可以在feature (如exon) 或meta-feature (如gene) 水平上定量; 在计算多重映射和多重重叠reads方面具有高度灵活性; 自动检测输入格式 (SAM或BAM); 自动对paired-end reads进行排序; …… 2. 输入数据 featureCounts的输入数据包括: SAM或BAM格式的一个或多个aligned reads文件; 基因组特征列表【Gene Transfer Fo...
选择gtf中提供的id identifier!!!-t<string># 设置feature-type,-t指定的必须是gtf中有的feature,同时read只有落到这些feature上才会被统计到,默认是“exon”-p # 只能用在paired-end的情况中,会统计fragment而不统计read-B# 在-p选择的条件下,只有两端read都比对上的fragment才会被统计-C# 如果-C被设置,那融...
-D < int >#最长的fragmen,默认是600 -f# 如果-f被设置,那将会统计feature层面的数据,如exon-level,否则会统计meta-feature层面的数据,如gene-levels 四、软件运行命令 nohup featureCounts -T 5 -p -t exon -g transcript_id \ -a ~/lncRNA_project/07.identification/step5/filter5_by_nr.gtf \ -o...
feature指的是基因组区间的最小单位,比如exon; 而metafeature可以看做是许多的feature构成的区间,比如属于同一个gene的外显子的组合。 在定量的时候,支持对单个feature定量(对外显子定量), 也支持对meta-feature进行定量(对基因进行定量)。 当reads 比对到2个或者以上的features 时,默认情况下,featureCounts在统计时...
-f 如果-f被设置,那将会统计feature层面的数据,如exon-level,否则会统计meta-feature层面的数据,如gene-levels -g < string > 当参考的gtf提供的时候,我们需要提供一个id identifier 来将feature水平的统计汇总为meta-feature水平的统计,默认为gene_id,注意!选择gtf中提供的id identifier!!! -t < string > 设...
It can count reads at feature (eg. exon) or meta-feature (eg. gene) level(也可以基于外显子定量) Highly flexible in counting multi-mapping and multi-overlapping reads. Such reads can be excluded, fully counted or fractionally counted(这点跟HTSeq-count不一样了,其对于多重比对的reads并不是采...
五、软件使用: 基本表达式 featureCounts [options] 参数说明 使用示例: $ /home/software/subread-2.0.2-Linux-x86_64/bin/featureCounts -T 5 -t exon -g gene_id -a/path-to-gtf/ERCC.gtf-o /path-to-output/all.id.txt*.bam1>counts.id.log 2>&1 链接:https:/...
• It supports GTF and SAF format annotation • It supports strand-specific read counting • It can count reads at feature (eg. exon) or meta-feature (eg. gene) level • Highly flexible in counting multi-mapping and multioverlapping reads. Such reads can be excluded, fully counted ...
I routinely summarize at both the gene and exon level using featureCounts (using -g 'gene_id' or 'exon_id'). This results in separate summary files (gene_counts.summary and exon_counts.summary) and MultiQC appears to only recognize one of those 2 files. Is there currently support for ...
Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or...