В этом примере показано, как считать функции от чтений секвенирования парного конца после выравнивания их к целому геному человека курировавшими Консорциумом Ссылки Генома. Этот пример использует Консорциальную Сборку Человека Ссылки Генома 38 релизов 12 (GRCh38.p12) закрашенной фигуры в качестве ссылки генома человека.
Этот пример работает над UNIX® и платформами Mac только. Загрузите Интерфейс Bioinformatics Toolbox™ для пакета поддержки Выравнивателя Галстука-бабочки из Add-On Explorer. Для получения дополнительной информации смотрите Пакеты Программной поддержки Bioinformatics Toolbox.
Этот пример принимает, что вы имеете:
Загруженный и извлеченный блок RefSeq из Консорциальной Сборки Человека Ссылки Генома 38 релизов 12 (GRCh38.p12) закрашенной фигуры.
Загруженный и организованный некоторый парный конец считывает данные. Этот пример использует exome секвенирование данных из этих 1 000 проектов геномов. Чтения парного конца обозначаются '_1' и '_2' в именах файлов.
Создайте индекс для выравнивания чтений к ссылке с помощью bowtie2build. Файл GCF_000001405.38_GRCh38.p12_genomic.fna содержит человеческий ссылочный геном в формате FASTA. bowtieIdx базовое имя файлов справочного указателя. '--threads 8' опция задает количество параллельных потоков, чтобы создать индексные файлы быстрее. Вы не должны задавать полные пути к файлам для *.fna или *.index файлов, если вы запускаете пример от того же местоположения папки. Задайте полные пути, если вы хотите хранить файлы в другом месте или запустить пример от другой папки.
bowtieIdx = 'GCF_000001405.38_GRCh38.p12_genomic.index'; buildFlag = bowtie2build('GCF_000001405.38_GRCh38.p12_genomic.fna',... bowtieIdx,'--threads 8');
Выровняйте чтения парного конца к ссылке с помощью bowtie2. Можно создать Bowtie2AlignOptions объект задать различные варианты, такие как количество параллельных потоков, чтобы использовать.
opt = Bowtie2AlignOptions; opt.NumThreads = 8; reads1 = 'HG00096_1.fastq'; reads2 = 'HG00096_2.fastq'; bowtie2(bowtieIdx,reads1,reads2,'HG00096.sam',opt);
Файлы SAM могут быть очень большими. Используйте BioMap выбрать только данные для правильной ссылки. В данном примере рассмотрите APOE, который является геном на Хромосоме 19 соединенных к болезни Альцгеймера. Создайте меньший файл BAM для APOE, чтобы улучшать производительность.
apoeRef = 'NC_000019.10'; % Reference name for Chromosome 19 in HG38 bm = BioMap('HG00096.sam','SelectReference',apoeRef); write(bm, 'HG00096.bam','Format','bam');
Warning: Found invalid tag in header type: 'PG'. Ignoring tag 'PN:bowtie2'. Warning: The read sequences in input SAM file do not appear to be ordered according to the start position of their alignments with the reference sequence. Because of this, there will be a decrease in performance when accessing the reads. For maximum performance, order the read sequences in the SAM file, before creating a BioMap object.
Используйте featurecount сравнить количество расшифровок стенограммы для каждого варианта APOE с помощью файла GTF. Полная таблица функций включена в блок GRCh38.p12 в формате GFF, который может быть преобразован в GTF с помощью cuffgffread. Этот пример использует упрощенный GTF на основе расшифровок стенограммы APOE. APOE_gene.gtf включен с программным обеспечением.
[FeatTable, Summary] = featurecount('APOE_gene.gtf','HG00096.bam',... 'Metafeature','transcript_id');
Processing GTF file APOE_gene.gtf ... Processing BAM file HG00096.bam ... Processing reference NC_000019.10 ... 10000 reads processed ... 20000 reads processed ... 30000 reads processed ... 40000 reads processed ... 50000 reads processed ... 60000 reads processed ... 70000 reads processed ... 80000 reads processed ... 90000 reads processed ... 100000 reads processed ... 110000 reads processed ... 120000 reads processed ... 130000 reads processed ... 140000 reads processed ... 150000 reads processed ... 160000 reads processed ... 170000 reads processed ... 180000 reads processed ... 190000 reads processed ... 200000 reads processed ... 210000 reads processed ... 220000 reads processed ... 230000 reads processed ... 240000 reads processed ... 250000 reads processed ... 260000 reads processed ... 270000 reads processed ... 280000 reads processed ... 290000 reads processed ... 300000 reads processed ... 310000 reads processed ... 320000 reads processed ... 330000 reads processed ... 340000 reads processed ... 350000 reads processed ... 360000 reads processed ... 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Done.
bamsort | samsort | bwamem | bowtie2 | bowtie2build | featurecount | BioMap | cuffgffread | cufflinks
