BOL: Related items

DECIPHER

Anjana — Fri, 30 Sep 2016 09:33:12 -0500

DECIPHER is a software toolset that can be used to maintain, analyze, and decipher large amounts of DNA sequence data. To install DECIPHER, see the Downloads page.

To begin using DECIPHER read the "Getting Started DECIPHERing" tutorial. Refer to the PDF documents below for instructions on how to use DECIPHER for various tasks.

Address of the bookmark: http://decipher.cee.wisc.edu/Documentation.html

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

SDA: Long-read sequence and assembly of segmental duplications

Jit — Tue, 05 Mar 2019 10:00:57 -0600

Segmental Duplication Assembler (SDA; https://github.com/mvollger/SDA) constructs graphs in which paralogous sequence variants define the nodes and long-read sequences provide attraction and repulsion edges, enabling the partition and assembly of long reads corresponding to distinct paralogs.

https://github.com/mvollger/SDA

Address of the bookmark: https://www.nature.com/articles/s41592-018-0236-3

CONTIGuator !

BioStar — Fri, 04 Oct 2019 01:27:58 -0500

CONTIGuator is a Python script for Linux environments whose purpose is to speed-up the bacterial genome assembly process and to obtain a first insight of the genome structure using the well-known artemis comparison tool (ACT).

Address of the bookmark: https://sourceforge.net/projects/contiguator/

Coronavirus Resources !

Neel — Wed, 25 Mar 2020 17:11:33 -0500

2019nCoVR features comprehensive integration of genomic and proteomic sequences as well as their metadata information from the GISAID, NCBI, NMDC and CNCB/NGDC. It also incorporates a wide range of relevant information including scientific literatures, news, and popular articles for science dissemination, and provides visualization functionalities for genome variation analysis results based on all collected 2019-nCoV strains.

Annotation

https://bigd.big.ac.cn/ncov/variation/annotation

Genome wharehouse

https://bigd.big.ac.cn/gwh/browse/index

Released Genome

https://bigd.big.ac.cn/ncov/release_genome

Download data

ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/

Raw data

https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae

Address of the bookmark: https://bigd.big.ac.cn/ncov/about

Sample bandage input file for visual analysis

Jit — Wed, 06 Jan 2021 03:51:50 -0600

Sample bandage input file for visual analysis ...

HapSolo: An optimization approach for removing secondary haplotigs during diploid genome assembly and scaffolding.

Jit — Mon, 26 Oct 2020 21:23:36 -0500

Despite marked recent improvements in long-read sequencing technology, the assembly of diploid genomes remains a difficult task. A major obstacle is distinguishing between alternative contigs that represent highly heterozygous regions. If primary and secondary contigs are not properly identified, the primary assembly will overrepresent both the size and complexity of the genome, which complicates downstream analysis such as scaffolding.

More at https://github.com/esolares/HapSolo

Address of the bookmark: https://github.com/esolares/HapSolo

Randomness and Probability

Jit — Tue, 08 Nov 2016 07:17:32 -0600

Randomness and Probability

Randomness and probability are two differnet concepts: probaility is a measure (according to measure theory) which measures the randomness. Randomness is the object to be measured by probability. For example, probability is a mapping from randomness to the real number between 0 and 1. The similar examples are that the entropy measures the uncertanity; product of length and width measures the area of rectangle etc.

Please see “A mathematical theory of ability measure” by N. Kong ets for more examples to answer this question.

HapSolo: An optimization approach for removing secondary haplotigs during diploid genome assembly and scaffolding

Jit — Sat, 08 May 2021 21:25:00 -0500

HapSolo, that identifies secondary contigs and defines a primary assembly based on multiple pairwise contig alignment metrics. HapSolo evaluates candidate primary assemblies using BUSCO scores and then distinguishes among candidate assemblies using a cost function. The cost function can be defined by the user but by default considers the number of missing, duplicated and single BUSCO genes within the assembly. HapSolo performs hill climbing to minimize cost over thousands of candidate assemblies.

Address of the bookmark: https://github.com/esolares/HapSolo

Method in Comparative genomics !!

Jit — Wed, 09 Nov 2016 16:29:24 -0600

We present methods for the automatic determination of genome correspondence. The algorithms enabled the automatic identification of orthologs for more than 90% of genes and intergenic regions across the four species despite the large number of duplicated genes in the yeast genome. The remaining ambiguities in the gene correspondence revealed recent gene family expansions in regions of rapid genomic change.

We present methods for the identification of protein-coding genes based on their patterns of nucleotide conservation across related species. We observed the pressure to conserve the reading frame of functional proteins and developed a test for gene identification with high sensitivity and specificity. We used this test to revisit the genome of S. cerevisiae, reducing the overall gene count by 500 genes (10% of previously annotated genes) and refining the gene structure of hundreds of genes. We present novel methods for the systematic de novo identification of regulatory motifs. The methods do not rely on previous knowledge of gene function and in that way differ from the current literature on computational motif discovery. Based on the genome-wide conservation patterns of known motifs, we developed three conservation criteria that we used to discover novel motifs. We used an enumeration approach to select strongly conserved motif cores, which we extended and collapsed into a small number of candidate regulatory motifs. These include most previously known regulatory motifs as well as several noteworthy novel motifs. The majority of discovered motifs are enriched in functionally related genes, allowing us to infer a candidate function for novel motifs.

Our results demonstrate the power of comparative genomics to further our understanding of any species. Our methods are validated by the extensive experimental knowledge in yeast, and will be invaluable in the study of complex genomes like that of human.

Address of the bookmark: http://web.mit.edu/manoli/www/publications/Kellis_JCB_04.pdf