baSeq docs › FASTQ files (Reads)

FASTQ files (Reads)

An analysis starts from counts. FASTQ files are counted first, in Reads on the Data page; the counts then open as a single-cell analysis for 10x Genomics data, or as a bulk analysis.

1. Open Reads

FASTQ files do not go on the start screen of an analysis, or in the upload area of the Datasets tab: both take counts, and both stop when you drop reads there. Open Data in the left menu, then Reads at the top right of the page.

The Data page, with Data outlined in the left menu and Reads outlined at the top right — Data in the left menu, then Reads at the top right.

Data outlined in the left menu — 1. Data, in the left menu.

Reads outlined between Datasets and Facility inboxes — 2. Reads, at the top right of the Data page.

If there is no Reads on your Data page, write to [email protected] and we switch it on for your account.

2. Drop the folder of FASTQ files

On the Reads tab, drop the folder that holds the FASTQ files on Drop a folder of FASTQ files, or press Choose a folder. Send the folder as your sequencing facility or 10x Genomics delivered it:

Every lane of every sample, paired or single reads, as .fastq.gz or .fq.gz. The samples are read from the file names, for example pbmc_1k_v3_S1_L001_R1_001.fastq.gz.
Index reads (I1, I2) can stay in the folder; they are set aside.
Add a sample sheet (.csv or .tsv) to the folder if you have one.

The run is named after the folder, unless you type a name under Name first. Keep the page open while the files upload. If the connection drops, open the run from the list on the Reads tab and it picks up where it stopped.

The Reads tab with the Drop a folder of FASTQ files area and the Choose a folder button outlined — The Reads tab. Drop the folder on the outlined area, or press Choose a folder.

Keep your own copy of the FASTQ files

baSeq deletes the FASTQ and BAM files 30 days after counting and never backs them up. You get a reminder email a week before. The counts, the quality report and the methods are kept and backed up.

3. Choose the organism and run the pre-flight

When the files are in, the run's page opens. Choose the organism under The reads are from and press Choose. The pre-flight runs with it unless you untick Run the pre-flight too: a look at each sample's first reads that takes from a few seconds to a few minutes.

10x Genomics data is recognised from the cell barcodes in read 1, and the pre-flight names the kit (3′ v2, v3 or v3.1, or v4). You do not choose it.
Bulk RNA-seq is checked for the species, the strand, the sex of each sample and its share of ribosomal RNA.

Anything worth a look before counting is listed on the page, with what you can do about it.

A run's page after the pre-flight: 1 sample of human cells, 10x 3′ v3 or v3.1, ready to count — A 10x run after its pre-flight. The kit was told from the barcodes: 95% of them are on 10x's v3 list.

4. Start counting

Tick I keep my own copy of the FASTQ files and press Start counting. You can close the page: baSeq emails you when the run is counted. Counting takes from minutes to a few hours, depending on the number of reads.

The tick box I keep my own copy of the FASTQ files, above the Start counting button — Tick the box, then Start counting.

A 10x sample is counted per cell with STARsolo, with the settings that match Cell Ranger: the cell barcodes are matched to 10x's list, reads are counted on exons and introns as Cell Ranger 7 does, and the cells are told from the empty droplets as Cell Ranger does. A bulk sample is trimmed, aligned and counted per gene, with a MultiQC quality report.

5. Start the analysis

When the run is counted, press Start a single-cell analysis (for 10x data) or Start a bulk analysis. The counts become a dataset on the Datasets tab and its page opens: press Analyse, choose the Project, and press Start analysis. The analysis opens with the samples to review, as after any upload.

A counted 10x run: 1 sample, 1,267 cells, with Start a single-cell analysis outlined — A counted 10x run, with the quality of each sample. The methods paragraph, ready to paste, is further down the page.

What Reads counts

Data	Counted
10x Genomics single-cell, 3′ gene expression (v2, v3, v3.1, v4)	Per cell, with STARsolo, into a single-cell dataset
Bulk RNA-seq, whole transcript or 3′ tag-seq (such as QuantSeq), with or without UMIs	Per gene, into a bulk dataset

Reads counts human reads against GRCh38 (GENCODE 50) and mouse reads against GRCm39 (GENCODE M39). 10x 5′, Multiome and Flex runs are not counted yet.

The quality of a 10x run

Each sample's row holds the numbers Cell Ranger's summary shows, so you can compare them with a run of your own.

Column	What it is
Cells	The barcodes told apart from empty droplets as cells.
Median genes	The genes found in the median cell.
Median UMIs	The molecules counted in the median cell.
Reads per cell	The sample's reads divided by its cells.
Saturation	The share of reads from molecules already seen. High saturation means that more sequencing would find few new molecules.
Valid barcodes	The share of reads whose cell barcode is on 10x's list.
Reads in cells	The share of the counted reads that come from cells rather than empty droplets.