<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/31375?offset=160 https://bioinformaticsonline.com/bookmarks/view/34475/oxford-nanopore-sequencing-hybrid-error-correction-and-de-novo-assembly-of-a-eukaryotic-genome Wed, 29 Nov 2017 05:08:53 -0600 https://bioinformaticsonline.com/bookmarks/view/34475/oxford-nanopore-sequencing-hybrid-error-correction-and-de-novo-assembly-of-a-eukaryotic-genome <![CDATA[Oxford Nanopore Sequencing, Hybrid Error Correction, and de novo Assembly of a Eukaryotic Genome]]> Monitoring the progress of DNA molecules through a membrane pore has been postulated as a method for sequencing DNA for several decades. Recently, a nanopore-based sequencing instrument, the Oxford Nanopore MinION, has become available that we used for sequencing the S. cerevisiae genome. To make use of these data, we developed a novel open-source hybrid error correction algorithm Nanocorr (https://github.com/jgurtowski/nanocorr) specifically for Oxford Nanopore reads, as existing packages were incapable of assembling the long read lengths (5-50kbp) at such high error rate (between ~5 and 40% error). With this new method we were able to perform a hybrid error correction of the nanopore reads using complementary MiSeq data and produce a de novo assembly that is highly contiguous and accurate: the contig N50 length is more than ten-times greater than an Illumina-only assembly (678kb versus 59.9kbp), and has greater than 99.88% consensus identity when compared to the reference. Furthermore, the assembly with the long nanopore reads presents a much more complete representation of the features of the genome and correctly assembles gene cassettes, rRNAs, transposable elements, and other genomic features that were almost entirely absent in the Illumina-only assembly.

Address of the bookmark: http://schatzlab.cshl.edu/data/nanocorr/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/35571/medusa-a-multi-draft-based-scaffolder Wed, 14 Feb 2018 02:49:00 -0600 https://bioinformaticsonline.com/bookmarks/view/35571/medusa-a-multi-draft-based-scaffolder <![CDATA[MeDuSa: a multi-draft based scaffolder]]> MeDuSa (Multi-Draft based Scaffolder), an algorithm for genome scaffolding. MeDuSa exploits information obtained from a set of (draft or closed) genomes from related organisms to determine the correct order and orientation of the contigs. MeDuSa formalises the scaffolding problem by means of a combinatorial optimisation formulation on graphs and implements an efficient constant factor approximation algorithm to solve it. In contrast to currently used scaffolders, it does not require either prior knowledge on the microrganisms dataset under analysis (e.g. their phylogenetic relationships) or the availability of paired end read libraries. 

Address of the bookmark: https://github.com/combogenomics/medusa

]]> Abhimanyu Singh https://bioinformaticsonline.com/researchlabs/view/43817/bioinfo-lab Fri, 04 Mar 2022 00:17:00 -0600 <![CDATA[Bioinfo Lab]]> The Institute of Bioinformatics conducts internationally renowned research and provides profound education in bioinformatics. Its research focuses on development and application of machine learning and statistical methods in biology and medicine.

Contact:
Computer Science Building (Science Park 3)
Altenberger Str. 69, A-4040 Linz, Austria
Tel. +43 732 2468 4520 / Fax +43 732 2468 4539
E-mail secretary@bioinf.jku.at

http://www.bioinf.jku.at/

]]> 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
Get:2 http://security.ubuntu.com/ubuntu xenial-security InRelease [107 kB] 
Hit:3 http://ppa.launchpad.net/webupd8team/java/ubuntu xenial InRelease 
Hit:4 http://be.archive.ubuntu.com/ubuntu xenial InRelease 
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Get:6 http://be.archive.ubuntu.com/ubuntu xenial-backports InRelease [107 kB] 
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]
Get:12 http://security.ubuntu.com/ubuntu xenial-security/main amd64 Packages [484 kB]
Get:13 http://security.ubuntu.com/ubuntu xenial-security/main i386 Packages [433 kB]
Get:14 http://security.ubuntu.com/ubuntu xenial-security/main Translation-en [209 kB]
Get:15 http://security.ubuntu.com/ubuntu xenial-security/main amd64 DEP-11 Metadata [67,5 kB]
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Get:17 http://security.ubuntu.com/ubuntu xenial-security/universe amd64 DEP-11 Metadata [107 kB]
Get:18 http://security.ubuntu.com/ubuntu xenial-security/universe DEP-11 64x64 Icons [147 kB]
Get:19 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 Packages [769 kB] 
Get:20 http://be.archive.ubuntu.com/ubuntu xenial-updates/main i386 Packages [710 kB] 
Get:21 http://be.archive.ubuntu.com/ubuntu xenial-updates/main Translation-en [319 kB]
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Get:24 http://be.archive.ubuntu.com/ubuntu xenial-updates/main DEP-11 64x64 Icons [228 kB] 
Get:25 http://be.archive.ubuntu.com/ubuntu xenial-updates/universe amd64 DEP-11 Metadata [246 kB]
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
Get:26 http://be.archive.ubuntu.com/ubuntu xenial-updates/universe DEP-11 64x64 Icons [331 kB]
Get:27 http://be.archive.ubuntu.com/ubuntu xenial-updates/multiverse amd64 DEP-11 Metadata [5.964 B]
Get:28 http://be.archive.ubuntu.com/ubuntu xenial-backports/main amd64 DEP-11 Metadata [3.328 B]
Get:29 http://be.archive.ubuntu.com/ubuntu xenial-backports/universe amd64 DEP-11 Metadata [5.088 B]
Fetched 4.779 kB in 2s (1.606 kB/s) 
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.
Need to get 15,2 MB of archives.
After this operation, 78,5 MB of additional disk space will be used.
Do you want to continue? [Y/n] Y
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Get:3 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 libqt5network5 amd64 5.5.1+dfsg-16ubuntu7.5 [540 kB]
Get:4 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 libxcb-icccm4 amd64 0.4.1-1ubuntu1 [10,4 kB]
Get:5 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 libxcb-image0 amd64 0.4.0-1build1 [12,3 kB]
Get:6 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 libxcb-keysyms1 amd64 0.4.0-1 [8.406 B]
Get:7 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 libxcb-randr0 amd64 1.11.1-1ubuntu1 [14,4 kB]
Get:8 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 libxcb-render-util0 amd64 0.3.9-1 [9.638 B]
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Get:32 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 libxcb-xfixes0-dev amd64 1.11.1-1ubuntu1 [11,2 kB]
Get:33 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 libxcb-sync-dev amd64 1.11.1-1ubuntu1 [10,1 kB]
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Get:35 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 libxshmfence-dev amd64 1.2-1 [3.676 B]
Get:36 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 libx11-xcb-dev amd64 2:1.6.3-1ubuntu2 [9.730 B]
Get:37 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 libwayland-bin amd64 1.12.0-1~ubuntu16.04.3 [18,4 kB]
Get:38 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 libwayland-dev amd64 1.12.0-1~ubuntu16.04.3 [92,4 kB]
Get:39 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 libmircore-dev amd64 0.26.3+16.04.20170605-0ubuntu1.1 [23,7 kB]
Get:40 http://be.archive.ubuntu.com/ubuntu xenial/main amd64 libprotobuf9v5 amd64 2.6.1-1.3 [326 kB]
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Get:53 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 libqt5concurrent5 amd64 5.5.1+dfsg-16ubuntu7.5 [24,3 kB]
Get:54 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 libqt5opengl5 amd64 5.5.1+dfsg-16ubuntu7.5 [128 kB]
Get:55 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 libqt5printsupport5 amd64 5.5.1+dfsg-16ubuntu7.5 [174 kB]
Get:56 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 libqt5sql5 amd64 5.5.1+dfsg-16ubuntu7.5 [104 kB]
Get:57 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 libqt5test5 amd64 5.5.1+dfsg-16ubuntu7.5 [84,5 kB]
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Get:60 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 qtbase5-dev-tools amd64 5.5.1+dfsg-16ubuntu7.5 [1.056 kB]
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Get:63 http://be.archive.ubuntu.com/ubuntu xenial-updates/main amd64 libqt5sql5-sqlite amd64 5.5.1+dfsg-16ubuntu7.5 [33,0 kB]
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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/bookmarks/view/36723/hapsembler-an-assembler-for-highly-polymorphic-genomes Tue, 22 May 2018 04:09:53 -0500 https://bioinformaticsonline.com/bookmarks/view/36723/hapsembler-an-assembler-for-highly-polymorphic-genomes <![CDATA[Hapsembler: An Assembler for Highly Polymorphic Genomes]]> Address of the bookmark: http://compbio.cs.toronto.edu/hapsembler/

]]> Jit https://bioinformaticsonline.com/blog/view/44703/the-role-of-lncrna-in-bioinformatics-unlocking-the-secrets-of-the-genome Sat, 07 Dec 2024 02:09:47 -0600 https://bioinformaticsonline.com/blog/view/44703/the-role-of-lncrna-in-bioinformatics-unlocking-the-secrets-of-the-genome <![CDATA[The Role of lncRNA in Bioinformatics: Unlocking the Secrets of the Genome]]> In the intricate dance of molecular biology, long non-coding RNAs (lncRNAs) have emerged as key players, capturing the interest of researchers worldwide. These RNA molecules, once dismissed as "junk," have proven to be vital in the regulation of gene expression, cellular processes, and the progression of diseases. The intersection of lncRNA studies and bioinformatics is transforming our understanding of these enigmatic molecules, offering profound insights into their structure, function, and therapeutic potential.

What Are lncRNAs?

lncRNAs are RNA transcripts longer than 200 nucleotides that do not code for proteins. Despite their non-coding nature, they play diverse roles in gene regulation, including chromatin remodeling, transcriptional control, and post-transcriptional processing. Unlike messenger RNAs (mRNAs), lncRNAs often function as scaffolds, decoys, or guides in cellular machinery, influencing biological processes such as cell differentiation, immune response, and even cancer metastasis.

Challenges in lncRNA Research

Identifying and understanding lncRNAs pose unique challenges:

  1. High Sequence Variability: Unlike protein-coding genes, lncRNAs exhibit low sequence conservation across species, making functional predictions difficult.
  2. Low Expression Levels: lncRNAs are often expressed at low levels, complicating their detection in transcriptomic data.
  3. Diverse Functions: The multifunctional nature of lncRNAs requires advanced computational tools to decipher their roles in complex networks.

Bioinformatics: A Crucial Ally in lncRNA Research

Bioinformatics bridges the gap between raw biological data and meaningful insights, making it indispensable in lncRNA research. Here’s how:

1. Identification and Annotation

High-throughput sequencing technologies like RNA-seq generate vast amounts of data. Bioinformatics tools such as StringTie, Cufflinks, and HISAT2 help assemble and annotate lncRNAs from this data. Additionally, databases like NONCODE, LNCipedia, and Ensembl provide curated repositories of lncRNA sequences and annotations.

2. Functional Prediction

Bioinformatics algorithms predict the potential functions of lncRNAs by analyzing their interactions with DNA, RNA, and proteins. Tools like LncRNA2Function and RIblast utilize sequence motifs and secondary structure predictions to hypothesize about the roles of specific lncRNAs.

3. Network Construction

lncRNAs often act as regulatory hubs. Bioinformatics platforms such as Cytoscape enable the visualization of lncRNA-mediated networks, elucidating their roles in pathways like cell cycle regulation and apoptosis.

4. Epigenetic Studies

lncRNAs are known to interact with chromatin-modifying complexes, influencing gene expression epigenetically. Tools like ChIP-seq and ATAC-seq, combined with computational pipelines, identify these interactions and map them to the genome.

5. Clinical Applications

Bioinformatics aids in the discovery of lncRNA biomarkers for diseases like cancer and neurodegenerative disorders. Machine learning models analyze differential expression profiles, helping prioritize lncRNAs with therapeutic potential.

Case Study: lncRNAs in Cancer Research

lncRNAs such as HOTAIR and MALAT1 have been implicated in cancer progression. Bioinformatics analyses have revealed their roles in promoting metastasis and altering the tumor microenvironment. For example, transcriptome analysis in cancer patients identifies lncRNA expression signatures, enabling precision medicine approaches.

Future Directions

The fusion of bioinformatics with experimental biology is unlocking the secrets of lncRNAs. Advances in artificial intelligence, single-cell sequencing, and structural modeling promise to overcome current limitations. Here are some promising directions:

  • Integrative Analysis: Combining multi-omics data to understand the interplay of lncRNAs with other biomolecules.
  • CRISPR Screens: Leveraging bioinformatics to design CRISPR-based functional screens for lncRNAs.
  • Therapeutic Development: Using bioinformatics to design lncRNA-based therapeutics, including antisense oligonucleotides and RNA interference tools.

Conclusion

lncRNAs are the hidden gems of the genome, and bioinformatics is the key to unearthing their full potential. As research progresses, lncRNAs could pave the way for novel diagnostics, targeted therapies, and personalized medicine, revolutionizing our approach to complex diseases.

The journey into the world of lncRNAs is only beginning, and bioinformatics will continue to play a pivotal role in decoding these molecular mysteries. Whether you’re a researcher, clinician, or bioinformatics enthusiast, the study of lncRNAs offers a fascinating frontier of discovery.

]]> LEGE https://bioinformaticsonline.com/blog/view/42633/protocol-for-de-novo-genome-assembly-using-illumina-reads Sat, 16 Jan 2021 21:42:11 -0600 https://bioinformaticsonline.com/blog/view/42633/protocol-for-de-novo-genome-assembly-using-illumina-reads <![CDATA[Protocol for De novo Genome Assembly using Illumina Reads]]> In this protocol, we address and describe the de novo assembly method for small to medium-sized genomes.

What is de novo genome assembly?
The method of taking a large number of short DNA sequences and placing them back together to create a reflection of the original chromosomes from which the DNA originated relates to genome assembly. No previous knowledge of the source DNA sequence length, structure or composition is inferred by De novo genome assemblies. The DNA of the target organism is split up into millions of tiny parts and read on a sequencing computer in a genome sequencing experiment. Depending on the sequencing system used, these "reads" range from 20 to 1000 nucleotide base pairs (bp) in length. Usually, length reads of 36 - 150 bp are produced for Illumina style short read sequencing. These reads can be either “single ended” as described above or “paired end.”

Why genome assembly?
In basic research into why and how they live, as well as in applied topics, identifying the DNA sequence of an organism is useful. Awareness of a DNA sequence may be useful in virtually any biological research because of the relevance of DNA to living things. For example, it may be used in medicine to classify, diagnose and eventually improve genetic disorder therapies. Similarly, pathogens study can lead to treatments for infectious diseases.

Raw NGS data
Reads can be saved as a Fasta file as text or in a FastQ file with their attributes. FastQ is the most common read file format since this is what the Illumina sequencing pipeline creates. This will henceforth be the subject of our conversation.

In a nutshell the protocol:
Get the sequence file(s) read from the sequencing machine (s).
Look at the readings - have an idea of what you have and what the standard is like.
If required, raw data cleanup/quality trimming.
Choose an adequate parameter set for assembly.
Assemble the data into scaffolds/contigs.
Examine the assembly performance and determine the efficiency of the assembly.

Read Quality Control:
Check the qualiy with fastQC.
Script
https://bioinformaticsonline.com/snippets/view/42540/install-fastqc-using-conda

Quality trimming/cleanup of read files.
This function trims adapters, barcodes and other contaminants from the reads.
Script
https://bioinformaticsonline.com/snippets/view/42542/trimmomatic-command

Genome Assembly:
The object of this portion of the protocol is to explain the method of assembling the reads trimmed by quality into draft contigs.

spades.py -1 illumina_R1.fastq.gz -2 illumina_R2.fastq.gz --careful --cov-cutoff auto -o result_of_spades_assembly_all_illumina

A significant range of short-read assemblers are available. Everyone with strengths and disadvantages of their own.
Some of the assemblers available include:
Velvet
SOAP-denovo
MIRA
ALLPATHS

Next step is to assess the suitability and what to do with a draft package of contiguous details for the remainder of the study now. Few stuff you can note about the contigs you just created: They're the draft Contigs. Any mis-assemblies can occur.

Mis-assembly checking and assembly metric tools:
QUAST - Quality assessment tool for genome assembly http://bioinf.spbau.ru/quast
Mauve assembly metrics - http://code.google.com/p/ngopt/wiki/How_To_Score_Genome_Assemblies_with_Mauve
InGAP-SV - https://sites.google.com/site/nextgengenomics/ingap and http://ingap.sourceforge.net/
inGAP is also useful for finding structural variants between genomes from read mappings.

Genome finishing tools:
Semi-automated gap fillers:
Gap filler - http://www.baseclear.com/landingpages/basetools-a-wide-range-of-bioinformatics-solutions/gapfiller/

IMAGE (V2) - http://sourceforge.net/apps/mediawiki/image2/index.php?title=Main_Page

Genome visualisers and editors:
Artemis - http://www.sanger.ac.uk/resources/software/artemis/
IGV - http://www.broadinstitute.org/igv/

Automated and semi automated annotation tools:
Prokka - https://github.com/tseemann/prokka
RAST - http://www.nmpdr.org/FIG/wiki/view.cgi/FIG/RapidAnnotationServer
JCVI Annotation Service - http://www.jcvi.org/cms/research/projects/annotation-service/

Frequent command use for the analysis are at:

https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly
https://bioinformaticsonline.com/pages/view/42275/frequent-parameters-for-bioinformatics-tools

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/43652/peregrine-shimmer-genome-assembly-toolkit Thu, 16 Dec 2021 02:50:19 -0600 https://bioinformaticsonline.com/bookmarks/view/43652/peregrine-shimmer-genome-assembly-toolkit <![CDATA[Peregrine & SHIMMER Genome Assembly Toolkit]]> Peregrine is a fast genome assembler for accurate long reads (length > 10kb, accuracy > 99%). It can assemble a human genome from 30x reads within 20 cpu hours from reads to polished consensus. It uses Sparse HIereachical MimiMizER (SHIMMER) for fast read-to-read overlaping without quadratic comparisions used in other OLC assemblers.

Address of the bookmark: https://github.com/cschin/Peregrine

]]> Abhi https://bioinformaticsonline.com/researchlabs/view/4591/the-breitbart-lab Tue, 17 Sep 2013 18:19:49 -0500 <![CDATA[The Breitbart lab]]> Breitbart’s lab has created a new branch of biology called metagenomics in which one can sample and sequence genetic material collected from the environment.

Breitbart lab is located in the College of Marine Science at the University of South Florida. She is chosen as top "10 Brilliant" scientist by Popular Science magazine.
http://www.popsci.com/science/article/2013-09/mya-breitbart

Lab Link:
https://sites.google.com/site/breitbartgenomicslab/
http://www.marine.usf.edu/faculty/mya-breitbart.shtml

]]> https://bioinformaticsonline.com/researchlabs/view/22761/pit-bioinformatics-group Tue, 16 Jun 2015 14:34:26 -0500 <![CDATA[PIT Bioinformatics Group]]> PIT Bioinformatics Group solves problems in bioinformatics and computational biology. Recent developed online tools:

- Budapest Reference Connectome: View a parametrizable connectome (brain graph).
- AmphoraNet: The webserver implementation of the AMPHORA2 workflow for phylogenetic analysis of metagenomic shotgun sequencing data.
- AmphoraVizu: Chart visualization for metagenomics analysis tools AMPHORA2 and AmphoraNet.
- SCARF: Free online association rule mining tool.

More at: http://pitgroup.org

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