Running the Create ArchRProject workflow

Jen Garbarino
22 steps
2 minutes

Latch

This workflow is intended to be used after clustering parameters were selected in optimize archR. this workflow only uses one set of clustering parameters and does peak calling as well as motif enrichment. It creates many more outputs and figures for downstream analysis.

Click on the workflows button in LatchBio to go to the workflows tab

Click on the create ArchRProject workflow

To add your sample click add a row

Enter the Run_id here

Run_id should not have any spaces and cannot start with or be a single number. This needs to be a unique identifier for every sample in the project

If you have an additional name for the sample, input it here

Next associate the fragments file for this Run_id

To find the fragment file in LatchBio, click select file. Navigate to the fragment files and click "Select".

Service run fragment files will be located in the Raw_Data folder.

Enter Condition if applicable to samples. You can leave this blank.

No spaces allowed within condition. If you have two conditions you can separate with a dash (dash cannot be used within condition). example: "post_treatment-non_resonder" will give you two conditions: post_treatment and non-responder. "post treatment-non-responder" will lead to errors.

Next we will input the location of the spatial directory. This folder is generated by AtlasXbrowser and is needed to connect the data to the imaging done of the sample.

Click "Select Folder"\ Navigate to the location of the spatial folders. Select the folder called spatial within the Run_ID labelled folder

We also will associate the position file for the sample here. This file determines where on the image the data is located and which datapoints contain tissue and should be included in the analysis.

Click "tissue_positions_list.csv" to specify the tissue position list within the folder and click "Select".

For additional samples click add a row and follow the above steps to add their information

Set genome for experiment (mm10-mouse, hg38-human) contact AtlasXomics if you need an additional reference genomes added

Enter a project name to call this workflow execution. Project name cannot contain spaces and will be the name of the output folder for this execution.

The next few parameters are able be optimized in our optimize archR workflow to prevent multiple runnings of create archRProject

LSI (Latent Semantic Indexing) resolution helps determine how the points in UMAP space are distributed. This is from a scale of 0-1 with lower numbers being more conservative.

LSI varFeatures is how many variable features from the sample are being used for the cluserting. 25,000 is our standard value but you can use more or less features here to add in more information or reduce noise respectively. We typically try 15,000 for lower input samples or 50,000 for higher input samples.

Clustering resolution dictates which regions of the UMAP are called different clusters. The UMAP will not change but how many regions it identifies within it is determined here. This is on a scale of 0-1 with 1 maximizing the amount of clusters identified.

For additional filtering options click "Hidden Parameters"

This workflow defaults to filtering out points with a TSS less than 2. To raise or lower this cutoff you can change this field.

This workflow defaults to having no minimum fragments count per point. If you would like to increase this to remove low count regions, edit this field.

When you have finished adding all the parametrs click launch workflow. You will be taken to the execution page where you can track the progress of your workflow.

Running the Create ArchRProject workflow

Jen Garbarino
22 steps
2 minutes