functions to retrieve the sequences around peaks, obtain enriched Gene Ontology (GO) terms, find the nearest gene, exon, miRNA or custom features such as most conserved elements and other transcription factor binding sites supplied by users. The package leverages the biomaRt, IRanges, Biostrings, BSgenome, GO.db, multtest and stat packages. Documentation

Additional ChIP-Seq Packages

DiffBind: Documentation

MOSAICS: Documentation

iSeq: Documentation

ChIPseqR: Documentation

ChiPsim: Documentation

CSAR: Documentation

ChIP-Seq Pipeline: PICS, rGADEM and MotIV (developer web site)

SPP: ChIP-seq processing pipeline

SPP Tutorial

MACS

SIPeS

RNA-Seq Analysis

Counting Reads that Overlap with Annotation Ranges 

The GenomicRanges package provides support for importing into R short read alignment data in BAM format (via Rsamtools) and associating them with genomic feature ranges, such as exons or genes. This way one can quantify the number of reads aligning to annotated genomic regions. The package defines general purpose containers for storing genomic intervals as well as more specialized containers for storing alignments against a reference genome. The two main functions for read counting provided by this infrastructure are countOverlaps and summarizeOverlaps. For their proper usage, it is important to read the corresponding PDF manual. Documentation

Differential Gene Expression Analysis with DESeq

The DESeq package contains functions to call differentially expressed genes (DEGs) in count tables based on a model using the negative binomial distribution. It expects as input a data frame with the raw read counts per region/gene of interest (rows) for each test sample (columns).  Such a count table can be imported into R or generated from BAM alignment files using the countOverlaps function as introduced above. Documentation

Differential Gene Expression Analysis with edgeR

The edgeR package uses empirical Bayes estimation and exact tests based on the negative binomial distribution to call differentially expressed genes (DEGs) in count data. 

Documentation

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); parathyroidSE explains how to generate exon read counts in R

DEGseq

baySeq (also see: segmentSeq)

Genominator (Bullard et al. 2010)

Detection of Alternative Splice Junctions

Another utility of RNA-Seq experiments is the analysis of splice junctions. The following software suggestions provide this utility:

ERANGE
TopHat

SpliceMap

SplitSeek

DNA-Methylation Data Analysis

HT-Seq Data Visualization

ggbio: ggplot2 extension for genomics data (online manual) Gviz: Plotting data and annotation information along genomic coordinates HilbertVis: Hilbert genome plots

GenomeGraphs: Plotting genomic information from Ensembl

TileQC: Flow Cell Quality Visualization

rtracklayer: R interface to genome browsers

genoPlotR: Plotting maps of genes and genomes

Genominator: Tools for storing, accessing, analyzing and visualizing genomic data.

 

To install all packages

source("http://bioconductor.org/biocLite.R")
biocLite()
biocLite(c("ShortRead", "Biostrings", "IRanges", "BSgenome", "rtracklayer", "biomaRt", "chipseq", "ChIPpeakAnno", "Rsamtools", "BayesPeak", "PICS", "GenomicRanges", "DESeq", "edgeR", "leeBamViews", "GenomicFeatures", "BSgenome.Celegans.UCSC.ce2"))

]]> John Parker https://bioinformaticsonline.com/news/view/19272/translate2r Fri, 21 Nov 2014 01:16:06 -0600 https://bioinformaticsonline.com/news/view/19272/translate2r <![CDATA[translate2R]]> After their presentation at the international “user!” conference, data analysis specialist eoda starts the public alpha testing of translate2R. With the start of alpha testing the innovative migration solution by the company hailing from Kassel discards the working title “translateR” and takes on the final product brand name “translate2R”. translate2R is a service for the automated translation of SPSS® syntax to R code, therefore supporting data analysts with a quick and low-risk migration to R.

The manual translation of many, frequently rather complex SPSS scripts often presents itself as a tedious and error-prone task, and represents a rather large obstacle for many analysts and companies to migrate to a modern, open source data management and analysis tool like R. With translate2R this hurdle will be diminished substantially.

Find at https://service.eoda.de/translater/?lang=en

]]> Rahul Nayak https://bioinformaticsonline.com/pages/view/21365/a-guide-for-complete-r-beginners Fri, 20 Feb 2015 23:36:46 -0600 https://bioinformaticsonline.com/pages/view/21365/a-guide-for-complete-r-beginners <![CDATA[A guide for complete R beginners !]]> This tutorial is intended to introduce users quickly to the basics of R, focusing on a few common tasks that  biologists need to perform  some basic analysis:  load a table, plot some graphs, and perform some basic statistics. More extensive tutorials can be found on the project website and via bioconductor (not covered here).

R-language: http://www.r-project.org

BioConductor: http://www.bioconductor.org

Advantages of R

  • Free!
  • Powerful, many libraries have been created to perform application specific tasks. e.g. analysis of microarray experiments and Next-Gen sequencing (bioconductor: including Bioseq group).
  • Presentation quality graphics
    • Save as a png, pdf or svg
  • History
    • What you do can be saved for the next time you use R.
    • Ability to turn it into an automated script to perform again and again on different data

Disadvantages

Preparation

  • (Optional) Download and save the tutorial data set from
    • http://bioinformatics.knowledgeblog.org/wp-content/uploads/bioinf/kerr/data.tsv
    • Start R (type R on a Linux or Mac terminal, or find the starting link from PC)

Getting More Help

  • Project Home page
    • http://www.r-project.org/
    • Check out the ‘introduction to R’, which is a much more in depth guide .
    • Also R has a built-in help system (see later)

Working directory

This is the directory used to store your data and results. It is useful if it is also the directory where your input data is stored.

  • Mac/Linux: this is the directory where you typed in R
  • PC: Change using the change working directory option
]]> Archana Malhotra https://bioinformaticsonline.com/news/view/22133/r-320-is-released Sat, 18 Apr 2015 05:06:44 -0500 https://bioinformaticsonline.com/news/view/22133/r-320-is-released <![CDATA[R 3.2.0 is released]]> R 3.2.0 (codename “Full of Ingredients”) was released yesterday. You can get the latest binaries version from here. (or the .tar.gz source code from here). The full list of new features and bug fixes is provided below.

Upgrading to R 3.2.0 on Windows

If you are using Windows you can easily upgrade to the latest version of R using the installr package. Simply run the following code:

# installing/loading the latest installr package:
install.packages("installr"); library(installr) #load / install+load installr
 
updateR() # updating R.

Running “updateR()” will detect if there is a new R version available, and if so it will download+install it (etc.).

If you are an R blogger yourself you are invited to add your own R content feed to this site (Non-English R bloggers should add themselves- here)

NEW FEATURES

  • anyNA() gains a recursive argument.
  • When x is missing and names is not false (including the default value), Sys.getenv(x, names) returns an object of class "Dlist" and hence prints tidily.
  • (Windows.) shell() no longer consults the environment variable SHELL: too many systems have been encountered where it was set incorrectly (usually to a path where software was compiled, not where it was installed). R_SHELL, the preferred way to select a non-default shell, can be used instead.
  • Some unusual arguments to embedFonts() can now be specified as character vectors, and the defaults have been changed accordingly.
  • Functions in the Summary group duplicate less. (PR#15798)
  • (Unix-alikes.) system(cmd, input = ) now uses ‘shell-execution-environment’ redirection, which will be more natural if cmd is not a single command (but requires a POSIX-compliant shell). (Wish of PR#15508)
  • read.fwf() and read.DIF() gain a fileEncoding argument, for convenience.
  • Graphics devices can add attributes to their description in .Device and .Devices. Several of those included with R use a "filepath" attribute.
  • pmatch() uses hashing in more cases and so is faster at the expense of using more memory. (PR#15697)
  • pairs() gains new arguments to select sets of variables to be plotted against each other.
  • file.info(, extra_cols = FALSE) allows a minimal set of columns to be computed on Unix-alikes: on some systems without properly-configured caching this can be significantly faster with large file lists.
  • New function dir.exists() in package base to test efficiently whether one or more paths exist and are directories.
  • dput() and friends gain new controls hexNumeric and digits17 which output double and complex quantities as, respectively, binary fractions (exactly, see sprintf("%a")) and as decimals with up to 17 significant digits.
  • save(), saveRDS() and serialize() now support ascii = NA which writes ASCII files using sprintf("%a") for double/complex quantities. This is read-compatible with ascii = TRUE but avoids binary->decimal->binary conversions with potential loss of precision. Unfortunately the Windows C runtime’s lack of C99 compliance means that the format cannot be read correctly there in R before 3.1.2.
  • The default for formatC(decimal.mark =) has been changed to be getOption("OutDec"); this makes it more consistent with format() and suitable for use in print methods, e.g. those for classes "density", "ecdf", "stepfun" and "summary.lm".

    getOption("OutDec") is now consulted by the print method for class "kmeans", by cut(), dendrogram(), plot.ts() and quantile() when constructing labels and for the report fromlegend(trace = TRUE).

    (In part, wish of PR#15819.)

  • printNum() and hence format() and formatC() give a warning if big.mark and decimal.mark are set to the same value (period and comma are not uncommonly used for each, and this is a check that conventions have not got mixed).
  • merge() can create a result which uses long vectors on 64-bit platforms.
  • dget() gains a new argument keep.source which defaults to FALSE for speed (dput() and dget() are most often used for data objects where this can make dget() many times faster).
  • Packages may now use a file of common macro definitions in their help files, and may import definitions from other packages.
  • A number of macros have been added in the new ‘share/Rd’ directory for use in package overview help pages, and promptPackage() now makes use of them.
  • tools::parse_Rd() gains a new permissive argument which converts unrecognized macros into text. This is used by utils:::format.bibentry to allow LaTeX markup to be ignored.
  • options(OutDec =) can now specify a multi-byte character, e.g., options(OutDec = "u00b7") in a UTF-8 locale.
  • is.recursive(x) is no longer true when x is an external pointer, a weak reference or byte code; the first enables all.equal(x, x) when x .
  • ls() (aka objects()) and as.list.environment() gain a new argument sorted.
  • The "source" attribute (which has not been added to functions by R since before R version 2.14.0) is no longer treated as special.
  • Function returnValue() has been added to give on.exit() code access to a function’s return value for debugging purposes.
  • crossprod(x, y) allows more matrix coercions when x or y are vectors, now equalling t(x) %*% y in these cases (also reported by Radford Neal). Similarly, tcrossprod(x,y) and %*% work in more cases with vector arguments.
  • Utility function dynGet() useful for detecting cycles, aka infinite recursions.
  • The byte-code compiler and interpreter include new instructions that allow many scalar subsetting and assignment and scalar arithmetic operations to be handled more efficiently. This can result in significant performance improvements in scalar numerical code.
  • apply(m, 2, identity) is now the same as the matrix m when it has named row names.
  • A new function debuggingState() has been added, allowing to temporarily turn off debugging.
  • example() gets a new optional argument run.donttest and tools::Rd2ex() a corresponding commentDonttest, with a default such that example(..) in help examples will run donttest code only if used interactively (a change in behaviour).
  • rbind.data.frame() gains an optional argument make.row.names, for potential speedup.
  • New function extSoftVersion() to report on the versions of third-party software in use in this session. Currently reports versions of zlib, bzlib, the liblzma from xz, PCRE, ICU, TRE and the iconv implementation.

    A similar function grSoftVersion() in package grDevices reports on third-party graphics software.

    Function tcltk::tclVersion() reports the Tcl/Tk version.

  • Calling callGeneric() without arguments now works with primitive generics to some extent.
  • vapply(x, FUN, FUN.VALUE) is more efficient notably for large length(FUN.VALUE); as extension of PR#16061.
  • as.table() now allows tables with one or more dimensions of length 0 (such as as.table(integer())).
  • names(x) now clears the names of call and ... objects.
  • library() will report a warning when an insufficient dependency version is masking a sufficient one later on the library search path.
  • A new plot() method for class "raster" has been added.
  • New check_packages_in_dir_changes() function in package tools for conveniently analyzing how changing sources impacts the check results of their reverse dependencies.
  • Speed-up from Peter Haverty for ls() and methods:::.requirePackage() speeding up package loading. (PR#16133)
  • New get0() function, combining exists() and get() in one call, for efficiency.
  • match.call() gains an envir argument for specifying the environment from which to retrieve the ... in the call, if any; this environment was wrong (or at least undesirable) when thedefinition argument was a function.
  • topenv() has been made .Internal() for speedup, based on Peter Haverty’s proposal in PR#16140.
  • getOption() no longer calls options() in the main case.
  • Optional use of libcurl (version 7.28.0 from Oct 2012 or later) for Internet access:
    • capabilities("libcurl") reports if this is available.
    • libcurlVersion() reports the version in use, and other details of the "libcurl" build including which URL schemes it supports.
    • curlGetHeaders() retrieves the headers for http://, https://, ftp:// and ftps:// URLs: analysis of these headers can provide insights into the ‘existence’ of a URL (it might for example be permanently redirected) and is so used in R CMD check --as-cran.
    • download.file() has a new optional method "libcurl" which will handle more URL schemes, follow redirections, and allows simultaneous downloads of multiple URLs.
    • url() has a new method "libcurl" which handles more URL schemes and follows redirections. The default method is controlled by a new option url.method, which applies also to the opening of URLs via file() (which happens implicitly in functions such as read.table.)
    • When file() or url() is invoked with a https:// or ftps:// URL which the current method cannot handle, it switches to a suitable method if one is available.
  • (Windows.) The DLLs ‘internet.dll’ and ‘internet2.dll’ have been merged. In this version it is safe to switch (repeatedly) between the internal and Windows internet functions within an Rsession.

    The Windows internet functions are still selected by flag –internet2 or setInternet2(). This can be overridden for an url() connection via its new method argument.

    download.file() has new method "wininet", selected as the default by –internet2 or setInternet2().

  • parent.env<- can no longer modify the parent of a locked namespace or namespace imports environment. Contributed by Karl Millar.
  • New function isLoadedNamespace() for readability and speed.
  • names(env) now returns all the object names of an environment env, equivalently to ls(env, all.names = TRUE, sorted = FALSE) and also to the names of the corresponding list,names(as.list(env, all.names = TRUE)). Note that although names() returns a character vector, the names have no particular ordering.
  • The memory manager now grows the heap more aggressively. This reduces the number of garbage collections, in particular while data or code are loaded, at the expense of slightly increasing the memory footprint.
  • New function trimws() for removing leading/trailing whitespace.
  • cbind() and rbind() now consider S4 inheritance during S3 dispatch and also obey deparse.level.
  • cbind() and rbind() will delegate recursively to methods::cbind2 (methods::rbind2) when at least one argument is an S4 object and S3 dispatch fails (due to ambiguity).
  • (Windows.) download.file(quiet = FALSE) now uses text rather than Windows progress bars in non-interactive use.
  • New function hsearch_db() in package utils for building and retrieving the help search database used by help.search(), along with functions for inspecting the concepts and keywords in the help search database.
  • New function .getNamespaceInfo(), a no-check version of getNamespaceInfo() mostly for internal speedups.
  • The help search system now takes keyword entries in Rd files which are not standard keywords (as given in ‘KEYWORDS’ in the R documentation directory) as concepts. For standard keyword entries the corresponding descriptions are additionally taken as concepts.
  • New lengths() function for getting the lengths of all elements in a list.
  • New function toTitleCase() in package tools, tailored to package titles.
  • The matrix methods of cbind() and rbind() allow matrices as inputs which have 2^31 or more elements. (For cbind(), wish of PR#16198.)
  • The default method of image() has an explicit check for a numeric or logical matrix (which was always required).
  • URLencode() will not by default encode further URLs which appear to be already encoded.
  • BIC(mod) and BIC(mod, mod2) now give non-NA numbers for arima() fitted models, as nobs(mod) now gives the number of “used” observations for such models. This fixes PR#16198, quite differently than proposed there.
  • The print() methods for "htest", "pairwise.htest" and "power.htest" objects now have a digits argument defaulting to (a function of) getOption("digits"), and influencing all printed numbers coherently. Unavoidably, this changes the display of such test results in some cases.
  • Code completion for namespaces now recognizes all loaded namespaces, rather than only the ones that are also attached.
  • The code completion mechanism can now be replaced by a user-specified completer function, for (temporary) situations where the usual code completion is inappropriate.
  • unzip() will now warn if it is able to detect truncation when unpacking a file of 4GB or more (related to PR#16243).
  • methods() reports S4 in addition to S3 methods; output is simplified when the class argument is used. .S3methods() and methods::.S4methods() report S3 and S4 methods separately.
  • Higher order functions such as the apply functions and Reduce() now force arguments to the functions they apply in order to eliminate undesirable interactions between lazy evaluation and variable capture in closures. This resolves PR#16093.

More at http://cran.rstudio.com/

Reference: http://www.r-bloggers.com/r-3-2-0-is-released-using-the-installr-package-to-upgrade-in-windows-os/

]]> Neel https://bioinformaticsonline.com/opportunity/view/24178/essentials-of-statistics-and-data-analysis-using-r Mon, 31 Aug 2015 01:32:12 -0500 <![CDATA[Essentials of Statistics and Data Analysis using R]]> Clinical Development Services Agency (CDSA) is an extramural unit of Translational Health Science and Technology Institute (THSTI), Department of Biotechnology, Ministry of Science & Technology, Government of India. CDSA has a national mandate of strengthening capacity and capability building in the area of Clinical development and Translational Research.

CDSA is pleased to announce a 4 days hands-on training program on “Essentials of Statistics and Data Analysis using R” at ICGEB, Aruna Asaf Ali Road, New Delhi on December 1 – 4, 2015. This will involve developing and enhancing skills to understand basic principles of statistics for summarizing data and use of appropriate statistical tests as well as providing an understanding of data analysis using R. Didactic lectures with practical sessions will be delivered by experienced faculties from AIIMS and Novartis. Live classroom with power point presentations, case studies, mock exercise, practical sessions on R, group work with time for discussion and Q&A sessions are added advantages of this workshop.

Please contact gayatrivishwakarma.cdsa@thsti.res.in or vineetabaloni.cdsa@thsti.res.in for program and registration details.

Please nominate personage or register yourself on or before November 6, 2015 along with the electronic transfer of registration fee.

]]> https://bioinformaticsonline.com/news/view/27235/supposedly-educational-r Tue, 03 May 2016 16:43:08 -0500 https://bioinformaticsonline.com/news/view/27235/supposedly-educational-r <![CDATA[Supposedly Educational R]]> R 3.3.0 (codename “Supposedly Educational”) was released today. You can get the latest binaries version from here. (or the .tar.gz source code from here). The full list of new features and bug fixes is provided below.

If you are using Windows you can easily upgrade to the latest version of R using the installr package. Simply run the following code in Rgui:

install.packages("installr") # install 
setInternet2(TRUE)
installr::updateR() # updating R.

Running “updateR()” will detect if there is a new R version available, and if so it will download+install it (etc.). There is also a step by step tutorial (with screenshots) on how to upgrade R on Windows, using the installr package. If you only see the option to upgrade to an older version of R, then change your mirror or try again in a few hours (it usually take around 24 hours for all CRAN mirrors to get the latest version of R).

I try to keep the installr package updated and useful, so if you have any suggestions or remarks on the package – you are invited to open an issue in the github page.

]]> Rahul Nayak