Tag: Next Generation Sequencing

SHOREmap 3.6 – Mutant Mapping with Next Generation Sequencing data

SHOREmap 3.6

:: DESCRIPTION

SHOREmap is an extension of the short read analysis pipeline SHORE. SHOREmap supports genome-wide genotyping and candidate-gene sequencing in a single step through analysis of deep sequencing data from a large pool of recombinants. SHOREmap requires aligned sequence data from a pooled mapping population. Based on the read count at marker positioning distinguishing the parents it regonizes regions with skews in the allele distribution. Annotating the changes within this interval rapidly leads to causal changes.

::DEVELOPER

KS’ Research Group / DW’s Research Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 SHOREmap 

:: MORE INFORMATION

Citation

Nat Methods. 2009 Aug;6(8):550-1.
SHOREmap: simultaneous mapping and mutation identification by deep sequencing.
Schneeberger K, Ossowski S, Lanz C, Juul T, Petersen AH, Nielsen KL, Jørgensen JE, Weigel D, Andersen SU.

RVD – Rare Single Nucleotide Variant Detection using Next-generation Sequencing

RVD

:: DESCRIPTION

RVD is a standalone algorithm for ultrasensitive rare single nucleotide variant detection using next-generation sequencing. The RVD program takes BAM files of deep sequencing reads in as input. Using a Beta-Binomial model, the algorithm estimates the error rate at each base position in the reference sequence.

::DEVELOPER

Ji Research Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  •  MacOsX / Linux
  • MatLab
  • Samtools

:: DOWNLOAD

  RVD

:: MORE INFORMATION

Citation

RVD: a command-line program for ultrasensitive rare single nucleotide variant detection using targeted next-generation DNA resequencing.
Cushing A, Flaherty P, Hopmans E, Bell JM, Ji HP.
BMC Res Notes. 2013 May 23;6:206.

UnoSeq 1.0 – Expression Profiling with Next Generation Sequencing without a Reference Genome

UnoSeq 1.0

:: DESCRIPTION

UnoSeq is a Java library to analyze next generation sequencing data (e.g. data generated by Illumina’s mRNAseq method) and especially perform expression profiling in organisms where no well-annotated reference genome exists.

::DEVELOPER

UnoSeq team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / Mac OsX.
  • Java
  • Bowtie
  • Velvet
  • BLAST

:: DOWNLOAD

 UnoSeq

:: MORE INFORMATION

Citation

Into the unknown: expression profiling without genome sequence information in CHO by next generation sequencing.
Birzele F, Schaub J, Rust W, Clemens C, Baum P, Kaufmann H, Weith A, Schulz TW, Hildebrandt T.
Nucleic Acids Res. 2010 Jul;38(12):3999-4010. doi: 10.1093/nar/gkq116.

SpliCQ 1.0 – Predict Alternative Splicing Events in Next Generation Sequencing data

SpliCQ 1.0

:: DESCRIPTION

SpliCQ can be used to analyse next generation sequencing reads for the expression of alternative splice variants by scoring the observations (reads) with known gene models (expectations) and novel gene models predicted based on the observations. Therefore the score allows to identify the most likely expressed isoforms in a tissue or cell line.

::DEVELOPER

SpliCQ team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/MacOsX
  • Java

:: DOWNLOAD

 SpliCQ

:: MORE INFORMATION

SNPTools 1.0 – SNP analysis in Next Generation Sequencing data

SNPTools 1.0

:: DESCRIPTION

SNPTools is a suite of tools that enables integrative SNP analysis in next generation sequencing data with large cohorts. It not only calls SNP in a population with high sensitivity and accuracy, but also employs a novel imputation engine to achieve highly accurate genotype calls in an efficient way.

::DEVELOPER

Human Genome Sequencing Center, Baylor College of Medicine

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ compiler

:: DOWNLOAD

 SNPTools

:: MORE INFORMATION

Citation

Genome Res. 2013 Jan 7. [Epub ahead of print]
An integrative variant analysis pipeline for accurate genotype/haplotype inference in population NGS data.
Wang Y, Lu J, Yu J, Gibbs RA, Yu F.

SNVer 0.5.3 / SNVerGUI – Rare and Common Variants Detection in Next Generation Sequencing

SNVer 0.5.3 / SNVerGUI

:: DESCRIPTION

SNVer is a statistical tool for calling common and rare variants in analysis of pool or individual next-generation sequencing data. It reports one single overall p-value for evaluating the significance of a candidate locus being a variant, based on which multiplicity control can be obtained. Loci with any (low) coverage can be tested and depth of coverage will be quantitatively factored into final significance calculation. SNVer runs very fast, making it feasible for analysis of whole-exome sequencing data, or even whole-genome sequencing data.

SNVerGUI is a desktop tool for variant detection from next generation sequencing data

:: SCREENSHOTS

SNVerGUI

::DEVELOPER

Zhi Wei

:: REQUIREMENTS

  • Linux/Windows/MacOsX

:: DOWNLOAD

 SNVer

:: MORE INFORMATION

Citation

Wei Z, Wang W, Hu P, Lyon GJ, and Hakonarson H,
SNVer: a statistical tool for variant calling in analysis of pooled or individual next-generation sequencing data,
Nucleic Acids Research, 2011, doi: 10.1093/nar/gkr599

W Wang, W Hu, F Hou, P Hu and Wei Z,
SNVerGUI: a desktop tool for variant analysis of next-generation sequencing data,
Journal of Medical Genetics, 2012 49 (12), 753-755.

PIFs 1.0 – Estimation of Population Allele Frequencies from Next-generation Sequencing data

PIFs 1.0

:: DESCRIPTION

PIFs (Pool_Ind_Freq_SNP.xls) is an excel encoded application (compatible with OpenOffice Calc) that includes various graphical and numerical outputs which allow NGS practitioners to assessing and comparing the precision in allele frequency estimation for both pool and diploid individual SNP data under various sampling, coverage and experimental error designs.

::DEVELOPER

Centre de Biologie et Gestion des Populations (CBGP)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows /  MacOsX
  • Excel

:: DOWNLOAD

 PIFs

:: MORE INFORMATION

Citation

Estimation of population allele frequencies from next-generation sequencing data: pool-versus individual-based genotyping.
Gautier M, Foucaud J, Gharbi K, Cézard T, Galan M, Loiseau A, Thomson M, Pudlo P, Kerdelhué C, Estoup A.
Mol Ecol. 2013 Jul;22(14):3766-79. doi: 10.1111/mec.12360.

targetSeqView – Visualize Next Generation Sequencing Reads over Putative Structural Variants

targetSeqView

:: DESCRIPTION

targetSeqView is a probability-based score and visualization method to aid in distinguishing true structural variants from alignment artifacts.

::DEVELOPER

targetSeqView team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • R

:: DOWNLOAD

  targetSeqView

:: MORE INFORMATION

Citation

Visualization and probability-based scoring of structural variants within repetitive sequences.
Halper-Stromberg E, Steranka J, Burns KH, Sabunciyan S, Irizarry RA.
Bioinformatics. 2014 Jun 1;30(11):1514-21. doi: 10.1093/bioinformatics/btu054.

PoPoolation 1.2.2 / PoPoolation2 1.201 / PoPoolation TE 1.02 – Analyse Pooled Next Generation Sequencing data

popoolation 1.2.2 / PoPoolation2 1.201 / PoPoolation TE 1.02

:: DESCRIPTION

PoPoolation is a collection of tools to facilitate population genetic studies of next generation sequencing data from pooled individuals

PoPoolation2 allows to compare allele frequencies for SNPs between two or more populations and to identify significant differences.

PoPoolation TE is a quick and simple pipeline for the analysis of transposable element insertions in (natural) populations using next generation sequencing.

DEVELOPER

Institute of Population Genetics, University of Veterinary Medicine Vienna

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 popoolation , PoPoolation2

:: MORE INFORMATION

Citation:

PoPoolation: a toolbox for population genetic analysis of next generation sequencing data from pooled individuals.
Kofler R, Orozco-terWengel P, De Maio N, Pandey RV, Nolte V, Futschik A, Kosiol C, Schlštterer C.
PLoS One. 2011 Jan 6;6(1):e15925.

Kofler,R.,Vinay Pandey, R. & Schloetterer, C
PoPoolation2: Identifying differentiation between populations using sequencing of pooled DNA samples (Pool-Seq);
Bioinformatics; Vol. 27 no. 24 2011, pages 3435–3436; doi:10.1093/bioinformatics/btr589

Robert Kofler, Andrea Betancourt and Christian Schloetterer (2012):
Sequencing of Pooled DNA Samples (Pool-Seq) Uncovers Complex Dynamics of Transposable Element Insertions in Drosophila melanogaster;
PLoS Genet 8(1): e1002487. doi:10.1371/journal.pgen.1002487

RVboost 0.1 – RNA-seq Variant Prioritization approach for Illumina Next-generation Sequencing data

RVboost 0.1

:: DESCRIPTION

RVboost is a novel method specific for RNA variant prioritization.

::DEVELOPER

RVboost team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 RVboost

:: MORE INFORMATION

Citation

RVboost: RNA-Seq variants prioritization using a boosting method.
Wang C, Davila JI, Baheti S, Bhagwate AV, Wang X, Kocher JP, Slager SL, Feldman AL, Novak AJ, Cerhan JR, Thompson EA, Asmann YW.
Bioinformatics. 2014 Aug 27. pii: btu577