# AMP0002_DeepSeq_no_group_4_FS_80

# Run Summary

Summary | Value
--- | ---
Run ID | AMP0002_DeepSeq_no_group_4_FS_80
Genome Assembly | mus_musculus_GRCm38.114
# Plates Detected | 1
# Groups | 1
# Reference Group | Group_A
# Total Wells Processed | 192
# Excluded Wells (empty FASTQs) | 0
# Cells (Before QC) | 192
# Cells (After QC) | 163
% Cells Filtered Out | 15.1 %
Seurat Version | 5.1.0
R Version | R version 4.2.3 (2023-03-15)
Analysis Date | 2026-05-01

# Introduction

This file contains an overview of the results from AMP0002_DeepSeq_no_group_4_FS_80.

Whenever possible we compare the reference group to the other groups using a two-sided Wilcoxon rank sum test. Only P-values inferior to 0.05 are displayed and encoded as follows:

- p-value < 0.05: “*”
- p-value < 0.01: “**”
- p-value < 0.001: “***”
- p-value < 0.0001: “****”

# QC Filtering

Before any downstream analysis, the dataset undergoes a quality-control (QC) filtering step. Only cells satisfying the filtering criteria listed below are retained for all subsequent plots, summaries and statistical tests shown in this report.

This means that all analyses in the following sections are performed exclusively on the filtered dataset.

## Filtering criteria

A cell is considered high quality and kept only if all of the following requirements are met:

- Raw reads > 100k
- Uniquely mapped reads > 75k
- Unmapped due to short reads < 25%
- The corresponding well is not flagged as excluded in the sample sheet (excludedWell == FALSE)

If no cells pass QC, downstream sections depending on filtered data are automatically skipped and a warning is displayed.

# Raw Reads

Number of raw reads per cell.

A uniform distribution of the reads between cells is expected when following the standard FLASH-seq protocol.

# Raw Reads - Plate View

Drop outs originating from FACS sorting issues are often characterized by a low number of associated reads.

# Mapping Stats

From STAR mapping statistics.

Uniquely Mapped reads: Reads associated to a single position in the reference genome. Multimapped reads: Reads mapping at multiple positions onto the reference. Unmapped reads: Reads that do not map to the reference genome or present a too high number of multimapped positions.

The percentage of uniquely mapped reads can vary between cell types. Good quality cells typically display values >70%.

# Sequencing Depth Saturation

Warning

Downsampling was not computed because no `_ft.down.txt` files were found.

# Read Distribution

The read distribution between 3’/5’UTR, exonic coding sequence, intronic and intergenic regions are estimated using RSeQC. Read tag percentages are displayed.

The majority of the reads will be distributed between CDS exon and intronic categories.

# Mitochondrial Genes

Warning

Downsampling was not computed because no `_ft.down.txt` files were found.

# Gene-body Coverage

Distribution of the reads along the gene-body. As a full length protocol, FLASH-seq produces uniform distribution from 5’ to 3’.

Estimated using RSeQC.

# Population Overview

First glance at the single-cell populations. This analysis is provided for reference only. Due to its automated nature, we highly recommend fine-tuning the parameters before annotating your cell populations.

## Filtering

Cells are considered as outliers and filtered out of the population analysis if they don’t meet the following criteria:

- Mitochondria reads: 0.1%-10%
- Number of detected genes: >1000 and <(median + 2x median absolute deviation)
- Number of associated reads (exonic): median +/- 3x median absolute deviation

## Clustering

Cell populations are identified following the standard Seurat (V5) pipeline. Briefly, the data are log-normalized and then rescaled, regressing out the read counts.

The top 2000 most variable features are extracted using ‘vst’ function and used to run a principal component analysis. The number of dimensions is chosen as follows:

- Number of principal components (PCs) that explain >80% of the variability
- Number of PCs where the variance drop between two consecutive PCs is >0.25%

Both metrics are compared and the smallest number of PCs is selected. These dimensions are used to cluster cells into groups (shared nearest neighbor) and to display the results (UMAP).

## Feature Distribution

## Markers

Wilcoxon-test — LogFC > |1| — minimal population expression > 0.5 — Bonferroni correction for multiple testing.

Only genes with adjusted p-values < 0.05 are displayed.

# Drop-out Rate

Percentage of cells that did not pass the QC filtering criteria described in the QC Filtering section.

These cells are considered low quality based on:

- Insufficient raw reads
- High percentage of unmapped reads
- Low number of uniquely mapped reads