BOL: Related items

COSMIC

Jit — Sat, 01 Oct 2016 15:04:10 -0500

The accurate description and annotation of structural variants can be complex. This is due to the different resolution that variants are reported from traditional cytogenetic coordinates down to the actual base pair positions. Furthermore, multiple rearrangements in a single area of the genome can make cataloguing and interpreting their effects challenging.

The Rearrangement Overview page describes the one or more breakpoints which make up a structural variant. A breakpoint is defined as a region or point where the sample sequence has altered from the reference sequence. Minimum interpretation is made of this data. One variant event can consist of one or multiple breakpoints. The Syntax (shown above the table) gives a detailed description of the variant and its location (e.g. chr11:g.36585230_76606619del, a deletion of roughly 40Mb on chromosome 11). Syntax is based on HGVS mutation nomenclature recommendations [http://www.hgvs.org/rec.html].

http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview

Address of the bookmark: http://cancer.sanger.ac.uk/cosmic/help/rearrangement/overview

Cancer Dependency Map

Jit — Thu, 13 Feb 2020 04:38:47 -0600

The consequences of alterations in the DNA of cancer cells and subsequent vulnerabilities are not fully understood. This project aims to assign a dependency to every cancer cell in a patient which could be exploited to develop new therapies. This knowledge is foundational for precision cancer medicine.

Address of the bookmark: https://depmap.sanger.ac.uk/

Prof. Chandrasekhar Kanduri Laboratory

Fri, 24 Jun 2016 16:59:43 -0500

Our lab has been interested in understanding how long noncoding RNAs control tumor initiation and progression, in addition to use them as potential biomarkers in diagnosis and therapy. We have been using neuroblastoma, a childhood cancer, as a model system to understand the functional role of long noncoding RNAs in cancer development and progression. By using new RNA sequencing technology on neuroblastoma tumors from a large group of Swedish children including both high-risk and low-risk neuroblastomas (108), we have identified several long noncoding RNAs that could have potential role in diagnosis and therapy. We are currently exploring the functional role of these differentially expressed long noncoding RNA in nuroblastoma progression and development.

Liu Lab

Tue, 04 Feb 2020 06:27:02 -0600

Shirley is a computational biologist with expertise in cancer epigenetics. Her research focuses on algorithm development and integrative mining from big data generated on microarrays, massively parallel sequencing, and other high throughput techniques to model the specificity and function of transcription factors, chromatin regulators and lncRNAs in tumor development, progression, drug response and resistance.

https://liulab-dfci.github.io/software/

DeCoSTAR - Detection of Co-evolution

Jit — Fri, 14 Apr 2017 06:27:25 -0500

DeCoSTAR is a software which aims at reconstructing ancestral gene or genome organizations, in the form of sets of neighborhood relations -adjacencies- between pairs of ancestral genes or gene domains.
Ancestral genes or domains are deduced from reconciled gene trees in a context of birth, speciation, duplication, loss, transfer, which are either given as input or computed with the ecceTERA package, to which DeCoSTAR is integrated. DeCoSTAR constructs parsimonious scenarios of gains and breakages of adjacencies, and contains in particular all the features of previous software DeCo, DeCoLT, ArtDeCo and DeClone. It provides statistical supports on ancestral adjacencies, or the possibility to handle badly assembled genomes.
DeCoSTAR is able to reconstruct the histories of domains inside genes, including gene fusion and fission events, as well as ancestral genome structures for dozens of whole genomes from all kingdoms of life in a few minutes.

Address of the bookmark: http://pbil.univ-lyon1.fr/software/DeCoSTAR/

Computational resources for TE discovery and TE detection

Abhimanyu Singh — Mon, 12 Feb 2018 10:29:18 -0600

Transposable Elements (TEs) to genome structure and evolution as well as their impact on genome sequencing, assembly, annotation and alignment has generated increasing interest in developing new methods for their computational analysis.

Following are the list of resource and location for TE discovery and TE detection:

BLASTER suite http://urgi.versailles.inra.fr/development/blaster/

Censor http://www.girinst.org/censor/download.php

find_ltr http://darwin.informatics.indiana.edu/cgi-bin/evolution/ltr.pl

FINDMITE http://jaketu.biochem.vt.edu/dl_software.htm

HMMER http://hmmer.janelia.org/

LTR_FINDER http://tlife.fudan.edu.cn/ltr_finder/

LTR_STRUC http://www.genetics.uga.edu/retrolab/data/LTR_Struc.html

LTR_MINER http://genomebiology.com/2004/5/10/R79/suppl/s7

LTR_par http://www.eecs.wsu.edu/~ananth/software.htm

MAK http://wesslercluster.plantbio.uga.edu/mak06.html

MaskerAid http://blast.wustl.edu/maskeraid/

mer-engine http://mer-engine.cshl.edu/mer-home.php

mreps http://bioinfo.lifl.fr/mreps/

PILER http://www.drive5.com/piler/

PLOTREP http://repeats.abc.hu/cgi-bin/plotrep.pl

RepBase http://www.girinst.org/

RepeatFinder http://cbcb.umd.edu/software/RepeatFinder/

RepeatGluer http://nbcr.sdsc.edu/euler/intro_tmp.htm

RepeatMasker http://www.repeatmasker.org/

RepeatRunner http://www.yandell-lab.org/repeat_runner/index.html

RepeatScout http://repeatscout.bioprojects.org/

repeat-match http://mummer.sourceforge.net/

REPuter http://www.genomes.de/

RetroMap http://www.burchsite.com/bioi/RetroMapHome.html

SMaRTFinder http://bioinf.dimi.uniud.it/software/software/smartfinder

Tandem Repeats Finder http://tandem.bu.edu/trf/trf.html

Transposon Cluster Finder http://www.mssm.edu/labs/warbup01/paper/files.html

TE nest http://www.plantgdb.org/prj/TE_nest/TE_nest.html

TRANSPO http://alggen.lsi.upc.es/recerca/search/transpo/transpo.html

TSDfinder http://www.ncbi.nlm.nih.gov/CBBresearch/Landsman/TSDfinder/

Tu Lab TE tools http://jaketu.biochem.vt.edu/dl_software.htm

WU-BLAST http://blast.wustl.edu

Platypus – R package for object detection and image segmentation.

BioStar — Mon, 09 Nov 2020 02:56:25 -0600

platypus is an R package for object detection and semantic segmentation. Currently using

platypus you can perform:

multi-class semantic segmentation using U-Net architecture
multi-class object detection using YOLOv3 architecture

You can install the latest version of platypus with remotes package:

remotes::install_github("maju116/platypus")

Note that in order to install platypus you need to install keras and tensorflow packages and Tensorflow version >= 2.0.0 ( Tensorflow 1.x will not be supported!)

Address of the bookmark: https://github.com/maju116/platypus

cisMuton: caller that detects SNVs/indels by comparing target (foreground) and control (background) samples

Jit — Tue, 11 Feb 2020 05:55:00 -0600

cisMuton is a caller that detects SNVs/indels by comparing target (foreground) and control (background) samples.

cisMuton calls mutations from target capture regions, which are defined by the overlapping regions of ${GROUP}.target.bed and ${GROUP}.gene.bed.

Please read the Quick Start Guide for cisCall first for an outline of how to run cisMuton.

Address of the bookmark: https://static.ciscall.org/cisCall5_doc/index.html

RITA: Rapid identification of high-confidence taxonomic assignments for metagenomic data

Jit — Mon, 27 Nov 2017 08:25:33 -0600

RITA is a standalone software package and Web server for taxonomic assignment of metagenomic sequence reads. By combining homology predictions from BLAST or UBLAST with compositional classifications from a Naive Bayes classifier, RITA is able to achieve very high accuracy on short reads. Unlike other hybrid approaches which combine these predictions for all sequences to be classified, RITA uses a pipeline to first identify cases where both types of classifier are in agreement, which constitute the highest-confidence set. Sequences not classified in this manner are subjected to a series of downstream classification steps.

This work has been accepted for publication:

MacDonald NJ, Parks DH, and Beiko RG. Rapid identification of taxonomic assignments. Accepted to Nucleic Acids Research April 4, 2012.

If you have any questions or bug reports, please let us know at .

Address of the bookmark: http://kiwi.cs.dal.ca/Software/RITA

Is reference genome necessary for gene expression study in transcriptome sequencing or for variant discovery in genome sequencing?

Rahul Agarwal — Wed, 17 Jul 2013 15:25:09 -0500

Like in case of plant genomes where nature of genome is too complex and huge in size to accomplish complete de novo assembly by current sequencing technology. What would be alternate solution? Can we live in reference free world?