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High-throughput RNA interference screening software tools | Non-coding RNA data analysis

RNAi is a process in which gene expression is inhibited by small RNA molecules such as small interfering RNAs (siRNAs) and short hairpin RNAs. High-throughput RNAi screening is a breakthrough technology for functional genomics and for drug target discovery (Orvedahl et al., 2011; Whitehurst et al., 2007). A frequently used screening platform uses 96-well or 384-well microtiter plates, on which each well contains siRNA oligos designed to target a specific gene. Source text: Zhong et al., 2013.

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CARD / Comprehensive Analysis of RNAi Data
Integrates analysis and visualization of RNAi screen data. CARD allows the user to seamlessly carry out sequential steps in a rigorous data analysis workflow, including normalization, off-target analysis, integration of gene expression data, optimal thresholds for hit selection and network/pathway analysis. CARD also uses cutting-edge data visualization techniques that allow users to interact dynamically with the figures and tables displayed on the web-browser to facilitate the hit selection process.
ATARiS / Analytic Technique for Assessment of RNAi by Similarity
Takes advantage of patterns in RNAi data across multiple samples to enrich for RNAi reagents. For each gene in a screen, ATARiS identifies sets of reagents with similar behaviour. It produces quantitative, gene-level phenotype values, which provide an intuitive measure of the effect of gene suppression in each sample. Our method uses only data from reagents determined to have primarily on-target effects, discarding data from reagents with off-target effects. One key advance of ATARiS lies in the ability to distinguish reagents with on-target effects and reject reagents with significant off-target effects by mining patterns across multisample screens.
HiTSeekR / High-Throughput Screening Kit for R
A one-stop solution for chemical compound screens, siRNA knock-down and CRISPR/Cas9 knock-out screens, as well as microRNA inhibitor and -mimics screens. HiTSeekR exploits HTS screening data in quite heterogeneous contexts to generate novel hypotheses for follow-up experiments: (i) a genome-wide RNAi screen to uncover modulators of TNF, (ii) a combined siRNA and miRNA mimics screen on vorinostat resistance and (iii) a small compound screen on KRAS synthetic lethality. HiTSeekR is the first approach to close the gap between raw data processing, network enrichment and wet lab target generation for various HTS screen types.
A package for the free statistical environment R which performs an analysis of high-throughput RNA interference (RNAi) knock-down experiments, generating lists of relevant genes and pathways out of raw experimental data. The library provides a quality assessment of the signal intensities, as well as a broad range of options for data normalization, different statistical tests for the identification of significant siRNAs, and a significance analysis of the biological processes involving corresponding genes. The results of the analysis are presented as a set of HTML pages. Additionally, all values and plots are available as either text files or pdf and png files.
HTS Helper
A handy freeware utility that can be used to process high-throughput screening data. The HTS Helper utility has been created to facilitate the systematic error correction of experimental HTS data. It implements several error correction and normalization methods: (i) matrix error amendment (MEA); (ii) partial mean polish (PMP); (iii) well correction; (iv) Z-score normalization and (v) B-score normalization. By design, HTS Helper completes its work in three steps. First, it reads an HTS dataset from the input data file. Second, it applies the selected data processing method, if any. And finally, it saves the modified dataset into the output data file.
A statistical modeling framework that is based on experimental designs with at least two controls profiled throughout the experiment, and a normalization and variance estimation procedure with linear mixed-effects models. HTSmix (i) can be used in conjunction with practical experimental designs; (ii) allows extensions to alternative experimental workflows; (iii) enables a sensitive discovery of biologically meaningful changes; and (iv) strongly outperforms the existing noise reduction procedures.
Provides an analytic tool that can generate figures for displaying data and hit selection results from HTS experiments. displayHTS can be used to generate not only useful distinctive graphics including the plate-well series plot, plate image and dual-flashlight plot but also other commonly used figures such as volcano plot and plate correlation plot. The visualization of data and hit selection results enabled by displayHTS is critical to reveal various patterns of spatial effects and assay quality issues in HTS experiments for both small molecules and siRNAs.
Provides an R/Shiny open-source web application for interactive visualization and exploratory analysis of arrayed high-throughput data. Using a light-weight infrastructure suitable for desktop computers, HTSvis can be used to visualize raw data, perform quality control and interactively visualize screening results from single- to multi-channel measurements, such as image-based, screens. Input data can either be a result file obtained upon analysis with cellHTS or a generic table with raw or analyzed data from, e.g. a high-content microscopy screen.
IQEM / Intensity Quantile Estimation and Mapping
Represents an improvement over existing methods of image non-uniformity (NU) correction used in high-content screening (HCS), which are based on varying degrees of simplification to a linear model approximation of NU bias. By estimating the full non-linear form of the NU bias, the IQEM method essentially applies a correction factor that is appropriate to each intensity quantile in the measured image. The method is particularly pertinent for the quantification of extremely low-intensity cell phenotypes, where multiplicative correction provides an inaccurate fit to the low-intensity image NU, and where background subtraction does not adequately model the range of dim intensity levels. An additional positive feature of the IQEM algorithm is that it can be applied on a batch-specific basis such that a unique image NU correction is estimated for each batch.
Enables researchers without a programming background to use strictly standardized mean difference (SSMD) as both a plate quality and a hit selection metric to analyze large data sets. GUItars is capable of analyzing large-scale data sets from screens with or without replicates. It is designed to automatically generate and save numerous graphical outputs known to be among the most informative high-throughput data visualization tools capturing plate-wise and screen-wise performances. The tool enables rapid analysis and illustration of data from large- or small-scale RNAi screens using SSMD and other traditional analysis methods.
web cellHTS
A web-based application utility for the end-to-end analysis of large cell-based screening experiments by cellHTS. The software guides the user through the configuration steps that are required for the analysis of single or multi-channel experiments. The web-application provides options for various standardization and normalization methods, annotation of data sets and a comprehensive HTML report of the screening data analysis, including a ranked hit list. Sessions can be saved and restored for later re-analysis. The web frontend for the cellHTS R/Bioconductor package interacts with it through an R-server implementation that enables highly parallel analysis of screening data sets. web cellHTS further provides a file import and configuration module for common file formats.
SPICE / shRNA target prediction informed by comprehensive enquiry
A web-based analysis and search tool for investigating biological information about shRNA sequences using random oligonucleotides. SPICE displays target candidate genes with sequence alignment as well as information associated with each gene. It executes several tasks: (i) identification of siRNA sequence region in vector harboring shRNA-encoding DNA, (ii) sequence alignment between passenger strand of the siRNA and human RefSeq DNA database, (iii) functional annotation of the siRNA target DNA using databases, (iv) calculation of Gene Expression Omnibus (GEO) profile data to show significant microarray experiments in humans, and (v) preparation of downloadable summary files to support spreadsheet database construction in a local personal computer.
Corrects genome-wide siRNA screens for seed mediated off-target effect. ScsR offers suitable functions to identify the effective seeds/miRNAs and to visualize their effect. In example, it presents method that takes as input a dataframe containing the results of an siRNA screen. Then it adds a set of column that are useful for sorting to the dataframe. This screen must contain the siRNA sequences in a dedicated column (the sequences have to be provided in the guide/antisense orientation).
SbacHTS / Spatial background noise correction for High-Throughput RNAi Screening
A software tool for visualization, estimation and correction of spatial background noise in high-throughput RNAi screens. SbacHTS is supported on the Galaxy open-source framework with a user-friendly open access web interface. We find that SbacHTS software can effectively detect and correct spatial background noise, increase signal to noise ratio and enhance statistical detection power in high-throughput RNAi screening experiments. Although a genome-wide siRNA screen was used to demonstrate SbacHTS, the software is also applicable to other high-throughput screening experiments with similar workflow, such as chemical compound screening.
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