Loading report..

Highlight Samples

Regex mode off

    Rename Samples

    Click here for bulk input.

    Paste two columns of a tab-delimited table here (eg. from Excel).

    First column should be the old name, second column the new name.

    Regex mode off

      Show / Hide Samples

      Regex mode off

        Explain with AI

        Configure AI settings to get explanations of plots and data in this report.

        Keys entered here will be stored in your browser's local storage. See the docs.


        Anonymize samples off

        Export Plots

        px
        px
        X

        Download the raw data used to create the plots in this report below:

        Note that additional data was saved in multiqc_data when this report was generated.


        Choose Plots

        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411
        Settings are automatically saved. You can also save named configurations below.

        Save Settings

        You can save the toolbox settings for this report to the browser or as a file.


        Load Settings

        Choose a saved report profile from the browser or load from a file:

          Load from File

        Tool Citations

        Please remember to cite the tools that you use in your analysis.

        To help with this, you can download publication details of the tools mentioned in this report:

        About MultiQC

        This report was generated using MultiQC, version 1.27.1

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/MultiQC/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2025-03-28, 14:45 CET based on data in:
        • /scratch/siebrenf/lore4/qc/general_stats.tsv
        • /scratch/siebrenf/lore4/qc/reads_per_step.tsv
        • /scratch/siebrenf/lore4/qc/skera.tsv
        • /scratch/siebrenf/lore4/qc/lima.tsv
        • /scratch/siebrenf/lore4/qc/isoseq_correct_barcodes.tsv
        • /scratch/siebrenf/lore4/qc/isoseq_correct.tsv
        • /scratch/siebrenf/lore4/qc/isoseq_bcstats.tsv
        • /scratch/siebrenf/lore4/qc/isoseq_collapse.tsv
        • /scratch/siebrenf/lore4/qc/pigeon_classify_classifications_by_read.tsv
        • /scratch/siebrenf/lore4/qc/pigeon_classify_classifications.tsv
        • /scratch/siebrenf/lore4/qc/pigeon_classify_rt_switching.tsv
        • /scratch/siebrenf/lore4/qc/pigeon_classify_genes.tsv
        • /scratch/siebrenf/lore4/qc/pigeon_classify_filter_reasons.tsv
        • /scratch/siebrenf/lore4/qc/pigeon_classify_classifications_by_cell.tsv
        • /scratch/siebrenf/lore4/qc/pigeon_classify_classifications_by_transcript.tsv
        • /scratch/siebrenf/lore4/qc/pigeon_classify_classifications_by_isoform.tsv
        • /scratch/siebrenf/lore4/qc/pigeon_classify_classifications_by_mapping.tsv
        • /scratch/siebrenf/lore4/qc/pigeon_classify_junctions.tsv
        • /scratch/siebrenf/lore4/qc/pigeon_report.tsv
        • /scratch/siebrenf/lore4/qc/segmented.knee_mqc.png
        • /scratch/siebrenf/lore4/pbmm2/segmented.stats.tsv
        • /scratch/siebrenf/lore4/pbmm2/segmented.coverage.tsv
        • /scratch/siebrenf/lore4/pbmm2/segmented.bam.mtnucratiomtnuc.json
        • /scratch/siebrenf/lore4/qc

        General Statistics

        Showing 1/1 rows and 7/21 columns.
        Sample NameReads in cells% Reads in cellsMT genome coverageGenome coverageMT to Nuclear RatioM Genome readsM MT genome readsError rateNon-primaryReads mapped% Mapped% Proper pairs% MapQ 0 readsTotal seqsMean insertReadsBasesCoverageMean depthMean BQMean MQ
        segmented
        25.5M
        28.0%
        21562.0X
        5.2X
        4139.3
        16.0M
        0.4M
        0.47%
        0.0M
        16.2M
        99.6%
        0.0%
        8.4%
        16.3M
        0.0bp
        16.4M
        570.4Mb
        18.4%
        5.1x
        38.7
        54.9

        Reads per processing step

        The number of reads remaining after each processing step. The final reads are deduplicated and aligned to the genome/transcriptome.

        Legend:
        ccs_reads: Circular consensus sequencing (HiFi) reads (Skera)
        s_reads: Segmented reads (Skera)
        primed_reads: Primed reads (Lima)
        fl_reads: Full Length reads (Iso-seq correct)
        flnc_reads: Full Length Non-Chimeric reads (Iso-seq correct)
        polya_reads: PolyA-tailed reads (Iso-seq correct)
        non-missing: Barcoded reads (Iso-seq correct)
        yield_reads: Estimated reads in cells (Iso-seq correct).

        Created with MultiQC

        Skera

        Deconcatenates Kinnex HiFi reads to produce S-reads that represent the original cDNA molecules.

        Showing 1/1 rows and 5/5 columns.
        samplereadss_readsmean_len_s_readspercent_full_arraymean_array_size
        segmented
        6104086.0
        91323074.0
        981.0
        87.5
        15.0

        Lima

        Removes and spurious false positives.

        Showing 1/1 rows and 15/15 columns.
        sampleReads inputReads above all thresholds (A)Reads below any threshold (B) (B) Below min length (B) Below min score (B) Below min end score (B) Below min passes (B) Below min score lead (B) Below min ref span (B) Without SMRTbell adapter (B) Wrong different pair (B) Undesired 5p--5p pairs (B) Undesired 3p--3p pairs (A) With same pair (A) With different pair
        segmented
        91323074
        90692203
        630871
        12350
        0
        228466
        6
        0
        490179
        0
        0
        192404
        231319
        0
        90692203

        Iso-seq correct

        Identifies cell barcode errors and corrects them. Additionally, Iso-seq correct estimates which reads are likely to originate from real cells vs ambrient RNA.

        Stats

        Showing 1/1 rows and 10/10 columns.
        sampleprocessed_readsfiltered_readsprocessed_basesedit_read_countunchanged_read_countmissing_read_countfound_but_failing_read_countfailing_read_countyield_countyield_fraction
        segmented
        90460688.0
        0.0
        80744625524.0
        90448488.0
        4241.0
        7959.0
        64935802.0
        64943761.0
        25516927.0
        0.3

        Barcode corrections

        Created with MultiQC

        Barcode stats

        Showing 1/1 rows and 10/10 columns.
        samplenumber_unique_groupbarcodesnumber_unique_molbarcodestotal_number_readsmean_groupbarcode_depthcutoff_thresholdnumber_of_cellsmedian_umis_per_cellreads_in_cellsfraction_reads_in_cellsmean_reads_per_cell
        segmented
        1589554.0
        67814241.0
        90460688.0
        56.0
        1306.0
        13880.0
        2491.0
        57572148.0
        0.6
        4147.0

        Knee plots


        Samtools

        Version: 1.21

        Toolkit for interacting with BAM/CRAM files.URL: http://www.htslib.orgDOI: 10.1093/bioinformatics/btp352

        Percent mapped

        Alignment metrics from samtools stats; mapped vs. unmapped reads vs. reads mapped with MQ0.

        For a set of samples that have come from the same multiplexed library, similar numbers of reads for each sample are expected. Large differences in numbers might indicate issues during the library preparation process. Whilst large differences in read numbers may be controlled for in downstream processings (e.g. read count normalisation), you may wish to consider whether the read depths achieved have fallen below recommended levels depending on the applications.

        Low alignment rates could indicate contamination of samples (e.g. adapter sequences), low sequencing quality or other artefacts. These can be further investigated in the sequence level QC (e.g. from FastQC).

        Reads mapped with MQ0 often indicate that the reads are ambiguously mapped to multiple locations in the reference sequence. This can be due to repetitive regions in the genome, the presence of alternative contigs in the reference, or due to reads that are too short to be uniquely mapped. These reads are often filtered out in downstream analyses.

        Created with MultiQC

        Alignment stats

        This module parses the output from samtools stats. All numbers in millions.

        Created with MultiQC

        Coverage: global stats

        Stats parsed from samtools coverage output, and summarized (added up or weighted-averaged) across all regions.

        Showing 1/1 rows and 6/6 columns.
        Sample NameReadsBasesCoverageMean depthMean BQMean MQ
        segmented
        16.4M
        570.4Mb
        18.4%
        5.1x
        38.7
        54.9

        Coverage: stats per region

        Per-region stats parsed from samtools coverage output.

        Created with MultiQC

        Iso-seq collapse

        Collapses redundant transcripts into unique isoforms based on exonic structures.

        Showing 1/1 rows and 2/2 columns.
        samplenumber_mapped_unique_isoformsnumber_of_mapped_unique_loci
        segmented
        367493
        66670

        Pigeon Classify

        Pigeon is used to classify isoforms into categories, filter this output, and to report on the gene and isoform- level saturation.

        Classifications overview

        Showing 2/2 rows and 5/5 columns.
        SampleInputPassedRemovedUnique genesUnique transcripts
        segmented
        367145
        None
        None
        194323
        334597
        segmented (filtered)
        367145
        99229
        267916
        18466
        73051

        Classifications by read

        Showing 2/2 rows and 9/9 columns.
        SampleFull splice matchIncomplete splice matchNovel in catalogNovel not in catalogAntisenseGenic intronGenic genomicIntergenicOther
        segmented
        281708
        277377
        43298
        87264
        69017
        642
        214816
        631518
        2711
        segmented (filtered)
        272569
        178479
        41068
        35980
        2359
        0
        1211
        4518
        1514

        Classifications by isoform

        Showing 2/2 rows and 9/9 columns.
        SampleFull splice matchIncomplete splice matchNovel in catalogNovel not in catalogAntisenseGenic intronGenic genomicIntergenicOther
        segmented
        23132
        40877
        19057
        45211
        23068
        139
        48061
        166177
        1423
        segmented (filtered)
        22714
        32325
        18155
        19999
        1490
        0
        725
        2969
        852

        Classifications by cell

        Showing 2/2 rows and 4/4 columns.
        Samplemedian_genes_per_cellmedian_transcripts_per_cellmedian_genes_per_cell_knownmedian_transcripts_per_cell_known
        segmented
        205.0
        210.0
        117.0
        70.0
        segmented (filtered)
        76.0
        78.0
        75.0
        64.0

        Classifications by transcript

        Showing 2/2 rows and 4/4 columns.
        Sampletranscripts_fsmtranscripts_ismtranscripts_nictranscripts_nnc
        segmented
        23132.0
        40877.0
        19057.0
        45211.0
        segmented (filtered)
        22714.0
        32325.0
        18155.0
        19999.0

        Classifications by mapping

        Showing 2/2 rows and 3/3 columns.
        Sampleflnc_mapped_genomeflnc_mapped_transcriptomeflnc_mapped_transcriptome_excluding_ribomito
        segmented
        1608351.0
        689647.0
        658094.0
        segmented (filtered)
        537698.0
        528096.0
        499423.0

        Junctions

        Showing 2/2 rows and 4/4 columns.
        SampleKnown canonicalKnown non-canonicalNovel canonicalNovel non-canonical
        segmented
        643342
        1966
        54047
        50036
        segmented (filtered)
        525443
        42
        39918
        0

        Genes

        Showing 2/2 rows and 2/2 columns.
        SampleKnownNovel
        segmented
        18477
        175846
        segmented (filtered)
        14336
        4130

        RT Switching

        Showing 2/2 rows and 4/4 columns.
        SampleAll transcriptsUnique transcriptsAll junctionsUnique junctions
        segmented
        16546
        1034
        17283
        17283
        segmented (filtered)
        None
        None
        None
        None

        Filter reasons

        Showing 2/2 rows and 4/4 columns.
        SampleIntraprimingMonoexonicRT switchingLow coverage/non-canonical
        segmented
        None
        None
        None
        None
        segmented (filtered)
        23330
        0
        14550
        230036

        Saturation reports

        Gene and isoform- level saturation. The tables show the number of unique genes found in a subsampled number of reads.

        Created with MultiQC

        Software Versions

        Software Versions lists versions of software tools extracted from file contents.

        SoftwareVersion
        Samtools1.21
        mtnucratio0.7.1