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Sleuth is a program for differential analysis of RNA-Seq data. It makes use of quantification uncertainty estimates obtained via Kallisto for accurate differential analysis of isoforms or genes, allows testing in the context of experiments with complex designs, and supports interactive exploratory data analysis via sleuth live.
SeqAn is a C++ library of efficient algorithms and data structures for the analysis of sequences with the focus on biological data. It contains algorithms and data structures for string representation and their manipulation, online and indexed string search, efficient I/O of bioinformatics file formats, sequence alignment, and more.
This package provides data structures, algorithms and educational resources for bioinformatics.
The WiggleTools package allows genomewide data files to be manipulated as numerical functions, equipped with all the standard functional analysis operators (sum, product, product by a scalar, comparators), and derived statistics (mean, median, variance, stddev, t-test, Wilcoxon's rank sum test, etc).
This package analyses the Oxford Nanopore sequencing data at signal-level. Nanopolish can calculate an improved consensus sequence for a draft genome assembly, detect base modifications, call SNPs (Single nucleotide polymorphisms) and indels with respect to a reference genome and more.
MOFA is a factor analysis model that provides a general framework for the integration of multi-omic data sets in an unsupervised fashion. Intuitively, MOFA can be viewed as a versatile and statistically rigorous generalization of principal component analysis to multi-omics data. Given several data matrices with measurements of multiple -omics data types on the same or on overlapping sets of samples, MOFA infers an interpretable low-dimensional representation in terms of a few latent factors. These learnt factors represent the driving sources of variation across data modalities, thus facilitating the identification of cellular states or disease subgroups.
The Spliced Transcripts Alignment to a Reference (STAR) software is based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences.
This package is used for demultiplexing single-cell sequencing experiments of pooled cells. These cells are labeled with barcode oligonucleotides. The package implements methods to fit regression mixture models for a probabilistic classification of cells, including multiplet detection. Demultiplexing error rates can be estimated, and methods for quality control are provided.
BioJava is a project dedicated to providing a Java framework for processing biological data. It provides analytical and statistical routines, parsers for common file formats, reference implementations of popular algorithms, and allows the manipulation of sequences and 3D structures. The goal of the biojava project is to facilitate rapid application development for bioinformatics.
This package provides the core libraries.
python-scanrbp is a Python package that provides the scanRBP tool that loads RNA-protein binding motif PWM and computes the log-odds scores for all the loaded RBPs across a given genomic sequence and draws a heatmap of the scores.
This package provides a client for the OmniPath web service and many other resources. It also includes functions to transform and pretty print some of the downloaded data, functions to access a number of other resources such as BioPlex, ConsensusPathDB, EVEX, Gene Ontology, Guide to Pharmacology (IUPHAR/BPS), Harmonizome, HTRIdb, Human Phenotype Ontology, InWeb InBioMap, KEGG Pathway, Pathway Commons, Ramilowski et al. 2015, RegNetwork, ReMap, TF census, TRRUST and Vinayagam et al. 2011. Furthermore, OmnipathR features a close integration with the NicheNet method for ligand activity prediction from transcriptomics data, and its R implementation nichenetr.
Kraken is a taxonomic sequence classifier that assigns taxonomic labels to DNA sequences. Kraken examines the k-mers within a query sequence and uses the information within those k-mers to query a database. That database maps k-mers to the lowest common ancestor (LCA) of all genomes known to contain a given k-mer.
Bio-vcf provides a DSL for processing the VCF format. Record named fields can be queried with regular expressions. Bio-vcf is a new generation VCF parser, filter and converter. Bio-vcf is not only very fast for genome-wide (WGS) data, it also comes with a filtering, evaluation and rewrite language and can output any type of textual data, including VCF header and contents in RDF and JSON.
This is a set of R functions that allows you to generate precise figures. This tool will create clean markdown reports about what you just discovered.
FastQC aims to provide a simple way to do some quality control checks on raw sequence data coming from high throughput sequencing pipelines. It provides a modular set of analyses which you can use to give a quick impression of whether your data has any problems of which you should be aware before doing any further analysis.
The main functions of FastQC are:
Import of data from BAM, SAM or FastQ files (any variant);
Providing a quick overview to tell you in which areas there may be problems;
Summary graphs and tables to quickly assess your data;
Export of results to an HTML based permanent report;
Offline operation to allow automated generation of reports without running the interactive application.
TopHat is a fast splice junction mapper for nucleotide sequence reads produced by the RNA-Seq method. It aligns RNA-Seq reads to mammalian-sized genomes using the ultra high-throughput short read aligner Bowtie, and then analyzes the mapping results to identify splice junctions between exons.
BBKNN is a batch effect removal tool that can be directly used in the Scanpy workflow. It serves as an alternative to scanpy.api.pp.neighbors(), with both functions creating a neighbour graph for subsequent use in clustering, pseudotime and UMAP visualisation. If technical artifacts are present in the data, they will make it challenging to link corresponding cell types across different batches. BBKNN actively combats this effect by splitting your data into batches and finding a smaller number of neighbours for each cell within each of the groups. This helps create connections between analogous cells in different batches without altering the counts or PCA space.
Telomerecat is a tool for estimating the average telomere length (TL) for a paired end, whole genome sequencing (WGS) sample.
Telomerecat is adaptable, accurate and fast. The algorithm accounts for sequencing amplification artifacts, anneouploidy (common in cancer samples) and noise generated by WGS. For a high coverage WGS BAM file of around 100GB telomerecat can produce an estimate in ~1 hour.
genomepy is designed to provide a simple and straightforward way to download and use genomic data. This includes
searching available data,
showing the available metadata,
automatically downloading, preprocessing and matching data, and
generating optional aligner indexes.
All with sensible, yet controllable defaults.
eXpress is a streaming tool for quantifying the abundances of a set of target sequences from sampled subsequences. Example applications include transcript-level RNA-Seq quantification, allele-specific/haplotype expression analysis (from RNA-Seq), transcription factor binding quantification in ChIP-Seq, and analysis of metagenomic data.
This is an R package for pre-processing of flow and mass cytometry data. This package includes panel editing or renaming for FCS files, bead-based normalization and debarcoding.
This package lets you read and write files in Generic Feature Format (GFF) with Biopython integration.
Prodigal runs smoothly on finished genomes, draft genomes, and metagenomes, providing gene predictions in GFF3, Genbank, or Sequin table format. It runs quickly, in an unsupervised fashion, handles gaps, handles partial genes, and identifies translation initiation sites.
This package provides a library and collection of scripts to work with Illumina paired-end data (for CASAVA 1.8+).