Search Results for "rna-seq"
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Showing 272 open source projects for "rna-seq"
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SKUDONET ADC, operates at the application layer, efficiently distributing network load and application load across multiple servers. This not only enhances the performance of your application but also ensures that your web servers can handle more traffic seamlessly.
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HubSpot is an AI-powered customer platform with all the software, integrations, and resources you need to connect your marketing, sales, and customer service. HubSpot's connected platform enables you to grow your business faster by focusing on what matters most: your customers.
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FastQC
A quality control analysis tool for high throughput sequencing data
... then direct you to where your data may have problems and allow you to take necessary steps to correct it before doing any further analysis. FastQC is not tied to any specific type of sequencing technique, so it can be used to look at libraries of various experiment types (Genomic Sequencing, ChIP-Seq, RNA-Seq, BS-Seq etc etc). -
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kallisto
Near-optimal RNA-Seq quantification
kallisto is a program for near-optimal quantification of transcript abundances from RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads. It is based on the idea of using pseudoalignment to quickly determine reads and targets’ compatibility, with no need for alignment. According to benchmarks done on a Mac desktop computer, kallisto can quantify 30 million human bulk RNA-seq reads in less than 3 minutes with just the read sequences and a transcriptome... -
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awesome-single-cell
Community-curated list of software packages and data resources
Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc. List of software packages (and the people developing these methods) for single-cell data analysis, including RNA-seq, ATAC-seq, etc. Rapid, accurate and memory-frugal preprocessing of single-cell and single-nucleus RNA-seq data. Find bimodal, unimodal, and multimodal features in your data. Ascend is an R package comprised of fast, streamlined analysis functions optimized to address... -
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harmonypy
Integrate multiple high-dimensional datasets with fuzzy k-means
Harmony is an algorithm for integrating multiple high-dimensional datasets. harmonypy is a port of the harmony R package by Ilya Korsunsky. Harmony is a general-purpose R package with an efficient algorithm for integrating multiple data sets. It is especially useful for large single-cell datasets such as single-cell RNA-seq. -
When it comes to cybersecurity, what your clients don’t know can really hurt them. And believe it or not, keep them safe starts with asking questions. With ConnectWise Identify Assessment, get access to risk assessment backed by the NIST Cybersecurity Framework to uncover risks across your client’s entire business, not just their networks. With a clearly defined, easy-to-read risk report in hand, you can start having meaningful security conversations that can get you on the path of keeping your clients protected from every angle. Choose from two assessment levels to cover every client’s need, from the Essentials to cover the basics to our Comprehensive Assessment to dive deeper to uncover additional risks. Our intuitive heat map shows you your client’s overall risk level and priority to address risks based on probability and financial impact. Each report includes remediation recommendations to help you create a revenue-generating action plan.
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Immutable.js
Immutable collections for JavaScript
Immutable.js offers a collection of Persistent Immutable data structures for JavaScript. Immutable data is unchangeable once created, which makes application development so much simpler. There’s no defensive copying, and you get advanced memoization and change detection techniques with simple logic. Persistent data gives you a mutative API, one that doesn’t update data in-place but always produces new and updated data. The data structures that Immutable.js provides include List, Stack, Map,... -
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CPT
CPT: A Pre-Trained Unbalanced Transformer
... the new version of models with the old version of checkpoints with vocabulary alignment. Token embeddings found in the old checkpoints are copied. And other newly added parameters are randomly initialized. We further train the new CPT & Chinese BART 50K steps with batch size 2048, max-seq-length 1024, peak learning rate 2e-5, and warmup ratio 0.1. Aiming to unify both NLU and NLG tasks, We propose a novel Chinese Pre-trained Un-balanced Transformer (CPT). -
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RSeQC
RNA-seq data QC
RSeQC provides a number of functions to evaluate the quality of RNA-seq data. http://rseqc.sourceforge.net/ -
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Cyclops
An advanced platform for writing functional applications in Java 8
Fast purely functional datastructures (Vector, Seq / List, LazySeq / LazyList, NonEmptyList, HashSet, TreeSet, TrieSet, HashMap, LinkedMap, MultiMap, TreeMap, BankersQueue, LazyString, Discrete Interval Encoded Tree, Zipper, Range, Tree, DifferenceList, HList, Dependent Map). Structural Pattern Matching API (deconstruct algebraic product and sum types). Improved type safety via the removal of unsafe APIs -- E.g. Unlike Optional, Option has no get method (which could throw a null pointer... -
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Chat with your business data with Looker. More than just a modern business intelligence platform, you can turn to Looker for self-service or governed BI, build your own custom applications with trusted metrics, or even bring Looker modeling to your existing BI environment.
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Iperf 2
A means to measure network responsiveness and throughput
Iperf here is a means of measuring networks - capacity & latency (including ECN) over sockets both TCP and UDP. The goals include maintaining an active iperf code base across a broad set of platforms and operating systems. This is a multi-threaded design that scales with the number of CPUs or cores within a system. It supports both high impact and low impact techniques to obtain and report network performance. Current release: 2.2.0, April 10, 2024 (2.2.1 per coming soon) About iperf 2... -
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CPAT
RNA coding potential assessment tool
Using RNA-seq, tens of thousands of novel transcripts and isoforms have been identified (Djebali, et al Nature, 2012 , Carbili et al, Gene & Development, 2011) The discovery of these hidden transcriptome rejuvenate the need of distinguishing coding and noncoding RNA. However, Most previous coding potential prediction methods heavily rely on alignment, either pairwise alignment to search for protein evidence or multiple alignments to calculate phylogenetic conservation score (such as CPC... -
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PLEKv2
PLEKv2: predicting lncRNAs and mRNAs
PLEKv2: predicting lncRNAs and mRNAs based on intrinsic sequence features and the Coding-Net model INSTALLATION ------------- We upgraded PLEK to PLEKv2. All you need is RNA sequences (fasta file). Steps: 1. Download PLEK.2.1.tar.gz from * and decompress it. $ tar zvxf PLEK.2.1.tar.gz 2. Compile PLEK2.1 $ cd PLEK2.1 3. decompress Coding_Net_kmer6_orf.h5.bz2 model $ bunzip2 Coding_Net_kmer6_orf.h5.bz2 4. decompress Coding_Net_kmer6_orf_Arabidopsis.h5.bz2 model $ bunzip2 -
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relax
Molecular dynamics by NMR data analysis
The software package 'relax' is designed for the study of molecular dynamics through the analysis of experimental NMR data. Organic molecules, proteins, RNA, DNA, sugars, and other biomolecules are all supported. It supports exponential curve fitting for the calculation of the R1 and R2 relaxation rates, calculation of the NOE, reduced spectral density mapping, the Lipari and Szabo model-free analysis, study of domain motions via the N-state model and frame order dynamics theories using... -
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OmicSelector
Feature selection and deep learning modeling for omic biomarker study
OmicSelector is an environment, Docker-based web application, and R package for biomarker signature selection (feature selection) from high-throughput experiments and others. It was initially developed for miRNA-seq (small RNA, smRNA-seq; hence the name was miRNAselector), RNA-seq and qPCR, but can be applied for every problem where numeric features should be selected to counteract overfitting of the models. Using our tool, you can choose features, like miRNAs, with the most significant... -
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Weinberg-R2R
Faster creation of aesthetic RNA secondary structure diagrams
R2R is a program to assist in aesthetic drawings of RNA secondary structures. It is primarily aimed at drawing consensus diagrams, but can also draw single RNA molecules. R2R is freely available under the GNU Public License, and runs as a command-line program under UNIX-like systems such as Linux, MacOS Darwin or Cygwin on Windows. R2R was written by Zasha Weinberg. If you use it, please cite this paper: http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-12-3 -
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rna-test
script for variant calling of RNA-Seq
rna_test.sh is a shell script to run GATK best practice for variant-calling in RNAseq. It uses STAR2.5 for alignment, HaplotypeCaller to call variants, and Annovar to annotate. It also employs STAR-Fusion, Cufflinks and Stringtie FPKM, HTSeq_count and BAM-readcount. Notice: STAR_gene_read and HTSeq_count are added. exac03nontcga is added. STAR-Fusion is added. Stringtie is added. Disable BQSR (-skb) opteion is added. New avsnp(150) is updated. use -dcov in SplitNCigarReads... -
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sRNAWorkbench
The UEA sRNA Workbench
A suite of tools for analysing small RNA (sRNA) data from Next Generation Sequencing devices. Including expression profiling of known mirco RNA (miRNA), identification of novel miRNA in deep-sequencing data and identification of other interesting landmarks within high-throughput genetic data -
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miRge3
Comprehensive analysis of small RNA sequencing data
An update to Python package to perform comprehensive analysis of small RNA sequencing data, including miRNA annotation, A-to-I editing, novel miRNA detection, isomiR analysis, visualization through IGV, processing Unique Molecular Identifieres (UMI), tRF detection and producing interactive graphical output. miRge3.0 is developed in python v3.8 and is a recent update of our previous version miRge2.0. This build includes command line interface (CLI) and cross-platform Graphical User Interface... -
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TileCreator
A soft for designing primers for overlapping tiles over a transcript.
.... # Considerations - Only for MacOS for the moment. - Takes a very long time to open, but then it should work fine. - Only accepts DNA sequences as input ("T", not "U"). - It does not check for primer specificity nor primer dimers. - It is based on the original olaygo.py script found in seismic-rna by Matthew F. Allan (please check the Rouskin Lab repository). -
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HipMer
A High performance distributed memory assembler for big genomic data
... and accuracy in metagenomic assemblies. It is able to reconstruct rRNA elements via a separate algorithm which relies on reference SSU and LSU Hidden Markov Models to help traverse the contig graph around ribosomal RNA regions. For more information and publications visit the HipMer Portal (http://portal.nersc.gov/project/hipmer/) MetaHipMer is one component of the ExaBiome project (https://sites.google.com/lbl.gov/exabiome/home), part of the Exascale Computing Project: https://www.exascaleproject.org/ -
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CStone
Short-read de novo assembler that identifies chimeric contigs.
> CStone wiki: https://sourceforge.net/p/cstone/wiki/Home/ Related Software: 1. CStone: (See wiki) 2. CSReadGen: https://sourceforge.net/projects/csreadgen/ 3. CView: https://sourceforge.net/projects/cview/ 4. ChimSim: https://sourceforge.net/projects/chimsim/ 5. TVScript: https://sourceforge.net/projects/tvscript/ -
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CSReadGen
RNA-Seq read simulator that offers a wide range of parameter options.
> CSReadGen wiki: https://sourceforge.net/p/csreadgen/wiki/Home/ Related software: 1. CStone: https://sourceforge.net/projects/cstone/ 2. CSReadGen: (See wiki) 3. CView: https://sourceforge.net/projects/cview/ 4. ChimSim: https://sourceforge.net/projects/chimsim/ 5. TVScript: https://sourceforge.net/projects/tvscript/ -
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CIRI
CircRNA Identifier. A de novo circular RNA identification tool
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Keras TCN
Keras Temporal Convolutional Network
TCNs exhibit longer memory than recurrent architectures with the same capacity. Performs better than LSTM/GRU on a vast range of tasks (Seq. MNIST, Adding Problem, Copy Memory, Word-level PTB...). Parallelism (convolutional layers), flexible receptive field size (possible to specify how far the model can see), stable gradients (backpropagation through time, vanishing gradients). The usual way is to import the TCN layer and use it inside a Keras model. The receptive field is defined...