Several studies focus on the inference of developmental and response trajectories from single cell RNA-Seq (scRNA-Seq) data. A number of computational methods, often referred to as pseudo-time ordering, have been developed for this task. CRISPR has also been used to reconstruct lineage trees by inserting random mutations. The tbsp package implements an alternative method to detect significant, cell type specific sequence mutations from scRNA-Seq data.

This package implements the method csSAM that computes cell-specific differential expression from measured cell proportions using SAM.

Segemehl is software to map short sequencer reads to reference genomes. Segemehl implements a matching strategy based on enhanced suffix arrays (ESA). It accepts fasta and fastq queries (gzip'ed and bgzip'ed). In addition to the alignment of reads from standard DNA- and RNA-seq protocols, it also allows the mapping of bisulfite converted reads (Lister and Cokus) and implements a split read mapping strategy. The output of segemehl is a SAM or BAM formatted alignment file.

WebLogo is a web based application designed to make the generation of sequence logos as easy and painless as possible.

WebLogo can create output in several common graphics' formats, including the bitmap formats GIF and PNG, suitable for on-screen display, and the vector formats EPS and PDF, more suitable for printing, publication, and further editing. Additional graphics options include bitmap resolution, titles, optional axis, and axis labels, antialiasing, error bars, and alternative symbol formats.

A sequence logo is a graphical representation of an amino acid or nucleic acid multiple sequence alignment. Each logo consists of stacks of symbols, one stack for each position in the sequence. The overall height of the stack indicates the sequence conservation at that position, while the height of symbols within the stack indicates the relative frequency of each amino or nucleic acid at that position. The width of the stack is proportional to the fraction of valid symbols in that position.

Sjcount is a utility for fast quantification of splice junctions in RNA-seq data. It is annotation-agnostic and offset-aware. This version does count multisplits.

t-Stochastic Neighborhood Embedding (t-SNE) is a method for dimensionality reduction and visualization of high dimensional datasets. A popular implementation of t-SNE uses the Barnes-Hut algorithm to approximate the gradient at each iteration of gradient descent. This implementation differs in these ways:

• Instead of approximating the N-body simulation using Barnes-Hut, we interpolate onto an equispaced grid and use FFT to perform the convolution.

• Instead of computing nearest neighbors using vantage-point trees, we approximate nearest neighbors using the Annoy library. The neighbor lookups are multithreaded to take advantage of machines with multiple cores.

CLIPper is a tool to define peaks in CLIP-seq datasets.

Circus is an R package for annotation, analysis and visualization of circRNA data. Users can annotate their circRNA candidates with host genes, gene features they are spliced from, and discriminate between known and yet unknown splice junctions. Circular-to-linear ratios of circRNAs can be calculated, and a number of descriptive plots easily generated.

ngshmmalign is a profile HMM aligner for NGS reads designed particularly for small genomes (such as those of RNA viruses like HIV-1 and HCV) that experience substantial biological insertions and deletions.

CGAT-core is a set of libraries and helper functions used to enable researchers to design and build computational workflows for the analysis of large-scale data-analysis.

This package has been developed under ROpenSci gudelines to integrate conventional and cutting edge cytometry analysis tools under a unified framework. It aims to represent an intuitive and interactive approach to analysing cytometry data in R.

Bio++ is a set of C++ libraries for Bioinformatics, including sequence analysis, phylogenetics, molecular evolution and population genetics. This library provides sequence-related modules.

This package provides basic routines for estimation of gene-specific transcriptional derivatives and visualization of the resulting velocity patterns.

This is a package that lets you process UMI-4C data from scratch to produce nice plots.

PiGx SARS-CoV-2 is a pipeline for analysing data from sequenced wastewater samples and identifying given variants-of-concern of SARS-CoV-2. The pipeline can be used for continuous sampling. The output report will provide an intuitive visual overview about the development of variant abundance over time and location.

This package contains a multicore Barnes-Hut implementation of the t-SNE algorithm. The implementation is described here: http://lvdmaaten.github.io/publications/papers/JMLR_2014.pdf.

This package infers, visualizes and analyzes the cell-cell communication networks from scRNA-seq data.

Presto is a python toolkit for processing raw reads from high-throughput sequencing of B cell and T cell repertoires.

Vembrane simultaneously filters variants based on any INFO or FORMAT field, CHROM, POS, ID, REF, ALT, QUAL, FILTER, and the annotation field ANN. When filtering based on ANN, annotation entries are filtered first. If no annotation entry remains, the entire variant is deleted.

DelayedArray based image operations.

Fxtract extracts sequences from a protein or nucleotide fastx (FASTA or FASTQ) file given a subsequence. It uses a simple substring search for basic tasks but can change to using POSIX regular expressions, PCRE, hash lookups or multi-pattern searching as required. By default fxtract looks in the sequence of each record but can also be told to look in the header, comment or quality sections.

This is package for including transposable elements in differential enrichment analysis of sequencing datasets. TEtranscripts and TEcount take RNA-seq (and similar data) and annotates reads to both genes and transposable elements. TEtranscripts then performs differential analysis using DESeq2. Note that TEtranscripts and TEcount rely on specially curated GTF files, which are not included due to their size.

This is a collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using R.

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.