125 related articles for article (PubMed ID: 35866989)
1. LanceOtron: a deep learning peak caller for genome sequencing experiments.
Hentges LD; Sergeant MJ; Cole CB; Downes DJ; Hughes JR; Taylor S
Bioinformatics; 2022 Sep; 38(18):4255-4263. PubMed ID: 35866989
[TBL] [Abstract][Full Text] [Related]
2. RECAP reveals the true statistical significance of ChIP-seq peak calls.
Chitpin JG; Awdeh A; Perkins TJ
Bioinformatics; 2019 Oct; 35(19):3592-3598. PubMed ID: 30824903
[TBL] [Abstract][Full Text] [Related]
3. AIAP: A Quality Control and Integrative Analysis Package to Improve ATAC-seq Data Analysis.
Liu S; Li D; Lyu C; Gontarz PM; Miao B; Madden PAF; Wang T; Zhang B
Genomics Proteomics Bioinformatics; 2021 Aug; 19(4):641-651. PubMed ID: 34273560
[TBL] [Abstract][Full Text] [Related]
4. Unsupervised contrastive peak caller for ATAC-seq.
Vu HTH; Zhang Y; Tuteja G; Dorman KS
Genome Res; 2023 Jul; 33(7):1133-1144. PubMed ID: 37217250
[TBL] [Abstract][Full Text] [Related]
5. annoPeak: a web application to annotate and visualize peaks from ChIP-seq/ChIP-exo-seq.
Tang X; Srivastava A; Liu H; Machiraju R; Huang K; Leone G
Bioinformatics; 2017 May; 33(10):1570-1571. PubMed ID: 28169395
[TBL] [Abstract][Full Text] [Related]
6. NoPeak: k-mer-based motif discovery in ChIP-Seq data without peak calling.
Menzel M; Hurka S; Glasenhardt S; Gogol-Döring A
Bioinformatics; 2021 May; 37(5):596-602. PubMed ID: 32991679
[TBL] [Abstract][Full Text] [Related]
7. CoCoNet: an efficient deep learning tool for viral metagenome binning.
Arisdakessian CG; Nigro OD; Steward GF; Poisson G; Belcaid M
Bioinformatics; 2021 Sep; 37(18):2803-2810. PubMed ID: 33822891
[TBL] [Abstract][Full Text] [Related]
8. ReliableGenome: annotation of genomic regions with high/low variant calling concordance.
Popitsch N; ; Schuh A; Taylor JC
Bioinformatics; 2017 Jan; 33(2):155-160. PubMed ID: 27605105
[TBL] [Abstract][Full Text] [Related]
9. A flexible ChIP-sequencing simulation toolkit.
Zheng A; Lamkin M; Qiu Y; Ren K; Goren A; Gymrek M
BMC Bioinformatics; 2021 Apr; 22(1):201. PubMed ID: 33879052
[TBL] [Abstract][Full Text] [Related]
10. epic2 efficiently finds diffuse domains in ChIP-seq data.
Stovner EB; Sætrom P
Bioinformatics; 2019 Nov; 35(21):4392-4393. PubMed ID: 30923821
[TBL] [Abstract][Full Text] [Related]
11. GenoGAM: genome-wide generalized additive models for ChIP-Seq analysis.
Stricker G; Engelhardt A; Schulz D; Schmid M; Tresch A; Gagneur J
Bioinformatics; 2017 Aug; 33(15):2258-2265. PubMed ID: 28369277
[TBL] [Abstract][Full Text] [Related]
12. NanoSNP: a progressive and haplotype-aware SNP caller on low-coverage nanopore sequencing data.
Huang N; Xu M; Nie F; Ni P; Xiao CL; Luo F; Wang J
Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36548365
[TBL] [Abstract][Full Text] [Related]
13. Unified Analysis of Multiple ChIP-Seq Datasets.
Ma G; Babarinde IA; Zhuang Q; Hutchins AP
Methods Mol Biol; 2021; 2198():451-465. PubMed ID: 32822050
[TBL] [Abstract][Full Text] [Related]
14. DiffChIPL: a differential peak analysis method for high-throughput sequencing data with biological replicates based on limma.
Chen Y; Chen S; Lei EP
Bioinformatics; 2022 Sep; 38(17):4062-4069. PubMed ID: 35809062
[TBL] [Abstract][Full Text] [Related]
15. piPipes: a set of pipelines for piRNA and transposon analysis via small RNA-seq, RNA-seq, degradome- and CAGE-seq, ChIP-seq and genomic DNA sequencing.
Han BW; Wang W; Zamore PD; Weng Z
Bioinformatics; 2015 Feb; 31(4):593-5. PubMed ID: 25342065
[TBL] [Abstract][Full Text] [Related]
16. Deep-learning optimized DEOCSU suite provides an iterable pipeline for accurate ChIP-exo peak calling.
Bang I; Lee SM; Park S; Park JY; Nong LK; Gao Y; Palsson BO; Kim D
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36702751
[TBL] [Abstract][Full Text] [Related]
17. ATAC-DEA: A Web-Based ATAC-Seq Data Differential Peak and Annotation Analysis Application.
Zhang S; Wang S
J Comput Biol; 2023 Mar; 30(3):337-345. PubMed ID: 36656543
[TBL] [Abstract][Full Text] [Related]
18. ChIP-R: Assembling reproducible sets of ChIP-seq and ATAC-seq peaks from multiple replicates.
Newell R; Pienaar R; Balderson B; Piper M; Essebier A; Bodén M
Genomics; 2021 Jul; 113(4):1855-1866. PubMed ID: 33878366
[TBL] [Abstract][Full Text] [Related]
19. BinQuasi: a peak detection method for ChIP-sequencing data with biological replicates.
Goren E; Liu P; Wang C; Wang C
Bioinformatics; 2018 Sep; 34(17):2909-2917. PubMed ID: 29684098
[TBL] [Abstract][Full Text] [Related]
20. Sensitive and robust assessment of ChIP-seq read distribution using a strand-shift profile.
Nakato R; Shirahige K
Bioinformatics; 2018 Jul; 34(14):2356-2363. PubMed ID: 29528371
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]