SCRIP 1.0.0 – An Accurate Simulator for Single-Cell RNA Sequencing Data

SCRIP 1.0.0

:: DESCRIPTION

SCRIP provides a flexible Gamma-Poisson mixture and a Beta-Gamma-Poisson mixture framework to simulate scRNA-seq data.

::DEVELOPER

Fei Qin [aut, cre, cph]

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • R

:: DOWNLOAD

SCRIP

:: MORE INFORMATION

Citation:

Qin F, Luo X, Xiao F, Cai G.
SCRIP: an accurate simulator for single-cell RNA sequencing data.
Bioinformatics. 2021 Dec 7:btab824. doi: 10.1093/bioinformatics/btab824. Epub ahead of print. PMID: 34874992.

miRe2e – Finding pre-miRNA sequences in raw Genome-wide data

miRe2e

:: DESCRIPTION

miRe2e is a novel deep learning model based on Transformers that allows finding pre-miRNA sequences in raw genome-wide data.

::DEVELOPER

Research institute for signals, systems and computational intelligence

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • Python

:: DOWNLOAD

miRe2e

:: MORE INFORMATION

Citation:

Raad J, Bugnon LA, Milone DH, Stegmayer G.
miRe2e: a full end-to-end deep model based on Transformers for prediction of pre-miRNAs.
Bioinformatics. 2021 Dec 7:btab823. doi: 10.1093/bioinformatics/btab823. Epub ahead of print. PMID: 34875006.

PEPPRO v0.9.11 – A Modular, Containerized pipeline for PRO-seq Data Processing

PEPPRO v0.9.11

:: DESCRIPTION

PEPPRO is a pipeline for nascent RNA sequencing data. It can process PRO-seq, GRO-seq, and ChRO-seq data and is optimized on unique features of nascent RNA to be fast and accurate. It performs variable-length UMI adapter removal, read deduplication, trimming, mapping, QC, and signal tracks (bigWig) for plus and minus strands using mappability-scaled or unscaled read counts.

::DEVELOPER

Sheffield lab of computational biology

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

PEPPRO

:: MORE INFORMATION

Citation

Smith JP, Dutta AB, Sathyan KM, Guertin MJ, Sheffield NC.
PEPPRO: quality control and processing of nascent RNA profiling data.
Genome Biol. 2021 May 15;22(1):155. doi: 10.1186/s13059-021-02349-4. PMID: 33992117; PMCID: PMC8126160.

sgRNA-PSM – Predict sgRNAs on-target Activity based on Position Specific Mismatch

sgRNA-PSM

:: DESCRIPTION

sgRNA-PSM is a user-friendly and publicly accessible web-server to predict sgRNAs on-target activity based on Position Specific Mismatch

::DEVELOPER

Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Liu B, Luo Z, He J.
sgRNA-PSM: Predict sgRNAs On-Target Activity Based on Position-Specific Mismatch.
Mol Ther Nucleic Acids. 2020 Jun 5;20:323-330. doi: 10.1016/j.omtn.2020.01.029. Epub 2020 Jan 31. PMID: 32199128; PMCID: PMC7083770.

iCircDA-LTR – Identification of circRNA-disease Associations based on Learning to Rank

iCircDA-LTR

:: DESCRIPTION

iCircDA-LTR is a new predictor for circRNA-disease association prediction.

::DEVELOPER

Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Wei H, Xu Y, Liu B.
iCircDA-LTR: identification of circRNA-disease associations based on Learning to Rank.
Bioinformatics. 2021 May 8:btab334. doi: 10.1093/bioinformatics/btab334. Epub ahead of print. PMID: 33963827.

HDMC – Hierarchical Distribution Matching and Contrastive learning

HDMC

:: DESCRIPTION

HDMC is a novel deep learning based framework for batch effect removal in scRNA-seq data.

::DEVELOPER

HDMC team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

HDMC

:: MORE INFORMATION

Citation:

Wang X, Wang J, Zhang H, Huang S, Yin Y.
HDMC: a novel deep learning based framework for removing batch effects in single-cell RNA-seq data.
Bioinformatics. 2021 Dec 4:btab821. doi: 10.1093/bioinformatics/btab821. Epub ahead of print. PMID: 34864918.

RnaViz 2.0.3 – Secondary Structure Drawings of RNA Molecules

RnaViz 2.0.3

:: DESCRIPTION

RnaViz is a user-friendly, portable, GUI program for producing publication-quality secondary structure drawings of RNA molecules. Drawings can be created starting from DCSE alignment files if they incorporate structure information or from mfold ct files. The layout of a structure can be changed easily. Display of special structural elements such as pseudo-knots or unformatted areas is possible. Sequences can be automatically numbered, and several other types of labels can be used to annotate particular bases or areas. Although the program does not try to produce an initially non-overlapping drawing, the layout of a properly positioned structure drawing can be applied to newly created drawing using skeleton files. In this way a range of similar structures can be drawn with a minimum of effort. Skeletons for several types of RNA molecule are included with the program.

::DEVELOPER

Peter De Rijk

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

RnaViz

:: MORE INFORMATION

Citation

Peter De Rijk, Jan Wuyts and Rupert De Wachter (2003)
RnaViz2: an improved representation of RNA secondary structure.
Bioinformatics 19(2): 299-300

miRbiom – A Machine Learning Approach to Profile miRNAs

miRbiom

:: DESCRIPTION

miRbiom: Machine-Learning on Bayesian Causal Nets of RBP-miRNA interactions successfully predicts miRNA profiles

::DEVELOPER

SCBB-LAB (Studio of Computational Biology and Bioinformatics)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

miRbiom

:: MORE INFORMATION

Citation

Pradhan UK, Sharma NK, Kumar P, Kumar A, Gupta S, Shankar R.
miRbiom: Machine-learning on Bayesian causal nets of RBP-miRNA interactions successfully predicts miRNA profiles.
PLoS One. 2021 Oct 12;16(10):e0258550. doi: 10.1371/journal.pone.0258550. PMID: 34637468; PMCID: PMC8509996.

RBPSpot – Learning on Appropriate Contextual Information for RBP Binding Sites Discovery

RBPSpot

:: DESCRIPTION

BPSpot is a tool to identify RBP binding spots in RNA.

::DEVELOPER

SCBB-LAB (Studio of Computational Biology and Bioinformatics)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

RBPSpot

:: MORE INFORMATION

Citation

Sharma NK, Gupta S, Kumar A, Kumar P, Pradhan UK, Shankar R.
RBPSpot: Learning on appropriate contextual information for RBP binding sites discovery.
iScience. 2021 Oct 30;24(12):103381. doi: 10.1016/j.isci.2021.103381. PMID: 34841226; PMCID: PMC8605353.