Strand NGS Software is an integrated platform that provides analysis, management and visualization tools for next-generation sequencing data. The raw sample data can be imported for alignment in FASTA, FASTQ, Unaligned BAM, or tag-count format. In addition, pre-aligned data in SAM, BAM or Illumina-specific ELAND format can be directly imported for analysis. The software supports the following major NGS experiment workflows like Alignment, RNA-Seq Analysis, DNA-Seq Analysis, ChIP-Seq Analysis, Methyl-Seq Analysis, MeDIP-Seq Analysis, and Small RNA-Seq Analysis.
Strand NGS provides support for aligning reads to a genome for small RNA reads, DNA reads (for ChIP-Seq and DNA-Seq applications), and RNA reads (spliced and unspliced reads) from sequencing platforms like Illumina, Ion Torrent, ABI, 454(Roche), and Pac Bio. The Strand NGS aligner, uses a new proprietary algorithm based on the Burrows Wheeler Transform and Smith Waterman dynamic programming. Other alignment algorithms are often limited to either a specific class of reads or alignment characteristics. Strand NGS aligner, however, has been optimized to handle both short reads and long reads, allows an arbitrary number of gaps and mismatches, and handles both single and paired end reads.Various quality inspection options including pre-alignment, post-alignment, vendor-specific, and library QC plots along with multiple filtering steps ensure that any poor quality data is kept out of the analysis.
Transcriptome data can be visualized and analyzed using the RNA-Seq workflow in Strand NGS. In addition to classical differential gene expression analysis, Strand NGS can be used to find alternatively spliced genes to discover novel genes and exons, and to identify novel splice junctions. In many disorders like cancer, the genetic make-up of a cell is changed in such a profound way, that genes fuse together, resulting in a hybrid protein with potentially devastating effects on the cell – these gene fusions can also be discovered by Strand NGS. Learn more
Strand NGS supports expression analysis of various small RNA species, supports detection of novel small RNA genes, and their classification. After quantification of reads, identify differentially expressed small RNA genes, and visualize the results in a small RNA-specific gene view. The miRNA targets of interesting small RNA genes can be predicted using multiple target prediction databases like TargetScan, PicTar, TarBase, microRNA.org, and PITA.Learn more
Strand NGS supports the DNA-Seq workflow for detecting small variations including SNPs, MNPs, and InDels (DIPs) from whole genome, whole exome, targeted Re-sequencing and amplicon panel data. These variants, of both homozygous and heterozygous kinds, can be annotated with information from dbSNP to identify known and novel variants. In addition, the effect of these variants on transcripts can be assessed, resulting in classifications such as non-synonymous coding SNP or frameshift InDel. Larger structural variations, including large insertions, deletions, inversions, and translocations, can be detected for experiments that use paired-end, mate-paired and split read data. In addition, copy number variations can be detected in samples using tumor-normal pairs or using a reference coverage profile. Learn more
The ChIP-Seq analysis workflow supports identification of transcription factor binding sites and histone modification, by using peak detection algorithms such as PICS and MACS. For transcription factors, this can be followed up by looking for potential motifs in these peak regions, by using the GADEM motif-detection algorithm. The genes close to the detected peaks can be identified as good candidates for transcription factor regulation. Learn more
Strand NGS supports analysis and visualization of bisulfite treated methyl-seq data – from whole genome or targeted experiments. Within this workflow detect methylation in individual samples and identify differentially methylated cytosines across samples /target regions and also study methylation effects at the genic level. Further downstream analysis such as GO and pathway analysis can be performed on the set of affected genes.Learn more
Strand NGS supports genome-wide methylation analysis using MeDIP-Seq data. The workflow supports data normalization before estimating the methylation signal and identifies differential methylation events across a pair of conditions. These regions can be further annotated based on their location with respect to known genes. Downstream analysis such as GO, pathway analysis can be performed on selected entities.Learn more
Strand NGS provides custom visualizations to verify analysis results from the workflows above, including a feature-rich embedded Genome Browser. Strand NGS comes pre-packaged with annotations for several standard organisms and supports the ability to create annotations for other organisms. Gene and transcript annotations from multiple sources like UCSC, Ensembl, RefSeq are supported. Genes identified by any of the workflow steps above can be subject to biological interpretation and discovery using steps such as Gene Ontology enrichment, GSEA, NLP derived interaction network analysis and significant pathways analysis.
• Gene, exon and transcript 
• Detect SNPs, MNPs and 
• Detect peaks using PICS 
Details for standalone and concurrent licenses are available on request. Software support is available around-the-clock by phone and email. Training and services can be provided for diverse research requirements.
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