Bioinformatics Software: Sequence Analysis
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abSYNTH Bioinformatics Tools

abSYNTH Bioinformatics Tools | Bioinformatics Software: Sequence Analysis | Scoop.it

Via Costas Bouyioukos, Pedro Fernandes
Mel Melendrez-Vallard's insight:

well that's neat.

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Costas Bouyioukos's curator insight, March 26, 2014 4:31 AM

Our tutorial on tools for the systematic analysis of periodicities on genomic sequences run (almost) smoothly yesterday at the 2014 aSSB Evry Thematic School.

 

Find the tools of MEGA team on iSSB webtools server https://absynth.issb.genopole.fr/Bioinformatics/

under the systems biology section.
(registration, simple and free, is required)

Bioinformatics Software: Sequence Analysis
Research and postings on the latest in bioinformatic analysis software that's out there/published and open source. Let's not re-invent the wheel. Disclaimer: I do not promote one software over the next, you'll have to evaluate software on your own.
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StatQuest: PCA clearly explained | RNA-Seq Blog

StatQuest: PCA clearly explained | RNA-Seq Blog | Bioinformatics Software: Sequence Analysis | Scoop.it
RNA-seq results often contain a PCA or MDS plot. This StatQuest explains how these graphs are generated, how to interpret them, and how to determine if the plot
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A new statistical method allows researchers to infer different developmental processes from RNA-Seq data | RNA-Seq Blog

Through RNA sequencing, researchers can measure which genes are expressed in each individual cell of a sample. A new statistical method allows researchers to
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A Comparative View of Comparative Phylogeography

A Comparative View of Comparative Phylogeography | Bioinformatics Software: Sequence Analysis | Scoop.it
A recent issue of PNAS includes papers from a Sackler Colloquium on comparative phylogeography. As stated by the organizers, a major purpose of that gathering “was to bring together leading scienti…
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SNP calling from RNA-seq data without a reference genome | RNA-Seq Blog

SNPs (Single Nucleotide Polymorphisms) are genetic markers whose precise identification is a prerequisite for association studies. Methods to identify them are
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recount: A large-scale resource of analysis-ready RNA-seq expression data

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution
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A Primer on the Great BAMM Controversy

A Primer on the Great BAMM Controversy | Bioinformatics Software: Sequence Analysis | Scoop.it
Update, 26 August 2016, 2:30PM. A number of readers brought my attention to a series of blog posts by Moore et al. responding to Rabosky’s rebuttal of their published critique of BAMM. I̵…
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A workflow for analysis of small RNA sequencing data | RNA-Seq Blog

A workflow for analysis of small RNA sequencing data | RNA-Seq Blog | Bioinformatics Software: Sequence Analysis | Scoop.it
Small RNAs (size 20-30 nt) of various types have been actively investigated in recent years, and their subcellular compartmentalization and relative
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Indel detection from RNA-seq data: tool evaluation and strategies for accurate detection of actionable mutations

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Simultaneous gene finding in multiple genomes

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Rescooped by Mel Melendrez-Vallard from Viruses and Bioinformatics from Virology.uvic.ca
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Tips for effective use of BLAST and other NCBI tools

The National Center for Biotechnology Information (NCBI) provides one of the most extensive sets of web-based tools for biological research. The tools are indispensable when planning genomics experiments, including for qPCR, NGS, and CRISPR. In this presentation, Dr Matt McNeill takes a practical look at getting started with the wealth of NCBI tools, and shares some relevant tips to help you sift through the tools and options that we regularly use. In particular, he focuses on commonly adjusted parameters that will allow you to more effectively use the powerful Basic Local Alignment Algorithm Tool (BLAST) to identify off-target hybridization/annealing events. Dr McNeill also covers practical examples using NCBI tools to design assays.


Via Integrated DNA Technologies, Chris Upton + helpers
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Reopening Instructor Training

Software Carpentry is a volunteer non-profit organization dedicated to teaching basic computing skills to researchers.
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Benchmarking of the Oxford Nanopore MinION sequencing for quantitative and qualitative assessment of cDNA populations

Benchmarking of the Oxford Nanopore MinION sequencing for quantitative and qualitative assessment of cDNA populations | Bioinformatics Software: Sequence Analysis | Scoop.it
To assess the performance of the Oxford Nanopore Technologies MinION sequencing platform, cDNAs from the External RNA Controls Consortium (ERCC) RNA Spike-In mix were sequenced.
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RV-Typer: A Web Server for Typing of Rhinoviruses Using Alignment-Free Approach

Rhinoviruses (RV) are increasingly being reported to cause mild to severe infections of respiratory tract in humans. RV are antigenically the most diverse species of the genus Enterovirus and family Picornaviridae .

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Rail-RNA: Scalable analysis of RNA-seq splicing and coverage

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BMC Genomics

BMC Genomics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We do not make editorial decisions on the basis of the interest of a study or its likely impact. Studies must be scientifically valid; for research articles this includes a scientifically sound research question, the use of suitable methods and analysis, and following community-agreed standards relevant to the research field.

Specific criteria for other article types can be found in the submission guidelines.

BMC series - open, inclusive and trusted.


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ABSSeq – a new RNA-Seq analysis method based on modelling absolute expression differences | RNA-Seq Blog

The recent advances in next generation sequencing technology have made the sequencing of RNA (i.e., RNA-Seq) an extemely popular approach for gene expression
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LPEseq: Local-Pooled-Error Test for RNA Sequencing Experiments with a Small Number of Replicates

RNA-Sequencing (RNA-Seq) provides valuable information for characterizing the molecular nature of the cells, in particular, identification of differentially expressed transcripts on a genome-wide scale. Unfortunately, cost and limited specimen availability often lead to studies with small sample sizes, and hypothesis testing on differential expression between classes with a small number of samples is generally limited. The problem is especially challenging when only one sample per each class exists. In this case, only a few methods among many that have been developed are applicable for identifying differentially expressed transcripts. Thus, the aim of this study was to develop a method able to accurately test differential expression with a limited number of samples, in particular non-replicated samples. We propose a local-pooled-error method for RNA-Seq data (LPEseq) to account for non-replicated samples in the analysis of differential expression. Our LPEseq method extends the existing LPE method, which was proposed for microarray data, to allow examination of non-replicated RNA-Seq experiments. We demonstrated the validity of the LPEseq method using both real and simulated datasets. By comparing the results obtained using the LPEseq method with those obtained from other methods, we found that the LPEseq method outperformed the others for non-replicated datasets, and showed a similar performance with replicated samples; LPEseq consistently showed high true discovery rate while not increasing the rate of false positives regardless of the number of samples. Our proposed LPEseq method can be effectively used to conduct differential expression analysis as a preliminary design step or for investigation of a rare specimen, for which a limited number of samples is available.
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scater: pre-processing, quality control, normalisation and visualisation of single-cell RNA-seq data in R

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution
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Statistical inference for time course RNA-Seq data using a negative binomial mixed-effect model

Statistical inference for time course RNA-Seq data using a negative binomial mixed-effect model
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On (mis)interpreting STRUCTURE/ADMIXTURE results

On (mis)interpreting STRUCTURE/ADMIXTURE results | Bioinformatics Software: Sequence Analysis | Scoop.it
STRUCTURE, ADMIXTURE and other similar software are among the most cited programs in modern population genomics. They are algorithms that estimate allele frequencies and admixture proportions under…
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End Sequence Analysis ToolKit (ESAT) expands the extractable from single cell RNA-seq experiments

End Sequence Analysis ToolKit (ESAT) expands the extractable from single cell RNA-seq experiments | Bioinformatics Software: Sequence Analysis | Scoop.it
An international, peer-reviewed genome sciences journal featuring outstanding original research that offers novel insights into the biology of all organisms
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A pipeline for rapid gene discovery and expression analysis of a plant host and its obligate parasite | RNA-Seq Blog

A pipeline for rapid gene discovery and expression analysis of a plant host and its obligate parasite | RNA-Seq Blog | Bioinformatics Software: Sequence Analysis | Scoop.it
Current and emerging plant diseases caused by obligate parasitic microbes such as rusts, downy mildews, and powdery mildews threaten worldwide crop production
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RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR | RNA-Seq Blog

RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR | RNA-Seq Blog | Bioinformatics Software: Sequence Analysis | Scoop.it
The ability to easily and efficiently analyse RNA-sequencing data is a key strength of the Bioconductor project. Starting with counts summarised at the gene
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DEAR-O: Differential Expression Analysis based on RNA-seq data - Online

bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution
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Practical Approaches for Detecting Selection in Microbial Genomes

Practical Approaches for Detecting Selection in Microbial Genomes | Bioinformatics Software: Sequence Analysis | Scoop.it

Microbial genome evolution is shaped by a variety of selective pressures.

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Full Assemblathon 1 analysis by UCSC team now available

Full Assemblathon 1 analysis by UCSC team now available The Assemblathon group from UC Santa Cruz have now released their full analysis of the Assemblathon 1 genome assembly assement. Click on the...

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