BOL: Related items

funannotate: Eukaryotic Genome Annotation Pipeline

Jit — Wed, 19 Sep 2018 07:47:22 -0500

Funannotate is a genome prediction, annotation, and comparison software package. It was originally written to annotate fungal genomes (small eukaryotes ~ 30 Mb genomes), but has evolved over time to accomodate larger genomes. The impetus for this software package was to be able to accurately and easily annotate a genome for submission to NCBI GenBank. Existing tools (such as Maker) require significant manually editing to comply with GenBank submission rules, thus funannotate is aimed at simplifying the genome submission process.

Address of the bookmark: https://github.com/nextgenusfs/funannotate

ChopStitch: exon annotation and splice graph construction using transcriptome assembly and whole genome sequencing data

Rahul Nayak — Tue, 03 Jul 2018 04:14:52 -0500

ChopStitch is a new method for finding putative exons and constructing splice graphs using an assembled transcriptome and whole genome shotgun sequencing (WGSS) data. ChopStitch identifies exon-exon boundaries in de novo assembled RNA-seq data with the help of a Bloom filter that represents the k-mer spectrum of WGSS reads. The algorithm also detects base substitutions in transcript sequences corresponding to sequencing or assembly errors, haplotype variations, or putative RNA editing events. The primary output of our tool is a FASTA file containing putative exons. Further, exon edges are interrogated for alternative exon-exon boundaries to detect transcript isoforms, which are reported as splice graphs in dot output format.

Address of the bookmark: https://github.com/bcgsc/ChopStitch

DIAL

Abhimanyu Singh — Wed, 01 Mar 2017 08:42:28 -0600

A computational pipeline for identifying single-base substitutions between two closely related genomes without the help of a reference genome. DIAL works even when the depth of coverage is insufficient for de novo assembly, and it can be extended to determine small insertions/deletions. Our main motivation is to use this tool to survey the genetic diversity of endangered species as the identified sequence differences can be used to design genotyping arrays to assist in the species' management.

http://www.bx.psu.edu/~ratan/

Address of the bookmark: http://www.bx.psu.edu/miller_lab/

Eugene V. Koonin Lab

Tue, 09 Jan 2018 05:01:15 -0600

Interested in understanding the evolution of life. To obtain glimpses of such understanding, we employ existing and new methods of computational biology to perform research in several major areas.

https://www.ncbi.nlm.nih.gov/research/groups/koonin/

Understanding Greedy Algorithms

Jit — Mon, 12 Dec 2016 04:37:40 -0600

Learning greedy algo for biologist.

https://www.topcoder.com/community/data-science/data-science-tutorials/greedy-is-good/

This webpage is also useful for the same:

http://learninglover.com/examples.php?id=59

http://www.cs.rpi.edu/~magdon/ps/conference/super_biokdd.pdf

https://ocw.mit.edu/courses/biology/7-91j-foundations-of-computational-and-systems-biology-spring-2014/lecture-slides/MIT7_91JS14_Lecture6.pdf

http://schatzlab.cshl.edu/teaching/AssemblyClass/01.%20Assembly%20Intro.pdf

http://lsl.sinica.edu.tw/Services/Class/files/20150612449.pdf

http://www.cs.jhu.edu/~langmea/resources/lecture_notes/assembly_scs.pdf

https://www2.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-43.pdf

Address of the bookmark: https://www.topcoder.com/community/data-science/data-science-tutorials/greedy-is-good/

PANDASEQ

Shruti Paniwala — Mon, 23 Jan 2017 04:54:32 -0600

PANDASEQ assembles paired-end Illumina reads into sequences, trying to correct for errors and uncalled bases. The assembler reads two files in FASTQ format with quality information. If amplification primers were used (e.g., to isolate a variable region of the 16S gene, or the constant regions around zinc finger binding residues), they can be removed from the sequence during assembly. The final sequence will correct any uncalled bases in the overlapping region using the complementary strand. When mismatches occur in the overlapping region, the base with the better quality score is chosen.
The algorithm is as follows:

1.Find the positions where the forward and reverse primers match best above the threshold and discard the ends of the sequence, including the primer.
2.Pick and overlap to maximise the probability of the forward and reverse reads having come from a single piece of DNA.
3.Identify the masking of the end of the read with the quality score B or # as done by CASAVA and adjust the probabilities in this region.
4.Construct an assembled sequence between the primers and calculate the quality.
5.Check for various constraints, including quality, length, uncalled bases, and user-supplied modules.

http://neufeldserver.uwaterloo.ca/~apmasell/pandaseq_man1.html

Address of the bookmark: http://neufeldserver.uwaterloo.ca/~apmasell/pandaseq_man1.html

Salzberg lab

Mon, 15 May 2017 05:14:01 -0500

We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with biomedical scientists to apply these methods to current problems arising in a broad spectrum of biological and medical research areas. We’re also part of the Center for Computational Biology, a group of 20+ faculty members and their labs at Johns Hopkins working on computational, statistical, and mathematical methods that can turn massive genomic data sets into biologically and clinically useful information.

https://salzberg-lab.org/

NCBI Datasets pages

BioStar — Wed, 12 Jul 2023 06:29:31 -0500

Update! Assembly and Genome record pages now redirect to new NCBI Datasets pages. NCBI Datasets is a new resource that makes it easier to find and download genome data. Learn more: https://ncbiinsights.ncbi.nlm.nih.gov/2023/07/11/ncbi-datasets-genome-assembly-pages/ #NCBICGR

Effective July 10, 2023, NCBI’s Assembly and Genome record pages now redirect to new NCBI Datasets pages. As previously announced, these updates are part of our ongoing effort to modernize and improve your user experience. NCBI Datasets is a new resource that makes it easier to find and download genome data.  

The following pages have been updated:

The NCBI Assembly record pages now redirect to the new NCBI Datasets Genome record pages that describe assembled genomes and provide links to related NCBI tools such as Genome Data Viewer and BLAST. 
The NCBI Genome record pages now redirect to the NCBI Datasets Taxonomy record pages that provide a taxonomy-focused portal to genes, genomes, and additional NCBI resources.

During this transition, you will have the option to return to the legacy Genome and Assembly record pages. We will remove the legacy pages in early 2024. 

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/

methylKit

Jit — Fri, 03 Jun 2016 10:09:29 -0500

methylKit is an R package for DNA methylation analysis and annotation from high-throughput bisulfite sequencing. The package is designed to deal with sequencing data from RRBS and its variants, but also target-capture methods such as Agilent SureSelect methyl-seq. In addition, methylKit can deal with base-pair resolution data for 5hmC obtained from Tab-seq or oxBS-seq. It can also handle whole-genome bisulfite sequencing data if proper input format is provided.

Address of the bookmark: https://github.com/al2na/methylKit