Partek® Flow® pipelines make analysis of next generation sequencing data easy and efficient. Our support scientists have validated the pipelines featured on this page for optimal performance. Feel free to download them and use in Partek Flow 3.0 or later versions to analyze your data.
Follow these step-by-step instructions to import pre-built pipelines to your installation of Partek Flow.
Pipeline for Ion AmpliSeq™ Transcriptome Human Gene Expression Research Panel for quantification, normalization and differential gene expression. This pipeline works with aligned reads coming from the Torrent Suite Software and the samples properly grouped with attributes in the Data tab. When running the pipeline, please choose the Assembly: Homo sapiens (human) - Ampliseq and Gene/feature annotation: AmpliSeq Transcriptome as the annotation model on the first step of the pipeline. You will also be asked to define the factors and the contrasts for statistical analysis.
This pipeline generates unaligned reads data node from BAM files. It also has post and pre-alignment QAQC. This pipeline may be particularly useful for users getting their data in the BAM file format. After the pipeline, it will have an unaligned data node that can be realigned using the different aligners in Partek Flow.
Convert Ion Torrent Data in the unaligned bam (UBAM) format to FASTQ then do pre-alignment QAQC. Ion Torrent Data can be in the unaligned bam (UBAM) file format. Since most data analysis is done in the FASTQ format, these files can be converted to FASTQ using this pipeline. This pipeline will show up if the selected data node is an unaligned BAM data node. Once it is converted to FASTQ, it can be aligned using various aligners available in Partek Flow or it can be fed to another pipeline.
RNA-Seq pipeline that takes into account the strand orientation preserved by Illumina TruSeq Stranded RNA library prep kits. Aligns reads to a reference genome using the STAR aligner, quantifies reads to a transcriptome, filters out low-expressing transcripts and normalizes the data.
Filters your data and removes reads that map to known ribosomal RNA and mitochondrial DNA sequences. This pipeline will work if the correct reference sequence is provided. For human, mouse, and rat genomes, you can use the reference sequence provided here (obtained from the Ensemble database): https://s3.amazonaws.com/PartekLibraryFiles/miRNA/Homo_sapiens.GRCh38.84.mtDNA_rRNA.fa https://s3.amazonaws.com/PartekLibraryFiles/miRNA/Mus_musculus.GRCm38.84.mtDNA_rRNA.fa https://s3.amazonaws.com/PartekLibraryFiles/miRNA/Rattus_norvegicus.Rnor_6.0.84.mtDNA_rRNA.fa