This package provides several programs that perform operations on SAM/BAM files. All of these programs are built into a single executable called bam.

Collectively, the bedtools utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable genome arithmetic: that is, set theory on the genome. For example, bedtools allows one to intersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF.

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.

Sailfish is a tool for genomic transcript quantification from RNA-seq data. It requires a set of target transcripts (either from a reference or de-novo assembly) to quantify. All you need to run sailfish is a fasta file containing your reference transcripts and a (set of) fasta/fastq file(s) containing your reads.

This package provides a library and collection of scripts to work with Illumina paired-end data (for CASAVA 1.8+).

The FASTX-Toolkit is a collection of command line tools for Short-Reads FASTA/FASTQ files preprocessing.

Next-Generation sequencing machines usually produce FASTA or FASTQ files, containing multiple short-reads sequences. The main processing of such FASTA/FASTQ files is mapping the sequences to reference genomes. However, it is sometimes more productive to preprocess the files before mapping the sequences to the genome---manipulating the sequences to produce better mapping results. The FASTX-Toolkit tools perform some of these preprocessing tasks.

This package provides bioinformatic tools to align, deduplicate, reformat, filter and normalize DNA and RNA-seq data. It includes the following tools: BBMap, a short read aligner for DNA and RNA-seq data; BBNorm, a kmer-based error-correction and normalization tool; Dedupe, a tool to simplify assemblies by removing duplicate or contained subsequences that share a target percent identity; Reformat, to convert reads between fasta/fastq/scarf/fasta+qual/sam, interleaved/paired, and ASCII-33/64, at over 500 MB/s; and BBDuk, a tool to filter, trim, or mask reads with kmer matches to an artifact/contaminant file.

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 provides a robust, parallelized Python CLI for annotating three prime UTR.

An ORF caller finds stretches of DNA that, when translated, are not interrupted by stop codons. OrfM finds and prints these ORFs.

The wavefront alignment (WFA) algorithm is an exact gap-affine algorithm that takes advantage of homologous regions between the sequences to accelerate the alignment process.

This package provides version 1.12 of the HTSlib C library for high-throughput sequence analysis. The package is primarily useful to developers of other R packages who wish to make use of HTSlib.

Taxtastic is software written in python used to build and maintain reference packages i.e. collections of reference trees, reference alignments, profiles, and associated taxonomic information.

GEMMA provides a standard linear mixed model resolver with application in GWAS.

Picard is a set of Java command line tools for manipulating high-throughput sequencing (HTS) data and formats. Picard is implemented using the HTSJDK Java library to support accessing file formats that are commonly used for high-throughput sequencing data such as SAM, BAM, CRAM and VCF.

Millefy is a tool for visualizing read coverage of scRNA-seq(single-cell RNA sequencing) datasets in genomic contexts. By dynamically and automatically reorder single cells based on locus-specific pseudo time, Millefy highlights cell-to-cell heterogeneity in read coverage of scRNA-seq data.

This package implements bindings for zarr store that are compatible with Bioconductor S4 data structures, namely the DataFrame and DelayedArray. This allows Zarr-backed data to be easily used as data frames with arbitrary sets of columns.

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.

PRINSEQ is a bioinformatics tool to help you preprocess your genomic or metagenomic sequence data in FASTA or FASTQ formats. The tool is written in Perl and can be helpful if you want to filter, reformat, or trim your sequence data. It also generates basic statistics for your sequences.

randfold computes the probability that, for a given sequence, the Minimum Free Energy (MFE) of the secondary structure is different from MFE computed with random sequences.

This package provides necessary tools for the analysis of the genomic interaction data stored in .cool format. This collection of tools includes operations like compartment, insulation or peak calling.

Samtools implements various utilities for post-processing nucleotide sequence alignments in the SAM, BAM, and CRAM formats, including indexing, variant calling (in conjunction with bcftools), and a simple alignment viewer.

METAL is a tool for meta-analysis genomewide association scans. METAL can combine either test statistics and standard errors or p-values across studies (taking sample size and direction of effect into account). METAL analysis is a convenient alternative to a direct analysis of merged data from multiple studies. It is especially appropriate when data from the individual studies cannot be analyzed together because of differences in ethnicity, phenotype distribution, gender or constraints in sharing of individual level data imposed. Meta-analysis results in little or no loss of efficiency compared to analysis of a combined dataset including data from all individual studies.

This package provides accelerated functions for the CIRI toolkit. It also provides the ccs executable to scan for circular consensus sequences.