BOL: Related items

CrossMap

Jitendra Narayan — Mon, 08 Feb 2016 15:47:00 -0600

CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between different assemblies (such as Human hg18 (NCBI36) <> hg19 (GRCh37), Mouse mm9 (MGSCv37) <> mm10 (GRCm38)).

It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.

CrossMap is designed to liftover genome coordinates between assemblies. It’s not a program for aligning sequences to reference genome.

We do not recommend using CrossMap to convert genome coordinates between species.

More at http://crossmap.sourceforge.net/

Address of the bookmark: http://crossmap.sourceforge.net/

Samtools Primer !!

Jit — Thu, 23 Jun 2016 07:18:17 -0500

SAMtools: Primer / Tutorial by Ethan Cerami, Ph.D.

keywords: samtools, next-gen, next-generation, sequencing, bowtie, sam, bam, primer, tutorial, how-to, introduction
Revisions

    1.0: May 30, 2013: First public release on biobits.org.
    1.1: July 24, 2013: Updated with Disqus Comments / Feedback section.
    1.2: December 19, 2014: Multiple updates, including:
        Updated to use samtools 1.1 and bcftools 1.2.
        Updated usage for bcftools.

About

SAMtools is a popular open-source tool used in next-generation sequence analysis. This primer provides an introduction to SAMtools, and is geared towards those new to next-generation sequence analysis. The primer is also designed to be self-contained and hands-on, meaning that you only need to install SAMtools, and no other tools, and sample data sets are provided. Terms in bold are also explained in the glossary at the end of the document.

Address of the bookmark: http://biobits.org/samtools_primer.html

Velvet tutorial

Poonam Mahapatra — Fri, 09 Dec 2016 04:19:07 -0600

The objective of this activity is to help you understand how to run Velvet in general, how to accurately estimate the insert size of a paired-end library through the use of Bowtie, the primary parameters of velvet, and the process involved in producing a de novo assembly from Illumina reads.

http://evomics.org/learning/assembly-and-alignment/velvet/

Address of the bookmark: http://evomics.org/learning/assembly-and-alignment/velvet/

Fools guide

Poonam Mahapatra — Sun, 02 Apr 2017 14:31:18 -0500

This website and accompaning documents are intended as a tool to help researchers dealing with non-model organisms acquire and process transcriptomic high-throughput sequencing data without having to learn extensive bioinformatics skills. It covers all steps from tissue collection, sample preparation and computer setup, through addressing biological questions with gene expression and SNP data.

http://sfg.stanford.edu/denovo.html

http://sfg.stanford.edu/sequencing.html

http://sfg.stanford.edu/BLAST.html

http://sfg.stanford.edu/denovo.html

Address of the bookmark: http://sfg.stanford.edu/guide.html

Mapping NGS

Abhimanyu Singh — Tue, 02 May 2017 07:58:07 -0500

NGS data are just a bunch of sequences, you have no idea which region in the genome each sequences comes from, which gene it represents...
To know that you have to align the sequences to the reference sequence. The reference sequence is in most cases the full genome sequence but sometimes, a library of EST sequences is used.
In either way, aligning your sequence reads to the reference sequence is called mapping.

The most used mappers of DNA-seq data are BWA and Bowtie for DNA-Seq data and Tophat, STAR or HISAT for RNA-Seq data. Mappers differ in which options they can take in, how fast and how accurate they are. Bowtie is faster than BWA, but looses some sensitivity (does not map an equal amount of reads to the correct position in the genome).

Address of the bookmark: http://wiki.bits.vib.be/index.php/Mapping_of_NGS_data

GABi

Fri, 06 Dec 2013 16:43:01 -0600

GABi Research
The major researching fields defined as the GABi scope are described next:
Sequence Analysis
Protein Structure Prediction
Comparative Genomics
Functional Analysis of Residues on Protein Families
Gene/Protein Networks
Genome structure & base composition
Highthroughput data analysis from NGS

Lab Page http://gabi.cidbio.org/index/

Update Genome Workbench 2.7.15 released

Surabhi Chaudhary — Wed, 26 Feb 2014 16:12:17 -0600

NCBI Genome Workbench is an integrated application for viewing and analyzing sequence data. With Genome Workbench, you can view data in publically available sequence databases at NCBI, and mix this data with your own private data.

Genome Workbench can display sequence data in many ways, including graphical sequence views, various alignment views, phylogenetic tree views, and tabular views of data. It can also align your private data to data in public databases, display your data in the context of public data, and retrieve BLAST results.

Genome Workbench is built on the NCBI C++ ToolKit and uses cross-platform APIs for graphics. It runs on your local machine, and is available for Windows 2000/XP, Linux, MacOS X, and various flavors of Unix.

NCBI Genome Workbench is an integrated application for viewing and analyzing sequence data. Genome Workbench was developed entirely in-house at NCBI and makes use of the NCBI C++ ToolKit. The C++ ToolKit provides a convenient and flexible cross-platform API for managing system internals, database connections, network sockets, and the NCBI data model. In addition, the C++ ToolKit provides the Object Manager, which abstracts handling of sequences and sequence-related objects.

New Features in Genome Workbench 2.7.15

Multiple Alignment View: implemented adaptive feature display when zooming in
Active Objects Inspector replaces Selection Inspector. New View should offer an improved selection context examination. See Using Active Objects Inspector tutorial for more details.
Binary packages for Linux OpenSUSE 13.1 are now available

Bug Fixes and Improvements in Genome Workbench 2.7.15

Fixed major issue with OpenGL overlay/scrolling. Could cause crashes or view scrolling irregularities
Multiple Pane View: fixed crash on loading BLAST results
Graphical Sequence View: fixed crash on zooming in and out, related to SNP track
Graphical Sequence View: fixed Go To Position dialog to give better diagnostics in case of a user error
Graphical Sequence View: PDF export fixed rendering of Markers with commas in the name
Text View / Flat File: fixed Mac OS rendering issues
Text View / Flat File: performance optimization, extended capabilities of real-time rendering of molecules to tens of thousands
File Import: optimization improvement to speed up load of files containing multiple project items
File Import: remapping stage now shows accession.version and description of molecules, instead of plain GI numbers
Mac OS: improved tooltips for toolbar buttons
Phylogenetic Tree Builder Tool: improved diagnostics of errors
Multiple Alignment View: optimizations to avoid main GUI freezes
Open Dialog: removed duplicate elements in table of genomes (load Genome)
PDF export: fixed issue with XREF table errors
Tree View: fixed issues with showing Force Layout progress on Mac OS
Tree View: PDF export fixed issues for showing labels of collapsed nodes
Tree View: added an option to stop layout
Tree View: broadcasting mechanism fixed not to accumulate selected nodes

Reference:

NCBI news

http://www.ncbi.nlm.nih.gov/tools/gbench/

How to sequence the human genome - Mark J. Kiel

Fri, 30 May 2014 13:24:11 -0500

View full lesson: http://ed.ted.com/lessons/how-to-sequence-the-human-genome-mark-j-kiel Your genome, every human's genome, consists of a unique DNA sequence of A's, T's, C's and G's that tell your cells how to operate. Thanks to technological advances, scientists are now able to know the sequence of letters that makes up an individual genome relatively quickly and inexpensively. Mark J. Kiel takes an in-depth look at the science behind the sequence. Lesson by Mark J. Kiel, animation by Marc Christoforidis.

COSMOS, our workflow management system for NGS data

Jit — Wed, 23 Jul 2014 07:29:14 -0500

COSMOS, our Python-based management system for implementing large-scale parallel workflows focusing on, but not restricted to, large-scale short-read "NGS" sequencing data is open-access published via Advance Access in Bioinformatics (Gafni et al. 2014). It is also available for download for non-commercial academic and research purposes at:

http://cosmos.hms.harvard.edu/.

Address of the bookmark: https://cosmos.hms.harvard.edu/

MIT Computational Biology Group

Thu, 18 Dec 2014 14:47:01 -0600

My research group consists primarily of computer science graduate students and postdocs with expertise in algorithms, statistical inferences and machine learning, and sharing a passion for understanding fundamental biological problems.

We work in a highly interdisciplinary environment at the interface of Computer Science and Biology. Since its inception, our lab has eagerly engaged in collaborative research partnerships with biological and experimental collaborators, facilitated by our affiliation with the Broad Institute and the Computational and Systems Biology initiative (CSBi) at MIT, our participation in the Epigenome Roadmap, ENCODE, and modENCODE consortia, and by several other ongoing collaborations at MIT, Harvard, and the Harvard Medical School affiliated hospitals.

http://compbio.mit.edu/