• Binaries for Linux/macOS
• From sources for Linux/macOS
• From sources for Windows

Address of the bookmark: https://github.com/imgag/ngs-bits

Tool link:

http://www.cs.cmu.edu/~ckingsf/software/sailfish/

Address of the bookmark: http://www.genengnews.com/gen-news-highlights/lightweight-algorithms-sail-through-rna-sequencing-data/81249765/

ORLANDO, USA, Oct 17, 2017/ PRNewswire/

Strand NGS now supports large scale RNA- and small-RNA-Seq and Unique Molecular Identifiers (UMIs) for DNA-, RNA-, and small-RNA-Seq.

Strand Life Sciences announced the latest version release of its bioinformatics flagship product, Strand NGS, at the Annual Meeting of the American Society of Human Genetics today. Two major themes in Strand NGS v3.1 address recent challenges in next generation sequencing (NGS).

The first theme is large-scale RNA-Seq data analysis. Current cross-cohort RNA- and small-RNA-Seq studies span tens of replicates and batches across hundreds of samples, sometimes conducted across several different institutions. For such studies, Strand NGS v3.1 includes confounding variable analysis to eliminate technical effects, including batch effects; the t-SNE plot; profile and heat-map plots of gene-body coverage; and several other notable visual enhancements.

The second new feature is support for Unique Molecular Identifiers, or UMIs, for DNA-, RNA- and small-RNA-Seq. UMI support in Strand NGS is end-to-end, spanning alignment to variant calling in DNA-Seq, and alignment to quantification in RNA- and small-RNA-Seq. The Bioo Scientific, Qiagen, and Rubicon UMI protocols are natively supported, and an intuitive interface allows the specification of custom UMI protocols.

“For liquid biopsies and low-grade FFPE samples, UMI support in DNA-Seq enables the detection of somatic variants at low concentrations. In RNA-Seq, large-scale and UMI support can be used in single-cell-based studies that reveal tumor-cell heterogeneity, even at low concentrations”, says Dr. Vamsi Veeramachaneni, Chief Scientific Officer, Strand Life Sciences.

“At Strand, we are continuously working towards improving the accuracy and efficiency of NGS data analysis. Customers can look forward to Strand NGS becoming available on the cloud in the near future”, says Dr. Ramesh Hariharan, Chief Executive Officer, Strand Life Sciences.

Visit Strand Life Sciences at ASHG booth #1017 to know more about Strand NGS v3.1 and other products and service offerings from Strand Life Sciences. Click here to access detailed agenda and v3.1 release notes.

About Strand Life Sciences

Strand Life Sciences is a premier life science informatics innovation company. Founded in 2000, Strand is a leader in technology innovations for healthcare using genomics. By enhancing sequence-based diagnostics and clinical genomic data interpretation using a strong foundation of computational, scientific, and medical expertise, Strand is bringing individualized medicine to the world. To know more, visit www.strandls.com

Address of the bookmark: http://www.strand-ngs.com/strand-announce-strandngss-v31

Speaker: Dr. Satish Sankaran, Vice President and Lab Director - Clinical Operations & Clinical Lab, Strand Life Sciences Pvt Ltd

Abstract: Next Generation sequencing has come a long way in aiding genetic disease diagnosis by bringing down both the time and cost of testing. Testing involves massively parallel sequencing of a single to 100s of genes in a one assay. With a large amount of sequence data getting generated from such assays, it is critical that the data is analyzed using standard analysis tools to detect wide range of variants. Strand Life Sciences, has tested more than 3000 clinical samples using multi-gene panels for diagnosis of rare disease conditions. NGS data analysis is done using the Strand NGS software and variant prioritization and reporting using StrandOMICS.

While most analysis software can easily detect single nucleotide variants, the complex ones involving insertions and deletions are usually missed. With multiple iterations the Strand NGS software is trained to effectively detect structural and copy number changes from a single NGS data set. This is critical in certain disease conditions like Retinoblastoma and Duchenne’s Muscular Dystrophy where there are clinically relevant deletions reported.

In this presentation, we present four different case studies where we were able to detect mutations due to unusual and difficult regions in the genome from the NGS data. These results were further confirmed using orthologous methods.

Session 1: 31 Jan 2018; 9:00 AM CET
Session 2: 31 Jan 2018; 8:00 AM PST

Register at http://www.strand-ngs.com/webinar_registration

Cleaning your data in this way is often required: Reads from small-RNA sequencing contain the 3’ sequencing adapter because the read is longer than the molecule that is sequenced. Amplicon reads start with a primer sequence. Poly-A tails are useful for pulling out RNA from your sample, but often you don’t want them to be in your reads.

Cutadapt helps with these trimming tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Also, paired-end reads and even colorspace data is supported. If you want, you can also just demultiplex your input data, without removing adapter sequences at all.

Cutadapt comes with an extensive suite of automated tests and is available under the terms of the MIT license.

If you use cutadapt, please cite DOI:10.14806/ej.17.1.200 .

Address of the bookmark: https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart

Address of the bookmark: https://github.com/vice87/gam-ngs

Address of the bookmark: https://github.com/clwgg/nQuireunder