BOL: Related items

Learn python with example

BioStar — Tue, 06 Aug 2024 23:51:51 -0500

There are over 21 unique Python project walkthroughs in this content that range from beginner to advanced. See below for the timestamps for these projects:

snakepipes: A toolkit based on snakemake and python for analysis of NGS data

Jit — Thu, 30 May 2019 04:06:13 -0500

snakePipes are flexible and powerful workflows built using snakemake that simplify the analysis of NGS data.

DNA-mapping*
ChIP-seq*
RNA-seq*
ATAC-seq*
scRNA-seq
Hi-C
Whole Genome Bisulfite Seq/WGBS

(*Also available in "allele-specific" mode)

snakePipes can be installed via conda :

'conda install -c mpi-ie -c bioconda -c conda-forge snakePipes'.

Source code (https://github.com/maxplanck-ie/snakepipes) and documentation (https://snakepipes.readthedocs.io/en/latest/) are available online.

Address of the bookmark: https://github.com/maxplanck-ie/snakepipes

Python Mini Projects !

BioStar — Mon, 16 Jan 2023 02:14:03 -0600

There is a directory for each chapter of the book. Each directory contains a test.py program you can use with pytest to check that you have written the program correctly. I have included a short README to describe each exercise. If you have problems writing code (or if you would like to support this project!), the book contains details about the skills you need.

https://github.com/kyclark/tiny_python_projects

Address of the bookmark: https://github.com/kyclark/tiny_python_projects

HTTDB - Horizontally transferred transposable elements database

Rahul Nayak — Tue, 23 Jan 2018 12:07:31 -0600

Transposons or Transposable elements (TEs) are "mobile genes" capable of mobilization from one genomic location to another through non-homologous recombination. As this movement is mediated by its own proteins and does not contribute to the survival of the host that it inhabits, they are known as selfish genomic parasites. Despite their capacity for transposition inside genomes, they can frequently transpose the species boundaries and consequently migrate from one species to another. Such phenomenon is called Horizontal Transposons Transfer. HTT was first discovered by Daniels et al. (1984) when analysing a P element that was transferred from Drosophila willistoni to D. melanogaster. Since then, many more cases have been documented in the literature. Moreover, in the last years, such discoveries have been boosted by the unprecedented amount of new genomes available. Despite the recognition of HTT as a common phenomenon in recent years, it is still difficult to draw major conclusions about HTT patterns, such as where in the tree of life these cases are more frequently found. This is mainly due to the historical bias and lack of studies in many taxa. To date, there has been no easy way to visualise each TE or host species, and should be further analysed in order to provide a more comprehensive view of such phenomena. Based on these concerns, we developed the HTT database to keep an updated repository of HTT events in all eukaryotes, allowing not only TE specialists to add new events and search the database, but also non-specialists. Moreover, we expanded the database to include Horizontal-Virus Transfer also known as endogenization events which is characterized by the stable integration a viral genomic fragment into the host genome.

https://www.ncbi.nlm.nih.gov/pubmed/29315358

Address of the bookmark: http://lpa.saogabriel.unipampa.edu.br:8080/httdatabase/

Should you get sequenced? Not all bad genes predict disease

Rahul Agarwal — Thu, 29 Aug 2013 15:10:53 -0500

“What we really don’t know yet is whether the predictive aspects of the genome are going to turn out to be beneficial or potentially harmful”

“As we roll out genomic medicine we are fighting against this society-wide misconception that having the bad gene means you’re going to get the disease. That’s only true in a very few cases.”

Source:Today Health

Address of the bookmark: http://www.today.com/health/should-you-get-sequenced-not-all-bad-genes-predict-disease-8C11017154

FGENESH - Program for predicting multiple genes in genomic DNA sequences

BioStar — Thu, 20 Dec 2018 11:55:08 -0600

FGENESH is the fastest (50-100 times faster than GenScan) and most accurate gene finder available - see the figure and the table below. In recent rice genome sequencing projects, it was cited "the most successful (gene finding) program (Yu et al. (2002) Science 296:79) and was used to produce 87% of all high-evidence predicted genes (Goff et al. (2002) Science 296:79).

Address of the bookmark: http://www.softberry.com/berry.phtml?topic=fgenesh&group=help&subgroup=gfind

GEO2R: compare two or more groups of Samples

Rahul Nayak — Sun, 20 Dec 2020 11:49:41 -0600

GEO2R to compare two or more groups of Samples in order to identify genes that are differentially expressed across experimental conditions.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/geo/geo2r/

2.4 Mb Genome Size for World's Biggest Virus

Jitendra Narayan — Thu, 08 Aug 2013 10:05:37 -0500

The genome size of new discovered Pandoraviruses have roughly twice the size of the record-holding Megavirus genomic code. Interestingly only 6 percent of its genes resembled the genes other organisms. It is assume that it may come from a different origin.

For detail : http://www.sciencemag.org/content/341/6143/281

http://www.npr.org/blogs/health/2013/07/18/203298244/worlds-biggest-virus-may-have-ancient-roots

Enrichr: a comprehensive gene set enrichment analysis

Jit — Thu, 27 Apr 2017 05:42:09 -0500

Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.

https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkw377

Address of the bookmark: http://amp.pharm.mssm.edu/Enrichr/

Scalpel

Shruti Paniwala — Wed, 20 Aug 2014 02:07:58 -0500

A team from Cold Spring Harbor Laboratory has released an algorithm, called Scalpel, for finding insertions and deletions in next generation sequencing data sets. Scalpel, which is open source and available for download on SourceForge, outperformed the popular tools GATK HaplotypeCaller and SOAPindel in test runs on both simulated and real whole human exomes.

Like other indel callers, Scalpel works by performing de novo assembly of regions of interest, so that misalignment to the reference genome cannot obscure the presence of an insertion or deletion. Scalpel's innovation is to repeatedly check its assembly before comparing to the reference genome, to account for simple sequence repeats that are a regular source of error in indel calling. When Scalpel assembles an exon, it collects reads that map to that exon (including partial matches), splits them into k-mers, and creates a de Bruijn graph to span the exon; however, if it detects repeats in the map, it iteratively increases the size of the k-mers by one base until the repeats are eliminated. This ensures that the final assembly of the exon is highly accurate while minimizing compute time.

The Cold Spring Harbor team's validation of Scalpel, published over the weekend in Nature Methods, compares Scalpel's performance on a live whole exome against HaplotypeCaller and SOAPindel. The donor is an individual with serious neurological disorders, which may be linked to a high incidence of indels. One thousand indels from this individual's exome, called by one or more of the informatics pipelines, were selected for focused resequencing. This resequencing revealed a 77% true positive rate for Scalpel calls, dramatically better than the rates for either of the competing tools; Scalpel performed especially well with indels longer than five base pairs, a traditional weak point for indel callers.

Finally, the authors demonstrate Scalpel's use on a large set of genetic data from nearly 600 families who donated samples to the Simons Simplex Collection, a project of the Simons Foundation Autism Research Initiative. Scalpel found a very high enrichment for indels in children affected by autism, compared with their unaffected siblings, a pattern that persisted even after excluding common variants.