MUSIC is an algorithm for identification of enriched regions at multiple scales in the read depth signals from ChIP-Seq experiments.

bustools is a program for manipulating BUS files for single cell RNA-Seq datasets. It can be used to error correct barcodes, collapse UMIs, produce gene count or transcript compatibility count matrices, and is useful for many other tasks.

CodeAndRoll2 is a set of more than 130 productivity functions. These functions are used by MarkdownReports, ggExpress, and SeuratUtils.

dnaio is a Python library for fast parsing of FASTQ and also FASTA files. The code was previously part of the cutadapt tool.

This package provides tools for handling BAM, SAM, Tabix, bgzf, CRAM, CSIv1, CSIv2 and FAI files.

This package provides a lightweight interface to Stan <https://mc-stan.org>. The CmdStanR interface is an alternative to RStan that calls the command line interface for compilation and running algorithms instead of interfacing with C++ via Rcpp'.

This package provides an accurate VCF/GFF3/GTF LiftOver tool for new genome assemblies.

MultiQC is a tool to aggregate bioinformatics results across many samples into a single report. It contains modules for a large number of common bioinformatics tools.

FastTree can handle alignments with up to a million of sequences in a reasonable amount of time and memory. For large alignments, FastTree is 100-1,000 times faster than PhyML 3.0 or RAxML 7.

PiGx is a collection of genomics pipelines. It includes the following pipelines:

• PiGx BSseq for raw fastq read data of bisulfite experiments

• PiGx RNAseq for RNAseq samples

• PiGx scRNAseq for single cell dropseq analysis

• PiGx ChIPseq for reads from ChIPseq experiments

All pipelines are easily configured with a simple sample sheet and a descriptive settings file. The result is a set of comprehensive, interactive HTML reports with interesting findings about your samples.

This package provides a Python package for reading raw fcs files

RSeQC provides a number of modules that can comprehensively evaluate high throughput sequence data, especially RNA-seq data. Some basic modules inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while RNA-seq specific modules evaluate sequencing saturation, mapped reads distribution, coverage uniformity, strand specificity, etc.

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.

CD-HIT is a program for clustering and comparing protein or nucleotide sequences. CD-HIT is designed to be fast and handle extremely large databases.

Ngs-bits (Next-Generation Sequencing) is collection of short-read and long-read sequencing tools for diagnostics.

CPAT is a method to distinguish coding and noncoding RNA by using a logistic regression model based on four pure sequence-based, linguistic features: ORF size, ORF coverage, Ficket TESTCODE, and Hexamer usage bias. Linguistic features based method does not require other genomes or protein databases to perform alignment and is more robust. Because it is alignment-free, it runs much faster and also easier to use.

Bioinformaticians often have to convert sequence files between formats and do little manipulations on them, and it's not worth writing scripts for that. Seqmagick is a utility to expose the file format conversion in BioPython in a convenient way. Instead of having a big mess of scripts, there is one that takes arguments.

PAIRADISE is a method for detecting allele-specific alternative splicing (ASAS) from RNA-seq data. Unlike conventional approaches that detect ASAS events one sample at a time, PAIRADISE aggregates ASAS signals across multiple individuals in a population. By treating the two alleles of an individual as paired, and multiple individuals sharing a heterozygous SNP as replicates, PAIRADISE formulates ASAS detection as a statistical problem for identifying differential alternative splicing from RNA-seq data with paired replicates.

This is a package providing efficient operations for single cell ATAC-seq fragments and RNA counts matrices. It is interoperable with standard file formats, and introduces efficient bit-packed formats that allow large storage savings and increased read speeds.

This package provides a deconvolution based on Single Nucleotide Position (SNP) for multiplexed scRNA-seq data. The name vireo stand for Variational Inference for Reconstructing Ensemble Origin by expressed SNPs in multiplexed scRNA-seq data and follows the clone identification from single-cell data named cardelino.

Exonerate is a generic tool for pairwise sequence comparison. It allows the alignment of sequences using a many alignment models, either exhaustive dynamic programming or a variety of heuristics.

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

This program searches for and removes remnant adapter sequences from High-Throughput Sequencing (HTS) data and (optionally) trims low quality bases from the 3' end of reads following adapter removal. AdapterRemoval can analyze both single end and paired end data, and can be used to merge overlapping paired-ended reads into (longer) consensus sequences. Additionally, the AdapterRemoval may be used to recover a consensus adapter sequence for paired-ended data, for which this information is not available.

Trinity assembles transcript sequences from Illumina RNA-Seq data. Trinity represents a novel method for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data. Trinity combines three independent software modules: Inchworm, Chrysalis, and Butterfly, applied sequentially to process large volumes of RNA-seq reads. Trinity partitions the sequence data into many individual de Bruijn graphs, each representing the transcriptional complexity at a given gene or locus, and then processes each graph independently to extract full-length splicing isoforms and to tease apart transcripts derived from paralogous genes.