--normalizeTo1x: 按照1x测序深度(reads per genome coverage, RPGC)进行标准化 --ignoreForNormalization: 指定那些染色体不需要经过标准化 如果需要以100为分箱,并且标准化到1x,且仅统计某一条染色体区域的正链,输出格式为 bedgraph,那么命令行可以这样写 bamCoverage -e 170 -bs 100 -of bedgraph -r Chr4...
https://deeptools.readthedocs.io/en/develop/content/installation.html 此工具将读取BAM文件，并生成bigWig或bedGraph。覆盖率计算为每个bin的读取次数，bin为定义的连续读取的窗口大小。bamCoverage通过RPKM，CPM，BPM ，1x，RPGC等方法提供标准化。较小的bin大小用于更高的分辨率，将覆盖范围标准化为1x...
--normalizeTo1x: 按照1x测序深度(reads per genome coverage, RPGC)进行标准化 --ignoreForNormalization: 指定那些染色体不需要经过标准化 如果需要以100为分箱,并且标准化到1x,且仅统计某一条染色体区域的正链,输出格式为bedgraph,那么命令行可以这样写 bamCoverage -e 170 -bs 100 -of bedgraph -r Chr4:1...
--normalizeTo1x: 按照1x测序深度(reads per genome coverage, RPGC)进行标准化 --ignoreForNormalization: 指定那些染色体不需要经过标准化 如果需要以100为分箱,并且标准化到1x,且仅统计某一条染色体区域的正链,输出格式为bedgraph,那么命令行可以这样写 bamCoverage-e170-bs100-of bedgraph -r Chr4:12985884:...
以下是ChIP-seq 数据转换的一个示例用法 -b, --bam ： 输入的bam文件 -o ：输出的bw文件 -bs, --binSize ：分割的bin size --normalizeUsing ：每个bins中read counts的校正单位，可以从 RPKM , CPM , BPM , RPM , RPGC 中选择 --effectiveGenomeSize ：可比对基因组区域的大小（bp...
bamCoverage --binSize 10 --smoothLength 30 -p 4 --normalizeUsing RPGC --effectiveGenomeSize 2150570000 --extendReads $fragLength -b $file1 -of bigwig -o raw.10x30.bw file2=/home/da528/ATAC_Analysis/cut_run/zhixin_analysis/downsampling_bam/Exp1/AD3_H3K27Ac_2_CKDL220009611-1a_HN37...
.. argparse:: :ref: deeptools.bamCoverage.parseArguments :prog: bamCoverage Usage hints A smaller bin size value will result in a higher resolution of the coverage track but also in a larger file size. The 1x normalization (RPGC) requires the input of a value for the effective genome ...
--scoreFileNameFILENAMEbigWigfile with the scores to be visualized. BigWig files can be obtained by using thebamCoverageorbamComparetools. only forscale-regionsmode: | Command | Expected Input | Explanation | |:---:|:---:|:---| | --regionBodyLength | INTEGER | Distance in bp to wh...
$ conda install-c bioconda deeptools conda 安装 $ conda install-c bioconda deeptools bamCoverage 介绍 image 此工具将读取BAM文件,并生成bigWig或bedGraph。覆盖率计算为每个bin的读取次数,bin为定义的连续读取的窗口大小。bamCoverage通过RPKM,CPM,BPM ,1x,RPGC等方法提供标准化。
可以自行设定覆盖度计算的窗口大小(bin);bamCoverage 内置了各种标准化方法:scaling factor, Reads Per Kilobase per Million mapped reads (RPKM), counts per million (CPM), bins per million mapped reads (BPM) and 1x depth (reads per genome coverage, RPGC)....