1 - 36 of 36 results

SAMtools

star_border star_border star_border star_border star_border
star star star star star
(5)
Allows users to interact with high-throughput sequencing data. SAMtools permits the manipulation of alignments in the SAM/BAM/CRAM formats: reading, writing, editing, indexing, viewing and converting SAM/BAM/CRAM format. It limits the mapping quality of reads with excessive mismatches and applies base alignment quality to fix alignment errors. This tool can sort and merge alignments, remove polymerase chain reaction (PCR) duplicates or generate per-position information.

Picard

star_border star_border star_border star_border star_border
star star star star star
(1)
Assists users in manipulating high-throughput sequencing (HTS) data and formats. Picard is a Java toolkit that provides a set of command line scripts. It comprises Java-based utilities that manipulate SAM files, and a Java API for creating new programs that reads and writes SAM files. Both SAM text format and SAM binary (BAM) format are supported. It also works with next generation sequencing (NGS).

Octopus-toolkit

New
Examines epigenomic and transcriptomic next generation sequencing (NGS) data. Octopus-toolkit can be used for antibody- or enzyme-mediated experiments and studies for the quantification of gene expression. It can accelerate the data mining of public epigenomic and transcriptomic NGS data for basic biomedical research. This tool provides a private and a public mode: one to process the user’s own data, and the other to analyze public NGS data by retrieving raw files from the GEO database.

UMI-tools / Unique Molecular Identifiers-tools

Demonstrates the value of properly accounting for errors in unique molecular identifiers (UMIs). UMI-tools removes PCR duplicates and implements a number of different UMI deduplication schemes. It can extract, remove and append UMI sequences from fastq reads. Compared with previous method, this one is superior at estimating the true number of unique molecules. The simulations provide an insight into the impact on quantification accuracy and indicate that application of an error-aware method is even more important with higher sequencing depth.

TRAPLINE / Transparent Reproducible and Automated PipeLINE

Obsolete
Serves for RNAseq data processing, evaluation and prediction. TRAPLINE guides researchers through the NGS data analysis process in a transparent and automated state-of-the-art pipeline. It can detect protein-protein interactions (PPIs), miRNA targets and alternatively splicing variants or promoter enriched sites. This tool includes different modules for several functions: (1) it scans the list of differentially expressed genes; (2) it includes modules for miRNA target prediction; and (3) a module is implemented to identify verified interactions between proteins of significantly upregulated and downregulated mRNAs.

RNA-Rocket

Obsolete
A free service that provides access to RNA-Seq and ChIP-Seq analysis tools for studying infectious diseases. The site makes available thousands of pre-indexed genomes, their annotations, and the ability to stream results to the bioinformatics resources VectorBase, EuPathDB, and PATRIC. The site also provides a combination of experimental data and metadata, examples of pre-computed analysis, step-by-step guides, and a user interface designed to enable both novice and experienced users of RNA-Seq data.

G-CNV / GPU-copy number variation

A graphics processing unit (GPU)-based tool for preparing data to detect copy number variations (CNVs) with read-depth methods. G-CNV can be used to (i) filter low-quality sequences, (ii) mask low-quality nucleotides, (iii) remove adapter sequences, (iv) remove duplicated reads, (v) map read sequences, (vi) remove ambiguous mappings, (vii) build the RD signal, and (viii) normalize it. Apart the task of removing adapter sequences, all the other tasks are implemented on GPU. G-CNV can be efficiently used as a third-party tool able to prepare data for the subsequent read-depth signal generation and analysis. Moreover, it can also be integrated in CNV detection tools to generate read-depth signals.

PyroTrimmer

Removes the barcodes, linkers, and primers, trims sequence regions with low quality scores, and filters out low-quality sequence reads. Although these functions have previously been implemented in other programs as well, PyroTrimmer has novelty in terms of the following features: i) more sensitive primer detection using Levenstein distance and global pairwise alignment, ii) the first stand-alone software with a graphic user interface, and iii) various options for trimming and filtering out the low-quality sequence reads.

ngscmd

A C program to manipulate next-generation sequence data files. The ngscmd program can work on a single fastQ input file, as well as mate pair files. The fastQ files can be input into the ngscmd program in either compressed or uncompressed form. Although there are many programs with functionality that is similar to ngscmd, the motivation for developing this program is that most tools exist in disparate form and many exist only as high-level scripting languages, which perform slowly.

qRNASeq script

Bioo Scientific offers a complementary qRNASeq script, which eliminates PCR duplicates from RNA-Seq data when Molecular Indexes™ or other stochastic adapters are used during library prep. Using read pairs aligned to transcripts and Fastq files, this script will generate: (i) a table listing fragments, (ii) the start/stop sites in transcripts, (iii) the molecular labels (also known as stochastic labels, or STLs), and (iv) a table listing total number of read pairs per transcript and number of read pairs after STL, USS, and STL/USS correction. This program was created by Weihong Xu from the Stanford Genome Technology Center and is supplied with a General Public License (GPL).

TRUmiCount

Removes the biases inherent in raw Unique Molecular Identifier (UMI) counts and produces unbiased and low-noise measurements of transcript abundance. In these conditions, TRUmiCount can realize comparisons between different genes, exons, and other genomic feature. This algorithm exploits the tree-step bias-correction and phantom-removal in expected read counts. In addition, TRUmiCount can thus help to increase the accuracy of many quantitative applications of Next Generation Sequencing (NGS).