PCRduplicates – Estimate PCR Duplication Rate from High-throughput Sequencing data

PCRduplicates

:: DESCRIPTION

PCRduplicates is a computational method to estimate the PCR duplication rate in high-throughput DNA sequencing experiments

::DEVELOPER

Bansal Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

PCRduplicates

:: MORE INFORMATION

Citation

Bansal V.
A computational method for estimating the PCR duplication rate in DNA and RNA-seq experiments.
BMC Bioinformatics. 2017 Mar 14;18(Suppl 3):43. doi: 10.1186/s12859-017-1471-9. PMID: 28361665; PMCID: PMC5374682.

TERIUS 1.0.1 – Prediction of lncRNA via High-throughput Sequencing data

TERIUS 1.0.1

:: DESCRIPTION

TERIUS is a program designed to differentiate between long non-coding RNAs and transcripts with coding potential or transcripts that are actually 3’UTR fragments of mRNAs. TERIUS distinguishes these transcripts using two-step filtration process from bona fide lncRNAs.

:: DEVELOPER

BIG Lab. (BIOINFORMATICS & GENOMICS)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

TERIUS

:: MORE INFORMATION

Citation:

Choi SW, Nam JW.
TERIUS: accurate prediction of lncRNA via high-throughput sequencing data representing RNA-binding protein association.
BMC Bioinformatics. 2018 Feb 19;19(Suppl 1):41. doi: 10.1186/s12859-018-2013-9. PMID: 29504902; PMCID: PMC5836835.

ezVIR 2 – Human Virus Screening from high-throughput Sequencing data

ezVIR 2

:: DESCRIPTION

ezVIR is a bioinformatics pipeline which was designed to process HTS data from any of the standard platforms and to evaluate the entire spectrum of known human viruses at once, providing results that are easy to interpret and customizable.

::DEVELOPER

Prof Zdobnov Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

ezVIR

:: MORE INFORMATION

Citation

Petty TJ, Cordey S, Padioleau I, Docquier M, Turin L, Preynat-Seauve O, Zdobnov EM, Kaiser L.
Comprehensive human virus screening using high-throughput sequencing with a user-friendly representation of bioinformatics analysis: a pilot study.
J Clin Microbiol. 2014 Sep;52(9):3351-61. doi: 10.1128/JCM.01389-14. Epub 2014 Jul 9. PMID: 25009045; PMCID: PMC4313162.

MultiGeMS 1.0 – Detection of SNVs from Multiple Samples Using Model Selection on High-Throughput Sequencing Data

MultiGeMS 1.0

:: DESCRIPTION

MultiGeMS (Multi-sample Genotype Model Selection) is a multiple sample single nucleotide variant (SNV) caller that works with alignment files of high-throughput sequencing (HTS) data. MultiGeMS calls SNVs based on a statistical model selection procedure and accounts for enzymatic substitution sequencing errors.

::DEVELOPER

Cui Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C Compiler

:: DOWNLOAD

 MultiGeMS

:: MORE INFORMATION

Citation

MultiGeMS: Detection of SNVs from Multiple Samples Using Model Selection on High-Throughput Sequencing Data.
Murillo G, You N, Su X, Cui W, Reilly MP, Li M, Ning K, Cui X.
Bioinformatics. 2016 Jan 18. pii: btv753

metagenomeSeq 1.34.0 – Statistical Analysis of Sparse High-throughput Sequencing data

metagenomeSeq 1.34.0

:: DESCRIPTION

metagenomeSeq is designed to determine features (be it Operational Taxanomic Unit (OTU), species, etc.) that are differentially abundant between two or more groups of multiple samples. metagenomeSeq is designed to address the effects of both normalization and under-sampling of microbial communities on disease association detection and the testing of feature correlations.

::DEVELOPER

HCBravo Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • R
  • BioCOnductor

:: DOWNLOAD

  metagenomeSeq

:: MORE INFORMATION

Citation:

Nat Methods. 2013 Dec;10(12):1200-2. doi: 10.1038/nmeth.2658. Epub 2013 Sep 29.
Differential abundance analysis for microbial marker-gene surveys.
Paulson JN1, Stine OC, Bravo HC, Pop M.

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