README.txt for AALS Mapping File
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OVERVIEW:

This document provides guidance and explanations for the accompanying mapping file designed to track and map vital information related to biological samples. The file contains several columns, each dedicated to specific details about the sample's identification, processing, storage, and logistics. The following sections detail the purpose and content of each column within the file.
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COLUMNS DESCRIPTION:

1. Participant ID: A unique identifier for the individual from whom the sample was obtained. This ID links the sample to the participant in a way that protects the individual's privacy.
2. Sample ID: A unique identifier assigned to the sample. This ID facilitates tracking the sample through its lifecycle, from collection to analysis.
3. GUID-Batch: A composite identifier combining a Globally Unique Identifier (GUID) with a batch number, aimed at improving the traceability of sample batches.
4. GUID: The Globally Unique Identifier is provided to ensure each sample's unique and unequivocal identification across all studies and databases.
5. Cell Line: Identifies the cell line the sample was derived from. This information is necessary for research involving cell culture and experimentation.
6. Batch #: The number assigned to a specific batch of samples differentiated together. Batch numbers aid in managing quality control and traceability.
7. Vial ID: The unique identification code for each vial containing a sample.  This information is necessary for precise sample identification and handling.
8. Site: Indicates the location where the sample is/was sent for analysis.
9. Shipment: Contains details regarding the shipment of samples. Samples are sent in groups of batches, typically 3 batches per shipment, and this column identifies the sequence and grouping of samples sent out.
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USAGE:

- The mapping file is designed for data analysis researchers, lab technicians, and logistics personnel involved with biological samples' collection, processing, analysis, and storage. It serves as a comprehensive tool for maintaining detailed records, ensuring each sample's traceability, and supporting quality control throughout various research phases.

Suggested ways to use the Sample Mapping File in Data Analysis
1. Pre-processing Step: Before starting the analysis, use the sample mapping file to categorize your data according to the batch number. This involves segregating the cell line differentiation samples based on their batch and identifying the corresponding batch control samples.

2. Normalization and Correction: Utilize statistical methods or software tools that are designed to adjust for batch effects. Methods such as ComBat (from the sva package in R) or Limma (also in R) can be applied, using the batch information from your mapping file to correct the data. The goal is to minimize the differences between batches that are not related to the biological variables of interest.

3. Quality Control: Use the mapping file to perform quality control checks. For example, ensure that batch controls behave as expected across different batches. Any inconsistency in control samples might indicate a problem with the batch effect correction process.

4. Data Analysis: Proceed with the analysis (e.g., differential expression analysis, clustering, or pathway analysis) after batch effect correction. The corrected dataset should reflect true biological variations rather than artifacts introduced by batch effects.

5. Validation and Interpretation: Finally, validate your findings by checking if the observed patterns or differences remain consistent across batches after correction. This step is crucial to confirm that the results are biologically meaningful and not influenced by batch-related variations.

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BATCH CONTROLS USING CTRL-NEUEU392AE8:

Please note that we have many samples mapped to CTRL-NEUEU392AE8. 
1. All CTRL-NEUEU392AE8 samples labelled “BTC” or "BTC2" in col “Batch #” are the Batch Technical Controls for the experiment.
- 2AE8iCTR-n6 line served as BTC and was produced in bulk Oct-Dec 2018. The same clone was used for bulk differentiation BTC2 in June-July 2021. Each OMICs lab receives a BTC or BTC2 pellet from these differentiations with each shipment to run with all the other vials in the shipment. This controls for ‘Omics assay-specific variability’; since BTC pellets were produced simultaneously with an SOP, a given assay should return the same results for any BTC pellet.
2. All CTRL-NEUEU392AE8 samples with an integer value in col “Batch #” are the Batch Differentiation Controls (BDC)
- 2AE8iCTR-n6 line is also differentiated with every group of differentiations. This controls for inter-batch variability in differentiation. This line is thawed, expanded, differentiated, and pelleted in addition to the ALS/CTR lines in each batch. Each OMICs lab receives a BDC pellet and ALS/CTR pellets for each differentiation batch.
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END OF README.txt