Search results for: signatures
An omics signature is a high‐dimensional readout of cellular state change that provides information about the biological processes affected by the perturbation which underlie the post‐perturbation phenotype of the cell. The signature in itself also provides information, although not always directly discernable, about the molecular mechanisms by which the perturbation causes observed changes. If we...
1. Search is a very important part of this portal given that the number of LINCS datasets and precomputed signatures is constantly growing. One is able to search for a LINCS dataset and/or precomputed signature of interest on iLINCS portal in a couple of ways. In the example below, we will search for a precomputed signatures for MCF7 cell line (the example of locating LINCS dataset of interest is...
An experiment may have a number of samples which are organized in different groups (sample subgroupings). One may wish to restrict analysis to only a subset of all the available samples for an experiment. If you are interested in the analysis of differentially expressed genes between two groups of samples, you may create a two-group sample differential expression signature by clicking "Create...
The iLINCS (Integrative LINCS) portal portal facilitates analysis of transcriptional drug signatures, and search for and analysis of groups of concordant transcriptional signatures of different drugs. The transcriptional signatures of chemical perturbagen activity in the iLINCS portal are constructed based on the Broad L1000 assay data. Each signature consists of the average z-scores and...
Transcriptional signatures of DrugMatrix. Signatures consist of differential gene expression and associated p-values for ~ 13,000 genes.
1. One may be interested to see all the metadata available for a particular precomputed signature. Let's say we would like to see more information for "LINCSCP_131839" signature. Let's click on the signature title as shown in the figure below.
2. As seen in the figure below, clicking on the signature title, opens up a new window containing a landing page for that particular signature. Similar...
In the "Signatures" pipeline, you may explore, analyze and visualize over 200,000 pre-computed signatures (i.e. list of "scores" (activity levels) for a list of genes or for all genes in the genome "genome-wide signatures"). One would land on the Signatures landing page by clicking "Signatures" on the iLINCS portal header.
As shown in the figure above, there are 9 pre-computed signature libraries...
1. One may also search for pre-computed signatures with pharmacological actions. To do this, let's click "Find Signatures with Pharmacological Actions" button on the bottom of Signatures pipeline landing page as shown below.
2. Clicking "Find Signatures with Pharmacological Actions" button will open a search field to input desired pharmacological actions as seen in the figure below. iLINCS will...
Transcriptional signatures constructed by comparing sample groups within the collection of public domain transcriptional dataset (GEO GDS collection). Each signature consists of differential expressions and associated p-values for all genes.
Transcriptional signatures of perturbagen activity constructed based on the version 2 of the original Connectivity Map dataset using Affymetrix expression arrays. Each signature consists of differential expressions and associated p-values for all genes when comparing perturbagen treated cell lines with appropriate controls.
Depending on the exact type of the query signature, the connectivity analysis with libraries of
pre‐computed iLINCS signature are computed using different connectivity metric.
If the query signature is selected from iLINCS libraries of pre‐computed signatures, the
connectivity with all other iLINCS signatures is pre‐computed using the extreme Pearson’s
correlation signed significances of all...
iLINCS pre-calculated signature connectivity is based on extreme correlation analysis, on the other hand, the uploaded signatures' similarity is based on weighted correlation calculation, please see the method section (https://www.nature.com/articles/s41467-022-32205-3).
In the following example, we will try to identify a signature(s) that would reverse activated Estrogen receptor transcriptional signature profile. First, we will select Estradiol treatment perturbagen signature in MCF7 (ER+ breast cancer cell line) and then will identify highly disconnected (opposite) signature(s) to reverse its transcriptional signature profile via either gene loss-of-function...
In the following work-flow example, we will start with a prototypical drug and will identify sets of drugs that have similar transcriptional signatures. Moreover, we will also pinpoint genes and pathways that are affected by the drug.
1. First, let's open Signatures Pipeline starting with the iLINCS homepage as shown below.
2. This will take you to a Signatures pipeline landing page that lists...
"Create a signature" function generates a two-group sample differential expression signature within a selected dataset using top 100 differentially expressed genes between the groups as seen in the figure below. You may adjust the number of included genes for the signature creation. You can select a different set of differentially expressed genes based on different cutoff (fold change and p-values...
In the following example, we will start with a gene knockdown (loss-of-function) transcriptional signature and will try to identify a drug or sets of drugs that have opposite transcriptional signatures. For this example, we will look at MTOR gene knockdown in PC3, prostate cancer cells; will compare its transcriptional signature to the known MTOR inhibitor drug, Sirolimus (Rapamycin) signature and...
Transcriptional signatures of perturbations by small molecules based on L1000 assay. Signatures were created by aggregating (ie averaging) Level 4 data for biological replicates as defined by the signatures metadata. Only signatures designated to be reproducible and self-connected ("gold") by the Broad institute are represented. The signatures consist of differential gene expressions and p-values...
Transcriptional signatures of gene overexpression based on L1000 assay. The signatures consist of differential gene expressions and p-values for 978 Landmark Genes measured by L1000 assay. The signatures were created by aggregating (ie averaging) Level 4 data for biological replicates as defined by the signatures metadata. Only signatures designated to be reproducible and self-connected ("gold...
The transcriptomics or proteomics signature is constructed by comparing expression levels of
two groups of samples (treatment group and baseline group) using Empirical Bayes linear model
implemented in the limma package. For the GREIN collection of GEO RNA‐seq datasets, the
signatures are constructed using the negative‐binomial generalized linear model as implemented
in the edgeR package.
Transcriptional signatures were constructed by further aggregating signatures of individual short hairpin RNA perturbations. The signatures are based only on the 978 Landmark Genes measured directly by the L1000 assay. The signatures for individual shRNA were created by aggregating (averaging) Level 4 data for biological replicates as defined by the signatures metadata. The signatures of...
Signatures of perturbations assayed by P100 against 96 phosphopeptide probes and GCP assay against ~60 probes that monitor combinations of post-translational modifications on histones. The data is generated by using mass spectrometry techniques to characterize proteome level molecular signatures of responses to small molecule and genetic pertubations in a number of different cell lines.
Transcriptional signatures constructed by comparing sample groups within the collection of public domain transcriptional dataset (EBI Array Express collection). Each signature consists of differential expressions and associated p-values for all genes.
These transcriptomic signatures were made using data from the Cancer Therapeutics Response Portal (CTRP) project. The data includes 860 cancer cell lines and combines basal (untreated) gene expression with measurements of sensitivity to 481 anti-cancer compounds. Drug sensitivity was measured as cell viability (ATP levels measured by CellTiter-Glo®) over a sixteen-point concentration-response...
Transcription factor (TF) binding signatures constructed using ENCODE ChiP-seq data. Each signature consists of genome scale (i.e. for each gene) scores and probabilities of regulation by the given TF in the specific context (cell line and treatment). These signatures were developed using our in-house TREG methodology.
True REGulation (TREG) method integrates Transcription factor (TF) information...
216,105 transcriptional signatures of cellular perturbations constructed using the LINCS pilot phase L1000. The chemical perturbagen and individual shRNA signatures are created by aggregating (ie averaging) Level 4 data for biological replicates as defined by the signatures metadata. Only signatures designated to be reproducible and self-connected ("gold") by the Broad institute are represented...
The perturbagen connectivity analysis compares the query signature to all signatures
for a given perturbagen as a group, thus extending the pair-wise connectivity analysis
to account for diversity of responses in different cellular contexts. This
is accomplished by performing the enrichment analysis of individual connectivity
scores between the query signature and set of all L1000 signatures of a...
The iLINCS (Integrative LINCS) portal is an web platform for analysis of LINCS data and signatures. The portal provides biologists-friendly user interfaces for analyzing transcriptomics and proteomics LINCS datasets. iLINCS web tools facilitate statistical analysis to identify differentially expressed genes and proteins; bioinformatics analysis to identify affected networks, pathway and gene lists...
Matching directly transcriptional signatures of a disease with negatively correlated transcriptional signatures of chemical perturbations (CP) underlies the Connectivity Map (CMap) approach to identifying potential drug candidates. Similarly, correlating signatures of chemical perturbagens with genetic perturbations of specific genes has been used to identify putative targets of drugs and other...
iLINCS (Integrative LINCS) is an integrative web platform for analysis of LINCS data and signatures. The portal provides biologists-friendly user interfaces for analyzing transcriptomics and proteomics LINCS datasets. The portal integrates R analytical engine via several R tools for web-computing (rserve, opencpu, Shiny, rgl) and DCIC developed web tools and applications (FTreeView, Enrichr) into...
One may wish to restrict analysis to only a subset of all the available samples for an experiment. We have described earlier how to generate a two-group sample differential expression signature by clicking "Create a Signature". The following section will explain how to find differentially expressed genes between multiple groups of samples.
1. To find differentially expressed genes between multiple...
The Library of Integrated Network-Based Cellular Signatures (LINCS) Program aims to create a network-based understanding of biology by cataloging changes in gene expression and other cellular processes that occur when cells are exposed to a variety of perturbing agents.
The LINCS Data and Signature Generation Centers produce a variety of data for the library. For such data to be standardized...
Tutorial-1: iLINCS landing page Navigation.
Tutorial-2: Analyze my genes against LINCS datasets.
Tutorial-3: Analyze LINCS transcriptomic and proteomic datasets.
Tutorial-4: Analyze a drug signature and find other drugs with similar signatures.
Tutorial-5: Datasets workflow.
Tutorial-6: Signature workflow.
Tutorial-7: Genes workflow.
As seen in the figure below, clicking "Analyze" button next to any of the datasets, opens up a new window containing a landing page for that particular dataset.
The figure above shows the landing page for the dataset with LINCS ID # EDS-1014. The typical dataset landing page layout contains a short dataset description, reference, exploratory tools and dataset analysis tools. On the bottom of the...
"Genes" pipeline allows a query of genes of interest against LINCS data. One may start a query by inputing a list of genes via Entrez gene IDs or gene symbols separated by comma in the search field and clicking "Search for set of gene symbols or IDs". This section describes how to submit your own list of genes for analysis.
The figure above shows the screen to submit your own list of genes. You...
1. Search is a very important part of this portal given that the number of LINCS datasets and precomputed signatures is constantly growing. One is able to search for a LINCS dataset and/or precomputed signature of interest on iLINCS portal in a couple of ways. In the example below, we will search for LINCS dataset for MCF7 cell line (the example of locating precomputed signature of interest is...
L1000CDS2 is an ultra-fast LINCS L1000 Characteristic Direction Signature Search Engine. (https://maayanlab.cloud/L1000CDS2/#/index)
The P100 assay is a mass spectrometry-based targeted phosphoproteomic assay that detects and quantifies a representative set of 96 phosphopeptide probes. Phosphopeptides are enriched via an automated protocol and then mixed with a set of isotopically-labeled internal standards that correspond to the analytes in the P100 assay. This mixture is introduced into a mass spectrometer using ultra-high...
You may interrogate gene and protein expression patterns in datasets and signatures for a selected set of genes of interest. In the example below, we are going to query a chosen set of genes in one of the LINCS datasets; we will interrogate MEP_LINCS RNA-seq dataset EDS-1014 for user-submitted list of genes of interest.
1. First, let's open Genes pipeline starting with the iLINCS homepage as...
L1000 fireworks display (L1000FWD) is a web application that provides interactive visualization of over 16000 drug and small-molecule induced gene expression signatures. (https://maayanlab.cloud/L1000FWD/)
Use case-1: Detecting and modulating mTOR pathway signaling.
Use case-2: Proteo-genomics analysis of cancer driver events in breast cancer.
Use case-3: Using iLINCS for analysis of transcriptional signature of COVID-19 infection.
Citation: Connecting omics signatures of diseases, drugs, and mechanisms of actions with iLINCS
Marcin Pilarczyk, Mehdi Fazel-Najafabadi, Michal Kouril, Behrouz Shamsaei, Juozas Vasiliauskas, Wen Niu, Naim Mahi, Lixia Zhang, Nicholas A. Clark, Yan Ren, Shana White, Rashid Karim, Huan Xu, Jacek Biesiada, Mark F. Bennett, Sarah E. Davidson, John F. Reichard, Kurt Roberts, Vasileios Stathias, Amar...
Global Chromatin Profiling (GCP) technology is a mass spectrometry-based assay to identify and quantify post-translational modifications on histone proteins from bulk chromatin (i.e. measuring changes in epigenetic marks on histones). Around 60 different combinations of histone modifications can be quantified on H3, with even more possible combinations on H4, H2A (including isoforms), and H2B...