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      • Creating and Analyzing a Project
        • Creating a New Project
        • The Metadata Tab
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        • Importing a GEO / ENA project
      • Bulk RNA-Seq
        • Importing the tutorial data set
        • Adding sample attributes
        • Running pre-alignment QA/QC
        • Trimming bases and filtering reads
        • Aligning to a reference genome
        • Running post-alignment QA/QC
        • Quantifying to an annotation model
        • Filtering features
        • Normalizing counts
        • Exploring the data set with PCA
        • Performing differential expression analysis with DESeq2
        • Viewing DESeq2 results and creating a gene list
        • Viewing a dot plot for a gene
        • Visualizing gene expression in Chromosome view
        • Generating a hierarchical clustering heatmap
        • Performing biological interpretation
        • Saving and running a pipeline
      • Analyzing Single Cell RNA-Seq Data
      • Analyzing CITE-Seq Data
        • Importing Feature Barcoding Data
        • Data Processing
        • Dimensionality Reduction and Clustering
        • Classifying Cells
        • Differentially Expressed Proteins and Genes
      • 10x Genomics Visium Spatial Data Analysis
        • Start with pre-processed Space Ranger output files
        • Start with 10x Genomics Visium fastq files
        • Spatial data analysis steps
        • View tissue images
      • 10x Genomics Xenium Data Analysis
        • Import 10x Genomics Xenium Analyzer output
        • Process Xenium data
        • Perform Exploratory analysis
        • Make comparisons using Compute biomarkers and Biological interpretation
      • Single Cell RNA-Seq Analysis (Multiple Samples)
        • Getting started with the tutorial data set
        • Classify cells from multiple samples using t-SNE
        • Compare expression between cell types with multiple samples
      • Analyzing Single Cell ATAC-Seq data
      • Analyzing Illumina Infinium Methylation array data
      • NanoString CosMx Tutorial
        • Importing CosMx data
        • QA/QC, data processing, and dimension reduction
        • Cell typing
        • Classify subpopulations & differential expression analysis
    • User Manual
      • Interface
      • Importing Data
        • SFTP File Transfer Instructions
        • Import single cell data
        • Importing 10x Genomics Matrix Files
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        • Partek Flow Uploader for Ion Torrent
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        • Import a GEO / ENA project
      • Task Menu
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        • QA/QC
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        • Pre-alignment tools
          • Trim bases
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          • Filter alignments
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        • Annotation/Metadata
          • Annotate cells
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        • Filtering
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          • DESeq2(R) vs DESeq2
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          • Transcript Expression Analysis - Cuffdiff
          • Troubleshooting
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        • Exploratory Analysis
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        • Trajectory Analysis
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        • Variant Callers
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        • Variant Analysis
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          • Annotate Variants
          • Annotate Variants (SnpEff)
          • Annotate Variants (VEP)
          • Filter Variants
          • Summarize Cohort Mutations
          • Combine Variants
        • Copy Number Analysis (CNVkit)
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          • Promoter sum matrix
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        • Export
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      • Data Viewer
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        • Chromosome View
          • Launching the Chromosome View
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          • Visualizing the Results Using Data Tracks
          • Annotating the Results
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        • Dot Plot
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        • Transcription Start Site (TSS) Plot
        • Sources of variation plot
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      • Pipelines
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            • Adding a Reference Sequence
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      • How to select the best single cell quality control thresholds
      • Cellular Differentiation Using Trajectory Analysis & Single Cell RNA-Seq Data
      • Spatial transcriptomics—what’s the big deal and why you should do it
      • Detecting differential gene expression in single cell RNA-Seq analysis
      • Batch remover for single cell data
      • How to perform single cell RNA sequencing: exploratory analysis
      • Single Cell Multiomics Analysis: Strategies for Integration
      • Pathway Analysis: ANOVA vs. Enrichment Analysis
      • Studying Immunotherapy with Multiomics: Simultaneous Measurement of Gene and Protein
      • How to Integrate ChIP-Seq and RNA-Seq Data
      • Enjoy Responsibly!
      • To Boldly Go…
      • Get to Know Your Cell
      • Aliens Among Us: How I Analyzed Non-Model Organism Data in Partek Flow
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    • Release Notes
      • Release Notes Archive - Partek Flow 10
  • Partek Genomics Suite
    • Installation Guide
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      • Lists
        • Importing a text file list
        • Adding annotations to a gene list
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        • Starting with a list of genomic regions
        • Starting with a list of SNPs
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      • Annotation
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        • Implementation Details
        • Configuring the GO ANOVA Dialog
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      • Visualizing NGS Data
      • Chromosome View
      • Methylation Workflows
      • Trio/Duo Analysis
      • Association Analysis
      • LOH detection with an allele ratio spreadsheet
      • Import data from Agilent feature extraction software
      • Illumina GenomeStudio Plugin
        • Import gene expression data
        • Import Genotype Data
        • Export CNV data to Illumina GenomeStudio using Partek report plug-in
        • Import data from Illumina GenomeStudio using Partek plug-in
        • Export methylation data to Illumina GenomeStudio using Partek report plug-in
    • Tutorials
      • Gene Expression Analysis
        • Importing Affymetrix CEL files
        • Adding sample information
        • Exploring gene expression data
        • Identifying differentially expressed genes using ANOVA
        • Creating gene lists from ANOVA results
        • Performing hierarchical clustering
        • Adding gene annotations
      • Gene Expression Analysis with Batch Effects
        • Importing the data set
        • Adding an annotation link
        • Exploring the data set with PCA
        • Detect differentially expressed genes with ANOVA
        • Removing batch effects
        • Creating a gene list using the Venn Diagram
        • Hierarchical clustering using a gene list
        • GO enrichment using a gene list
      • Differential Methylation Analysis
        • Import and normalize methylation data
        • Annotate samples
        • Perform data quality analysis and quality control
        • Detect differentially methylated loci
        • Create a marker list
        • Filter loci with the interactive filter
        • Obtain methylation signatures
        • Visualize methylation at each locus
        • Perform gene set and pathway analysis
        • Detect differentially methylated CpG islands
        • Optional: Add UCSC CpG island annotations
        • Optional: Use MethylationEPIC for CNV analysis
        • Optional: Import a Partek Project from Genome Studio
      • Partek Pathway
        • Performing pathway enrichment
        • Analyzing pathway enrichment in Partek Genomics Suite
        • Analyzing pathway enrichment in Partek Pathway
      • Gene Ontology Enrichment
        • Open a zipped project
        • Perform GO enrichment analysis
      • RNA-Seq Analysis
        • Importing aligned reads
        • Adding sample attributes
        • RNA-Seq mRNA quantification
        • Detecting differential expression in RNA-Seq data
        • Creating a gene list with advanced options
        • Visualizing mapped reads with Chromosome View
        • Visualizing differential isoform expression
        • Gene Ontology (GO) Enrichment
        • Analyzing the unexplained regions spreadsheet
      • ChIP-Seq Analysis
        • Importing ChIP-Seq data
        • Quality control for ChIP-Seq samples
        • Detecting peaks and enriched regions in ChIP-Seq data
        • Creating a list of enriched regions
        • Identifying novel and known motifs
        • Finding nearest genomic features
        • Visualizing reads and enriched regions
      • Survival Analysis
        • Kaplan-Meier Survival Analysis
        • Cox Regression Analysis
      • Model Selection Tool
      • Copy Number Analysis
        • Importing Copy Number Data
        • Exploring the data with PCA
        • Creating Copy Number from Allele Intensities
        • Detecting regions with copy number variation
        • Creating a list of regions
        • Finding genes with copy number variation
        • Optional: Additional options for annotating regions
        • Optional: GC wave correction for Affymetrix CEL files
        • Optional: Integrating copy number with LOH and AsCN
      • Loss of Heterozygosity
      • Allele Specific Copy Number
      • Gene Expression - Aging Study
      • miRNA Expression and Integration with Gene Expression
        • Analyze differentially expressed miRNAs
        • Integrate miRNA and Gene Expression data
      • Promoter Tiling Array
      • Human Exon Array
        • Importing Human Exon Array
        • Gene-level Analysis of Exon Array
        • Alt-Splicing Analysis of Exon Array
      • NCBI GEO Importer
    • Webinars
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      • Allele Intensity Import
      • Allele-Specific Copy Number
      • Calculating Genotype Likelihoods
      • ChIP-Seq Peak Detection
      • Detect Regions of Significance
      • Genomic Segmentation
      • Loss of Heterozygosity Analysis
      • Motif Discovery Methods
      • Partek Genomics Suite Security
      • Reads in RNA-Seq
      • RNA-Seq Methods
      • Unpaired Copy Number Estimation
    • Release Notes
    • Version Updates
    • TeamViewer Instructions
  • Getting Help
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On this page
  • How to create a project?
  • Can I change my user avatar?
  • How do I add and use my own lists?
  • Can I repeat a task and everything downstream of it, while changing only one/a few parameters?
  • What can I use to identify cells that are actively expressing genes within a gene list?
  • Can I build and use pipelines for my analysis?
  • How do I classify cells?
  • My server is full, how do I make more space?
  • How do I add library files if I am not studying human or mouse?
  • Are Genome coordinates 1-based or 0-based?
  • Can I add transgenes to my reference files?
  • How do I export data from the result nodes?
  • Why can’t I find the RPKM method on the normalization menu (I see FPKM)?
  • Why don't you have RPM in your normalization?
  • What is a canonical transcript?
  • Why are there decimal values in the Partek E/M quantification output?
  • Why is the number of variants listed in the variant reports and summarize cohort mutations report different?
  • How long is data retained for expired Partek Flow subscriptions?

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  1. Partek Flow
  2. Frequently Asked Questions

General

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Last updated 1 month ago

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How to create a project?

To create a project, you first need to , and then import the files into your project using the import data wizard, here is the video and more information.

Can I change my user avatar?

Yes, navigate to My profile and click the "Change image" button. Do this by clicking your avatar at the top right corner of the interface, select Settings, then choose Profile.

How do I add and use my own lists?

Click your avatar in the top right corner of the Partek Flow interface, choose Settings in the menu, and select Lists from the left panel of the Components section. Lists can also be generated from result tables using the "Save as managed list" button. For more information please click here.

Can I repeat a task and everything downstream of it, while changing only one/a few parameters?

Yes, click on the rectangular task that you want to change the parameters. On the context-specific menu on the right, under Task actions, select ā€˜Rerun with downstream tasks’, this will bring you to the task set up page where you can edit the parameters for the task, then click Finish to run the task with the new parameters. The tasks downstream of it will be initiated automatically.

What can I use to identify cells that are actively expressing genes within a gene list?

Use AUCell to identify cells with active gene sets; this task calculates a value for each cell by ranking all genes by their expression level in the cell and identifying what proportion of the genes from the gene list fall within the top 5% (default cutoff) of genes. An alternative option is to use the Gene score for a feature list to select and filter populations based on the distribution; click here for more information.

Can I build and use pipelines for my analysis?

Yes, click on Import a pipeline on the bottom of the Analyses tab dashboard. This will help you import either our hosted pipelines or your own saved pipeline which can be found under Settings -> Components -> Pipelines. Click here for steps to save and run a pipeline. For more information related to navigating pipelines click here.

How do I classify cells?

Classification in Partek Flow can be performed manually or with automatic cell classification which is explained in more detail here. Users often want to classify cells by gene expression threshold(s), for details on classification by marker expression click here. Automatic classification needs to be performed on a non-normalized single cell data node; once complete, publish cell attributes to project then use this classification in visualizations and tasks. You may choose to perform Graph-based clustering and K-means clustering to help identify biomarkers that can then be used to identify the clusters and we also provide hosted lists for different cell types.

My server is full, how do I make more space?

We recommend cleaning up projects as well as removing library files that you do not need, then removing the orphaned files. You can also export analyzed projects and save them on an external machine, then when you need them again you can import them to the server. Please see this information for more details related to: Project management, Removing library files, and Orphaned files. Right click on the data node to delete files from projects that are not needed (e.g. fastqs from project pipelines that are analyzed); you will not be able to perform tasks from this node once the files are deleted.

How do I add library files if I am not studying human or mouse?

To add a new assembly, click on Settings -> Library files. From the Assembly drop-down list, select Add assembly and specify the species. If the species name is not in the list, choose Other and type in the name with the assembly version (multiple assembly versions can exist for one species, e.g. hg19 and hg38 for Homo Sapiens). You need to add the reference file which is a .fasta file containing sequence information. Once the reference file is added, you can build any aligner index to perform the alignment task.

The Annotation model is a file containing feature location. This file can be used to quantify to annotation model in RNA-Seq analysis, or annotate variant or peaks in a DNA-Seq or ATAC-Seq/ChIP-Seq data analysis pipeline. The file format should be .gtf/.gff/.bed.

We recommend looking for the species files on the Ensembl website. There is no need to unzip or save these files to your local machine, instead right click and copy the link address of the specific file (not a link to a folder). For more details, here is the documentation chapter: Library File Management - PartekĀ® Documentation.

Are Genome coordinates 1-based or 0-based?

Genome coordinates for annotation models stored in Partek Flow are 1-based, start-inclusive, and stop-exclusive. This means that the first base position starts from one, the start coordinate for a feature is included in the feature and the stop/end coordinate is not included in the feature. These are the genome coordinates that are printed in various task reports and output files when an annotation model is involved in the task. When custom annotation files are added to Partek Flow, the genome coordinates are converted into this format. The coordinates are converted back if necessary for a specific task. shows how the genome coordinates vary between different annotation formats.

Can I add transgenes to my reference files?

Yes, to add transgenes (including gfp or related) to the references files, first choose an assembly, create the transgene reference, and merge the references together (e.g. combine mm10 with dttomato). This is the same process for the annotation file.

How do I export data from the result nodes?

Why can’t I find the RPKM method on the normalization menu (I see FPKM)?

When working with paired data it should be the case that FPKM is available, and when working with single end data RPKM should be available. These metrics are essentially analogous, but based on the underlying method used for calculation (accounting for two reads mapping to 1 fragment and not counting twice for paired end data). Here is a simple description of the differences in calculation between RPKM and FPKM: http://www.rna-seqblog.com/rpkm-fpkm-and-tpm-clearly-explained.

Why don't you have RPM in your normalization?

RPM (reads per million) is the same as Total Count. Please use Total Count.

What is a canonical transcript?

For genes with multiple transcripts, one of the transcripts is picked as the canonical transcript. Based on the UCSC definition from the table browser,

knownCanonical - identifies the canonical isoform of each cluster ID, or gene. Generally, this is the longest isoform.

we define the canonical transcript as either the longest CDS (coding DNA sequence) if the gene has translated transcripts, or the longest cDNA.

Why are there decimal values in the Partek E/M quantification output?

The Partek E/M quantification algorithm can give decimal values because of multi-mapping reads (the same read potentially aligning to multiple locations) and overlapping transcripts/genes (a read that maps to a location with multiple transcripts or genes at that location). In these scenarios, the read count will be split.

For example, if a read maps to two potential locations, then that read contributes 0.5 counts to the first location and 0.5 counts to the second location. Similarly, if a read maps to one location with two overlapping genes, then that read contributes 0.5 counts to the first gene and 0.5 counts to the second gene.

If you need to remove the decimal points for downstream analysis outside of Partek Flow, you can round the values to the nearest integer.

Why is the number of variants listed in the variant reports and summarize cohort mutations report different?

For variants with multiple alternative alleles, the variant has one row for all alternative alleles, while the summarize cohort mutations report lists each alternative allele on a separate rows. The number of variants listed at the top of the each report is calculated from the number of rows in the report.

How long is data retained for expired Partek Flow subscriptions?

Partek Flow data is retained for one year after the subscription expires. We recommend exporting your projects and data to your local machine prior to letting the subscription expire.

Left click to select the data node you want to export. In the bottom of the task menu there will be an option to .

transfer files to the Partek Flow server
Download data