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MACS:ChIP-Seq的基于模型的分析 最新发布: Github: PyPI: Bioconda: Debian Med: 介绍 随着测序技术的改进,染色质免疫沉淀后再进行高通量测序(ChIP-Seq)成为研究全基因组蛋白质-DNA相互作用的工具。 为了解决缺乏有力的ChIP-SEQ分析方法中,我们提出ÇhIP-情商的M个基于Odel等-A nalysis(MACS),用于识别转录因子结合位点。 MACS捕获基因组复杂性的影响,以评估丰富的ChIP区域的重要性,而MACS通过结合测序标签位置和方向信息来提高结合位点的空间分辨率。 MACS可以轻松地单独用于ChIP-Seq数据,也可以与特异性增加的对照样品一起使用。 此外,作为一般的峰调用者,如果要问的问题很简单:MACS可以比随机背景找到显着的读数覆盖率,那么MACS也可以应用于任何“ DNA富集测定”。 请注意,当前的M
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MACS:MACS-ChIP-Seq的基于模型的分析 (241个子文件)
CTCF_PE_ChIP_chr22_50k.bam.bai 51KB
CTCF_PE_CTRL_chr22_50k.bam.bai 37KB
tiny.bam.bai 1KB
CTCF_PE_CTRL_chr22_50k.bam 11.22MB
CTCF_PE_ChIP_chr22_50k.bam 9.05MB
tiny.bam 40KB
run_cmbreps_fisher.bdg 12.91MB
run_cmbreps_mean.bdg 12.89MB
run_callpeak_bedpe_narrow_control_lambda.bdg 10.02MB
run_callpeak_bampe_narrow_control_lambda.bdg 10.02MB
run_callpeak_bampe_broad_control_lambda.bdg 10.02MB
run_callpeak_bedpe_broad_control_lambda.bdg 10.02MB
run_pileup_ChIP.bed.bdg 9.94MB
run_cmbreps_max.bdg 7.27MB
run_callpeak_narrow2_control_lambda.bdg 6.29MB
run_callpeak_narrow3_control_lambda.bdg 6.29MB
run_bdgcmp_ppois.bdg 5.89MB
run_bdgcmp_FE.bdg 5.89MB
run_callpeak_narrow5_control_lambda.bdg 5.74MB
run_callpeak_broad_control_lambda.bdg 5.74MB
run_callpeak_narrow0_control_lambda.bdg 5.74MB
run_callpeak_narrow1_control_lambda.bdg 5.74MB
run_callpeak_pe_narrow_onlychip_control_lambda.bdg 4.19MB
run_callpeak_narrow_revert_control_lambda.bdg 3.71MB
run_callpeak_narrow_revert_treat_pileup.bdg 3.09MB
run_pileup_CTRL.bed.bdg 3.09MB
run_pileup_CTRLPE.bedpe.bdg 3.09MB
run_pileup_CTRLPE.bampe.bdg 3.09MB
run_bdgopt_max.bdg 2.84MB
run_callpeak_narrow5_treat_pileup.bdg 2.84MB
run_bdgopt_min.bdg 2.84MB
run_callpeak_broad_treat_pileup.bdg 2.84MB
run_callpeak_narrow1_treat_pileup.bdg 2.84MB
run_callpeak_narrow0_treat_pileup.bdg 2.84MB
run_pileup_ChIPPE.bedpe.bdg 2.84MB
run_pileup_ChIPPE.bampe.bdg 2.84MB
run_callpeak_bedpe_narrow_treat_pileup.bdg 2.84MB
run_callpeak_pe_narrow_onlychip_treat_pileup.bdg 2.84MB
run_callpeak_bampe_narrow_treat_pileup.bdg 2.84MB
run_callpeak_bedpe_broad_treat_pileup.bdg 2.84MB
run_callpeak_bampe_broad_treat_pileup.bdg 2.84MB
run_pileup_ChIP.bed.bdg 2.83MB
run_callpeak_narrow3_treat_pileup.bdg 2.81MB
run_callpeak_narrow4_treat_pileup.bdg 2.81MB
run_callpeak_narrow2_treat_pileup.bdg 2.77MB
run_callpeak_narrow4_control_lambda.bdg 25B
run_filterdup_result.bed 4.71MB
run_filterdup_result.bed 1.37MB
run_callpeak_narrow4_summits.bed 89KB
run_callpeak_pe_narrow_onlychip_summits.bed 58KB
run_callpeak_bedpe_narrow_summits.bed 47KB
run_callpeak_bampe_narrow_summits.bed 47KB
run_callpeak_narrow2_summits.bed 46KB
run_callpeak_narrow3_summits.bed 46KB
run_callpeak_narrow1_summits.bed 44KB
run_callpeak_narrow0_summits.bed 44KB
run_refinepeak_w_ofile.bed 44KB
run_refinepeak_w_prefix_refinepeak.bed 44KB
run_callpeak_narrow5_summits.bed 44KB
run_bdgdiff_prefix_c3.0_cond1.bed 38KB
cond1.bed 28KB
run_bdgdiff_prefix_c3.0_cond2.bed 90B
cond2.bed 90B
common.bed 89B
run_bdgdiff_prefix_c3.0_common.bed 89B
run_callpeak_50kcontigs_summits.bed 0B
run_callpeak_narrow_revert_summits.bed 0B
run_bdgbroadcall_w_prefix_c2.0_C1.50_l200_g30_G800_broad.bed12 721KB
run_filterdup_result_pe.bedpe 1.14MB
run_callpeak_bedpe_broad_peaks.broadPeak 60KB
run_callpeak_bampe_broad_peaks.broadPeak 60KB
run_callpeak_broad_peaks.broadPeak 59KB
bfc.c 19KB
mag.c 17KB
unitig.c 15KB
cPosValCalculation.c 14KB
rld0.c 13KB
ksw.c 12KB
bubble.c 12KB
swalign.c 10KB
mrope.c 8KB
misc.c 8KB
rope.c 7KB
rle.c 5KB
htab.c 3KB
example.c 2KB
kthread.c 2KB
bseq.c 1KB
ChangeLog 79KB
cmbreps 0B
cmdlinetest 15KB
.dockerignore 440B
run_callpeak_bedpe_broad_peaks.gappedPeak 83KB
run_callpeak_bampe_broad_peaks.gappedPeak 83KB
run_callpeak_broad_peaks.gappedPeak 83KB
.gitignore 2KB
.gitmodules 122B
Input_12878_5M.bed.gz 33.59MB
CTCF_12878_5M.bed.gz 30.34MB
contigs50k.bed.gz 681KB
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