From 7223582f3e77d05580a7244ec8e45b600e3a185c Mon Sep 17 00:00:00 2001 From: kchu25 Date: Fri, 16 Jun 2023 17:07:49 -0400 Subject: [PATCH] update readme --- README.md | 43 +++++++++++++++++++++++++++++++----------- imgs/re_gap.png | Bin 0 -> 141859 bytes imgs/re_high_pval.png | Bin 0 -> 212389 bytes imgs/re_top.png | Bin 0 -> 270705 bytes 4 files changed, 32 insertions(+), 11 deletions(-) create mode 100644 imgs/re_gap.png create mode 100644 imgs/re_high_pval.png create mode 100644 imgs/re_top.png diff --git a/README.md b/README.md index 8400563..84beba8 100644 --- a/README.md +++ b/README.md @@ -13,24 +13,24 @@ This code repository corresponds to the paper [Finding Motifs Using DNA Images D - [Motivation](#Motivation) - [Installation](#Installation) - [Usage](#Usage) -- [Interpret the results](#Interpret-the-results) - [Software requirements](#Software-requirements) - [Hardware requirements](#Hardware-requirements) - [Adjustable Hyperparameters](#Adjustable-Hyperparameters) +- [Interpret the results](#Interpret-the-results) - [Cite this work](#Cite-this-work) - [Contact](#Contact) ## Motivation -Traditional methods such as [STREME](https://meme-suite.org/meme/doc/streme.html) and [HOMER](http://homer.ucsd.edu/homer/motif/) excel at efficiently finding the primary motifs of a transcription factor. This begs the question -- why do we need another motif discovery method? +Traditional methods such as [STREME](https://meme-suite.org/meme/doc/streme.html) and [HOMER](http://homer.ucsd.edu/homer/motif/) excel at efficiently finding the primary motifs of a transcription factor. This raises the question: why do we require an additional motif discovery method? -Because there may be more patterns in the datasets that aren't fully captured. This is even more so in in-vivo datasets such as ChIP-Seq. +Because there may be more patterns in the datasets that aren't fully captured. This is especially evident for context-dependent binding sites, such as C2H2 zinc finger, and cooperative binding patterns observed in in-vivo datasets from ChIP-Seq. -Our work finds that more than half the ChiP-Seq datasets that we've selected from the database [JASPAR 2022](https://jaspar.genereg.net/) containes transposable elements that overlaps the primary binding sites. For instance, see [NFE2L2](https://en.wikipedia.org/wiki/NFE2L2), [YY1](https://en.wikipedia.org/wiki/YY1), [STAT1](https://en.wikipedia.org/wiki/STAT1), [SRF](https://en.wikipedia.org/wiki/Serum_response_factor), [AR](https://en.wikipedia.org/wiki/Androgen_receptor) ([Manuscript Figure 4](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btad378/7192989?utm_source=advanceaccess&utm_campaign=bioinformatics&utm_medium=email)): +Our work reveals that over half of the ChIP-Seq datasets selected from the [JASPAR 2022](https://jaspar.genereg.net/) database contain transposable elements that overlap the primary binding sites. For instance, see [NFE2L2](https://en.wikipedia.org/wiki/NFE2L2), [YY1](https://en.wikipedia.org/wiki/YY1), [STAT1](https://en.wikipedia.org/wiki/STAT1), [SRF](https://en.wikipedia.org/wiki/Serum_response_factor), [AR](https://en.wikipedia.org/wiki/Androgen_receptor) ([Manuscript Figure 4](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btad378/7192989?utm_source=advanceaccess&utm_campaign=bioinformatics&utm_medium=email)): ![image info](./imgs/long_1.png) -These long patterns pose challenges for traditional k-mer-based methods as space complexity is exponential. +These long patterns present challenges for traditional k-mer-based methods due to their exponential space complexity. Furthermore, many datasets exhibit a large presence of gapped motifs. For example, we found that ChIP-Seq datasets from both [JASPAR](https://jaspar.genereg.net/) and [Factorbook](https://www.factorbook.org/) often contains gapped motifs ([Manuscript Figure 6](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btad378/7192989?utm_source=advanceaccess&utm_campaign=bioinformatics&utm_medium=email)): @@ -38,12 +38,12 @@ Furthermore, many datasets exhibit a large presence of gapped motifs. For exampl and the spacers that characterized the gapped motifs [can be widely varied (Supplementary Material Figure 2)](./imgs/gaps.png). -Last, there may be cooperative binding patterns, e.g., ([Manuscript Figure 5](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btad378/7192989?utm_source=advanceaccess&utm_campaign=bioinformatics&utm_medium=email)): +Last, there are cooperative binding patterns, e.g., ([Manuscript Figure 5](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btad378/7192989?utm_source=advanceaccess&utm_campaign=bioinformatics&utm_medium=email)): ![image info](./imgs/avsec3.png) -for which we see consecutive occurrences of [Oct4](https://en.wikipedia.org/wiki/Oct-4) and cooccurrence of [Oct4](https://en.wikipedia.org/wiki/Oct-4) and [Zic3](https://en.wikipedia.org/wiki/ZIC3), in addition to the Oct4-Sox2 motif. The presence of gapped motifs and cooperative binding patterns presents challenges for k-mer-based methods, as these methods are primarily designed to detect ungapped motifs. +for which we see consecutive occurrences of [Oct4](https://en.wikipedia.org/wiki/Oct-4) and cooccurrence of [Oct4](https://en.wikipedia.org/wiki/Oct-4) and [Zic3](https://en.wikipedia.org/wiki/ZIC3), in addition to the Oct4-Sox2 motif. The presence of gapped motifs and cooperative binding patterns presents challenges for k-mer-based methods as well, as these methods are primarily designed to detect ungapped motifs. ## Installation @@ -68,10 +68,6 @@ discover_motifs("home/shane/mydata/fasta.fa", "home/shane/mydata/out/") ```` -## Interpret the results -(coming soon) - - ## Software requirements This package currectly requires [Weblogo](http://weblogo.threeplusone.com/manual.html#download) for PWM plotting. Install Weblogo by running the following command with python3 and pip3: ```bash @@ -89,6 +85,31 @@ Currently, a GPU is required for this package as it utilizes [CUDA.jl](https://g discover_motifs(, ; num_epochs=10) ```` +## Interpret the results + +### Summary page +Once the motif discovery process is complete, a summary.html page is generated in the output folder, providing a comprehensive overview of the results. + +For instance, here is an example result page showcasing data from the [SP1 transcription factor from JASPAR](https://jaspar.genereg.net/matrix/MA0079.3/): + +![image info](./imgs/re_top.png) + +The top of the result page has +- labels: A number assigned for each discovered motifs. + * Each label is hyperlinked to a text file in TRANSFAC format that can be parsed. +- p-value: The satistical significance of the discovered motif using Fisher exact test ([Manuscript section 2.7.2](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btad378/7192989?utm_source=advanceaccess&utm_campaign=bioinformatics&utm_medium=email)). +- instances: An estimate of the number of occurrences in the dataset ([Manuscript section 2.7.3](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btad378/7192989?utm_source=advanceaccess&utm_campaign=bioinformatics&utm_medium=email)). +- logo: Position weight matricies. + + +Note that in in-vivo datasets, especially for zinc-finger proteins, a large number of motifs can be observed, often characterized by variable spacings in their binding sites. + +![image info](./imgs/re_gap.png) + +### Statistically insignificant motifs +Some of the motifs shown here have their p-values in grey, which typically suggests that these motifs are not particularly enriched in the dataset. 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