General
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To create a project, you first need to , and then import the files into your project using the import data wizard, here is the and .
Yes, navigate to and click the "Change image" button. Do this by clicking your avatar at the top right corner of the interface, select , then choose .
Click your avatar in the top right corner of the Partek Flow interface, choose in the menu, and select from the left panel of the section. Lists can also be generated from result tables using the "Save as managed list" button. For more information please click .
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 ‘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.
Use 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; .
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.
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.
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.
RPM (reads per million) is the same as Total Count. Please use Total Count.
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.
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.
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.
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.
Yes, click on on the bottom of the tab dashboard. This will help you import either our hosted pipelines or your own saved pipeline which can be found under -> -> . Click for steps to save and run a pipeline. For more information related to navigating pipelines click .
Classification in Partek Flow can be performed manually or with automatic cell classification which is explained in more detail . Users often want to classify cells by gene expression threshold(s), for details on classification by marker expression click . Automatic classification needs to be performed on a non-normalized single cell data node; once complete, then use this classification in visualizations and tasks. You may choose to perform and to help identify biomarkers that can then be used to identify the clusters and we also provide hosted lists for different cell types.
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: , , and . 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.
To add a new assembly, click on -> . 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.
We recommend looking for the species files on the 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: .
Left click to select the data node you want to export. In the bottom of the task menu there will be an option to .
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: .
