1 · Choose samples
- Pick the barcode folders. From the sequencing output, use fastq_pass — drop the whole folder in and every barcode inside it becomes a sample, or drop individual barcodeNN folders.
- One folder is one sample. The folder name becomes the run name. Loose files dropped on their own are treated as a single sample.
- Check the list below. Untick anything you do not want in this batch, and set the sample name and record fields. Both can be changed after the run.
- Start runs. Upload and analysis run per sample; progress shows underneath. You can leave the page once it starts.
Accepts .fastq and .fastq.gz (also .fq), in any read orientation, up to 20 GB per sample. Output from a previous run found inside a sample folder is ignored and listed as skipped.
Sample record
Audit trail
Junction browser
Read pools
reads grouped by primer pair
Quality checks
Per-bin read counts
Differences from the reference
research use · not a result
A "possible mutation" is a difference from the reference that no
other sample here carries. It has not been confirmed and must not
be reported.
Substitutions only, inside the amplicons. This open scan does
not look for insertions or deletions. The listed ones, codon 41/42
(−TTCT) among them, are checked row by row on the
IMR panel tab. "No mutation found" means none of the kind
this looks for; a change at a position the IMR sheet lists is
always shown here, however many samples share it.
IMR targeted panel
Download .xlsx research use · not a resultEvery row of the IMR panel sheet (Coverage_Targeted LRS_panel design_IMR_coordinate.xlsx), in the sheet's own order and wording, with what this sample's control-amplicon reads say at that position. Each listed change is checked by haplotype: reads anchored across the site are compared with the reference, with the edited sequence and with every other listed change at the same site, and vote for the nearest, so one-base and 105 bp deletions are tested the same way. Fraction is mutant over mutant plus reference plus reads carrying another listed change; "other" reads (another listed change, or noise matching nothing) are shown, not dropped, and a row is only called when its mutant reads are at least 10% of all reads at the site. Beta-cluster HGVS is on the gene strand (NG_000007.3); the plus-strand edit tested is in the last column. Not assessable means too few anchored reads, which for the α2 poly A rows is structural: they sit on the HBA2 reverse primer.
Sequencing reads
Read length distribution
Reads per primer bin
Bin profile across samples
Alleles seen
What the columns mean
also on hoverSample records
Edit any cell, then save. These fields group the Summary charts. Expected result is used for the concordance check. Fields left blank stay blank; nothing is inferred.
How a breakpoint is found
All runs follow these steps. Counts on the right are from barcode85 (--THAI) and show how many reads survive each step.
All three find the same junction and are confirmed the same way. No
single method catches every allele, which is why there are three.
The Method column records which one was used.
What each method sees
One deletion, three ways it appears in the alignment. Grey is the reference, blue is where the read aligns, dashed is the deleted DNA. An inversion looks like the split case except that the second segment runs backwards.
Quality gate
Applied to every run. Thresholds derive from six samples and are provisional. Weak evidence flags a run for review; only a failed assay fails it. Thresholds can be overridden per site.
Confirmation
Every candidate junction is re-tested independently of the method that
found it. The two flanks are spliced into a synthetic
deletion-allele contig and the reads are mapped back to it. A correct
breakpoint lets reads run straight across the join; a wrong one leaves them
clipped. The join is then slid through the homology block to its
best-fitting position, which is what the Identity figure
reports. All fifteen samples reach at least 98% spanning, thirteen of them 100%.
Why the deletion is reconstructed
The contig cannot show a gap: the deleted bases are absent from it, so reads run straight through. Mapping to the reference directly shows no gap either. For −α4.2 and −α3.7 the whole amplicon aligns contiguously to one copy of the duplication, which is why those breakpoints were missed originally. The Deletion view therefore re-expresses each confirmed alignment in chr16 or chr11 coordinates, with a deletion of the called size inserted at the breakpoint. The coverage track shows it most clearly: a solid block either side, nothing between. An inversion has no such view: the span between its breakpoints is rearranged rather than absent, so only the breakpoint view is offered.
Barcode crosstalk
Index hopping leaks a few percent of one sample's reads into every other barcode on a flow cell. A leaked read carries a genuine junction and produces a plausible call, so the filter uses abundance, not junction quality. A bin below 20% of the sample's dominant diagnostic bin is rejected and reported in the per-bin table. Measured here, contamination never exceeded 9.2% of the top bin while a real allele is 100%, and spiking confirms the line: rejected at 1–15%, called at 20% and above.
What this does not tell you
Zygosity is not determined. The assay is allele-specific PCR, so read ratios carry no copy-number information. Inside a homology block the exact junction base is ambiguous: the deletion size is well determined, the coordinate is one valid representation of it.
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